System for estimating the environmental impact of agricultural land

Abstract

We provide a system that visualizes the various environmental impacts on agricultural land. [Solution] The agricultural land environmental load visualization system according to the present invention comprises: an object information acquisition unit that acquires object information to be visualized for environmental load; a spectral information acquisition unit that acquires a time-series spectrum; a meteorological information acquisition unit that acquires meteorological information; a feature information estimation unit that estimates feature information including photosynthetic pigment index and surface soil moisture index based on the time-series spectrum; a growth information estimation unit that estimates growth information in the evaluation area; a cultivation information estimation unit that estimates cultivation information in the evaluation area; a soil information estimation unit that estimates soil information in the evaluation area; an environmental load information estimation unit that estimates environmental load information in the evaluation area based on meteorological information, growth information, soil information, and cultivation information; and an output unit that visualizes and displays the calculated environmental load information.

Description

Technical Field

[0001] The present invention relates to a system for visualizing the environmental load of agricultural land.

Background Art

[0002] As the background art in this technical field, there is Japanese Patent Application Laid-Open No. 2023-511926 (Patent Document 1). This publication describes "providing a method, apparatus, and computer program product for estimating crop type or sowing date or both. In some embodiments, past crop growth time series and a plurality of simulated crop growth time series are determined, and the past time series is matched with each of the simulated time series to determine the estimated crop type or sowing date or both" (see the abstract).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In Patent Document 1, a mechanism is described in which one simulated time series can be determined for each combination of crop type / sowing date within a set of one or more crop types and one or more sowing dates based on past crop data. However, in Patent Document 1, a system for visualizing various environmental loads of agricultural land has not been studied. Therefore, the present invention provides a system for visualizing various environmental loads of agriculture.

Means for Solving the Problems

[0005] In order to solve the above problems, for example, the configuration described in the claims is adopted.

Effects of the Invention

[0006] According to the present invention, a system can be provided that visualizes various environmental burdens on agricultural land. Other issues, configurations, and effects not mentioned above will be clarified by the following description of the embodiments. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 shows an example of a configuration diagram for an environmental load visualization system. [Figure 2] Figure 2A shows an example of the multispectral characteristics of a cultivation area. Figure 2B shows an example of the multispectral characteristics of a soil area. [Figure 3] Figure 3 shows an example of the hardware configuration of the management server. [Figure 4] Figure 4A shows an example of satellite imagery. Figure 4B shows an example of multispectral information obtained from satellite imagery. [Figure 5] Figure 5A shows an example of feature information. Figure 5B shows an example of reference information. [Figure 6] Figure 6A shows an example of cultivation information. Figure 6B shows an example of growth information. [Figure 7] Figure 7A shows an example of soil information. Figure 7B shows an example of environmental impact information. [Figure 8] Figure 8 shows an example of an input information acquisition flow for acquiring information from an external source. [Figure 9] Figure 9 shows an example of a visualization flow for environmental information. [Figure 10] Figure 10 shows an example of the feature information estimation flow. [Figure 11] Figure 11 shows an example of the estimation flow of reference information. [Figure 12] Figure 12 shows an example of the estimation flow of cultivation information. [Figure 13] Figure 13 shows an example of the estimation flow for growth information. [Figure 14] FIG. 14 is a diagram showing an example of an estimation flow of soil information. [Figure 15] FIG. 15 is a diagram showing an example of an estimation flow of environmental load information. [Figure 16] FIG. 16 is a diagram showing an example of the hardware configuration of a user terminal.

Embodiments for Carrying Out the Invention

[0008] <1. Overall Configuration of the System> FIG. 1 is an example of a configuration diagram of an environmental load visualization system 1 (hereinafter, also referred to as the environmental load visualization system 1 or simply the system 1). The outline of the representative functions of the system 1 will be described. The system 1 has a function of acquiring time-series multi-spectrum information (multi-spectrum surface reflectance data) about an area to be evaluated and estimating various types of information necessary for field management using its characteristics.

[0009] The system 1 identifies an area to be evaluated, such as a vegetation area, from the acquired multi-spectrum information. The multi-spectrum information acquired from the field has the following characteristics. 1) During the year, vegetation periods and soil exposure periods repeat. 2) The vegetation periods and soil exposure periods within an area generally have the same start and end timings. 3) In areas where the same crop is planted, the multi-spectrum reflectance characteristics and the degree of growth are relatively uniform. Using such characteristics, the system 1 identifies the vegetation type, cultivation state, growth state, soil state, and environmental load state in the evaluation area. Note that information regarding the division of the evaluation area is stored in advance.

[0010] Among the evaluation areas, the area where crops are cultivated has the following spectral characteristics. That is, in the process of plant growth, the concentration of pigment molecules with characteristic light absorption characteristics such as chlorophyll and carotenoids for photosynthesis in the plant body increases, and the coverage rate of the plant body on the ground surface increases. An example of the multi-spectral characteristics at this time will be described.

[0011] Figure 2A is a diagram showing an example of the multi-spectral characteristics of the cultivated area. In this graph, for the multi-spectral reflectance observed from the vegetation area on different three days, the wavelength is taken on the horizontal axis and the reflectance is taken on the vertical axis, showing the reflectance values for each wavelength. As shown in Figure 2A, the multi-spectral characteristics of the vegetation area show characteristic trends due to the light absorption characteristics of the molecules contributing to the growth activities of the plants described above.

[0012] Specifically, in the graph shown in Figure 2A, the blue reflectance (B2) and the red reflectance (B4) decrease significantly, the green reflectance (B3) and the near-infrared reflectance (B8) increase significantly, and the near-infrared reflectance (B9) becomes flat. That is, the curves of B2~B4 are significantly convex upward, the curves of B3~B5 are significantly convex downward, and the curves of B6~B8 are significantly convex upward. This tendency is common in different three days. Therefore, when similar multi-spectral characteristics are confirmed for the multi-spectral information obtained from a specific evaluation area, it can be estimated that the area is a vegetation area where crops are cultivated. The details of the estimation process will be described later.

[0013] On the other hand, among the evaluation areas, the area where the soil is exposed shows different multi-spectral characteristics. Figure 2B is a diagram showing an example of the multi-spectral characteristics of the soil area. In this graph, for the multi-spectral reflectance observed from the soil area on different three days, the wavelength is taken on the horizontal axis and the reflectance is taken on the vertical axis, showing the reflectance values for each wavelength. As shown in Figure 2B, the multi-spectral characteristics of the soil area show a relatively flat tendency at all wavelengths.

[0014] In other words, the multispectral characteristics of reflectance are mainly determined by the amount of iron and manganese oxides, humus produced during the decomposition of organic matter, and moisture content. However, because soil is composed of a wide variety of materials, biases in reflectance across wavelengths are less likely to occur. This trend is consistent across three different days. Therefore, if relatively flat characteristics without prominent absorption bands, such as those found in vegetation, are observed in the multispectral information obtained from a specific evaluation area, that area can be estimated to be an area where soil is exposed. Details of the estimation process will be described later.

[0015] System 1 then extracts the multispectral characteristics to be evaluated from the multispectral information and performs a process to estimate cultivation information, vegetation information, soil information, and environmental load information. The configuration of System 1 is described in detail below.

[0016] As shown in Figure 1, the environmental load visualization system 1 comprises multiple user terminals 102 and a management server 103, with each user terminal 102 connected to the management server 103 via a network. The network can be wired or wireless, and each terminal can send and receive information via the network.

[0017] Each terminal and management server 103 of the environmental load visualization system 1 may be a mobile device such as a smartphone, tablet, mobile phone, or personal digital assistant (PDA), or a wearable device such as glasses, a wristwatch, or clothing. Alternatively, it may be a stationary or portable computer, or a server located in the cloud or on a network. Functionally, it may also be a VR (Virtual Reality) terminal, an AR (Augmented Reality) terminal, or an MR (Mixed Reality) terminal. Alternatively, it may be a combination of multiple such terminals. For example, a combination of one smartphone and one wearable device can logically function as a single terminal. Other types of information processing terminals may also be used.

[0018] The management server 103 and terminals of the environmental load visualization system 1 each include a processor that runs the operating system, applications, and programs; main memory such as RAM (Random Access Memory); auxiliary storage such as IC cards, hard disk drives, SSDs (Solid State Drives), and flash memory; a communication control unit such as a network card, wireless communication module, or mobile communication module; input devices such as a touch panel, keyboard, mouse, voice input, and camera; and output devices such as monitors and displays. The output devices may also be devices or terminals that transmit information for output to external monitors, displays, printers, or other equipment.

[0019] The main memory stores various programs and applications (also referred to as modules or processing units), and the processor executes these programs and applications to realize each functional element of the overall system. These modules (processing units) may be implemented in hardware, such as through integration. Furthermore, each module may be an independent program or application, or it may be implemented as a subprogram or function within a single integrated program or application.

[0020] In this specification, each module is described as the entity (subject) that performs the processing; however, in reality, the processor that processes various programs and applications (modules) executes the processing. The auxiliary storage device stores various databases (DBs). A "database" is a functional element (storage unit) that stores a data set so that it can handle any data manipulation (e.g., extraction, addition, deletion, overwriting, etc.) from the processor or an external computer. The implementation method of a database is not limited; for example, it may be a database management system, spreadsheet software, or text files such as XML or JSON.

[0021] <2. User Terminal Configuration> Next, the configuration of the user terminal 102 will be described. Figure 16 shows an example of the hardware configuration of the user terminal 102. The user terminal 102 is a terminal device such as a smartphone, tablet, notebook PC, or desktop PC.

[0022] As shown in Figure 16, the main memory 201 of the user terminal 102 stores programs and applications such as the target area evaluation module 211 and the server cooperation module 212. The processor 203 executes these programs and applications to realize each functional element of the user terminal 102.

[0023] The target area evaluation module 211 works in cooperation with the server integration module 212 to output evaluation results such as environmental load for an area specified by the user. The server integration module 212 works in conjunction with other servers, such as the management server 103, to obtain evaluation results such as environmental load for an area specified by the user. The specific processing performed by each of these modules will be described later.

[0024] <3. Configuration of Management Server 103> Figure 3 shows an example of the hardware configuration of the management server 103. The management server 103 is composed of, for example, a server located on the cloud. The main memory 301 stores the following programs and applications, and the processor 203 executes these programs and applications to realize the various functional elements of the management server 103. • Input information acquisition unit 311 • Target information acquisition unit 312 • Weather information acquisition unit 313 • Spectrum information acquisition unit 314 • Feature information estimation unit 315 ·Reference information estimation unit 316 ·Cultivation information estimation department 317 ·Growth information estimation section 318 • Soil information estimation unit 319 ·Environmental load information estimation unit 320 Output section 321 The functions of each of these functional elements are described below.

[0025] <3-1. Overview of each module's functions> Next, we will explain the functions of each functional element stored in the main memory 301 in order.

[0026] (Input information acquisition unit 311) The input information acquisition unit 311 acquires various types of information entered by the user. The user enters actual and planned values ​​for cultivation information, growth information, and soil information. While this information may be estimated by the system, the user can also provide it as external input to correct the estimation results and improve accuracy. The input information acquisition unit 311 acquires the entered information and records it in the data tables described later. Details of the input information acquisition process will be described later.

[0027] (Target information acquisition unit 312) The target information acquisition unit 312 acquires information from the user regarding the period and area to be evaluated by System 1. The target information acquisition unit 312 records the acquired target information in the auxiliary storage device 302. Details of the target information will be described later.

[0028] (Weather information acquisition unit 313) The weather information acquisition unit 313 acquires temperature, solar radiation, precipitation, and humidity for a specified area and period from the weather database. Details of the weather information will be described later.

[0029] (Spectrum information acquisition unit 314) The spectral information acquisition unit 314 acquires spectral information, including time-series multispectral surface reflectance. The means for acquiring the time-series multispectral surface reflectance data can be any of the following: an Earth observation optical satellite, a drone, an aircraft, or a fixed-point camera, all of which are capable of taking images under the same conditions over time. The temporal resolution (data observation frequency) of the multispectral surface reflectance data must be sufficiently short (e.g., less than one week) compared to the crop cultivation period (several weeks). The spatial resolution must be sufficiently short (e.g., less than 20m) compared to the size of the crop cultivation area (tens of meters to thousands of meters). The time range for acquisition must be sufficiently long (e.g., several years) compared to the cultivation period.

[0030] (Feature information estimation unit 315) The feature information estimation unit 315 estimates and acquires unknown feature information indicating the growth status and soil characteristics of the target area based on the time-series multispectral information of the target area acquired by the spectral information acquisition unit 314. Specifically, it calculates vegetation indices such as the photosynthetic pigment index (CSI), extracts spectral characteristics for each growth stage, and further extracts the time period at which certain criteria are met as a feature period. The feature information estimation unit 315 records the obtained index values, spectral characteristics, and period information in the auxiliary storage device 302. Details regarding the calculation method for multispectral indexes and the conditions for period extraction will be described later.

[0031] (Reference information estimation unit 316) The reference information estimation unit 316 estimates and acquires unknown reference information, such as reference spectra and reference growing periods for each vegetation type and vegetation history, based on acquired characteristic information or measured information. It can also acquire known reference information input by the user, such as measured values ​​for each vegetation type and vegetation history provided by research institutions or experimental farms. Reference information refers to various types of information that indicate the typical spectral characteristics of vegetation and soil in the evaluation area, cultivation period, and yield. Furthermore, the reference information estimation unit 316 estimates standard characteristic values ​​for at least one type of information in the evaluation area, such as vegetation type, fertilization type, and vegetation history. The reference information estimation unit 316 records the acquired reference information in the auxiliary storage device 302. The specific contents and estimation methods of this reference information will be described in detail in the following section.

[0032] (Cultivation Information Estimation Department 317) The cultivation information estimation unit 317 estimates and acquires unknown cultivation information based on acquired characteristic information or other information. The cultivation information estimation unit 317 can also acquire known cultivation information entered by the user. Cultivation information refers to various types of information related to cultivation activities concerning vegetation in the evaluation area. The cultivation information estimation unit 317 records the acquired cultivation information in the auxiliary storage device 302. Details of the cultivation information and the cultivation information estimation process will be described later.

[0033] (Growth information estimation section 318) The growth information estimation unit 318 estimates and acquires unknown growth information based on acquired characteristic information or other information. The growth information estimation unit 318 can also acquire known growth information entered by the user. Growth information refers to various types of information regarding the growth status of vegetation in the evaluation area. The growth information estimation unit 318 records the acquired growth information in the auxiliary storage device 302. Details of the growth information and the growth information estimation process will be described later.

[0034] (Soil information estimation unit 319) The soil information estimation unit 319 estimates and acquires unknown soil information based on the estimated cultivation information and growth information. The soil information estimation unit 319 can also acquire known soil information entered by the user. Soil information refers to various types of information about the soil condition in the evaluation area. The soil information estimation unit 319 records the acquired soil information in the auxiliary storage device 302. Details of the soil information and the soil information estimation process will be described later.

[0035] (Environmental load information estimation unit 320) The environmental load information estimation unit 320 estimates and acquires unknown environmental load information based on the estimated growth information and soil information. Environmental load information refers to various types of information indicating the degree of environmental load in the evaluation area. The environmental load information estimation unit 320 records the acquired environmental load information in the auxiliary storage device 302. Details of the environmental load information and the environmental load information estimation process will be described later.

[0036] (Output section 321) The output unit 321 aggregates and outputs various types of information acquired by each of the aforementioned modules based on conditions including at least one of the following: by area, by vegetation type, and by period. The output unit 321 visualizes and displays the calculated environmental load information on a map in association with geographic information. Here, vegetation type is information used to uniquely link vegetation information that indicates the characteristics of vegetation. Vegetation type may be any of the following: item (rice, wheat, soybeans, root vegetables, etc.), variety (Koshihikari, Yumichikara, etc.), classification by light utilization efficiency (C4 plants, C3 plants, etc.), or classification by part of the harvested product (root vegetables, leafy and stem vegetables, root vegetables, etc.). Vegetation type is identified by vegetation information, vegetation characteristic information, and vegetation determination information. Furthermore, the output unit 321 can display or output various types of information not only on the map but also in various data formats and display formats.

[0037] <3-2. Details of each piece of information> Next, we will describe in detail the various types of information stored in the auxiliary storage device 302. (Target Information) The information to be evaluated includes, for example, the evaluation area and the evaluation period. Each of these items will be explained below in order.

[0038] [Evaluation Area] In this specification, an evaluation area refers to information used to uniquely identify an area where farmland or vegetation exists. Specific examples include an evaluation area ID, center coordinates, latitude and longitude range (latitude of the northern and southern ends, longitude of the eastern and western ends), boundary information based on polygonal shape, and area. If the area is subdivided into smaller sections, multispectral information may be managed for each smallest section (area division ID). Alternatively, the area division ID may be set using a 1-pixel unit as the smallest division in the observed ground surface reflectance image. The evaluation area is registered in the database on the auxiliary storage device 302 based on geographic coordinates and administrative division information entered from the user terminal 102.

[0039] [Evaluation period] In this invention, "period" refers to a value indicating the start, end, and unit of the period for evaluating vegetation. The unit of the period may be hours, days, weeks, months, or years. The start and end dates of the period may be in either the Gregorian calendar or the Japanese calendar.

[0040] (Weather information) Next, weather information includes, for example, temperature, solar radiation, precipitation, and humidity. Each of these items will be explained in order below.

[0041] [temperature] Temperature refers to time-series information on the temperature of the air near the ground in a designated evaluation area. The temperature resolution can be hourly, daily, weekly, monthly, or yearly. The unit of temperature can be absolute temperature (K), Fahrenheit (F), or Celsius (°C).

[0042] [Solar radiation] Solar radiation is time-series information on the solar energy reaching the ground surface in a designated evaluation area. Specifically, it includes the energy of direct light and the energy of scattered light. The time resolution of solar radiation can be hour, day, week, month, or year. The unit of solar radiation can be any unit that indicates the amount of energy per unit time per unit area, such as J / m² / h or W / m². It is also possible to consider the case where direct light is blocked by the topography of the ground surface, resulting in only scattered light energy. Furthermore, the energy of reflected light from buildings may also be considered.

[0043] [Precipitation] Precipitation is time-series information on the amount of water that falls from the atmosphere to the Earth's surface in a designated evaluation area. The resolution of precipitation can be hourly, daily, weekly, monthly, or yearly. The unit of precipitation can be any unit that represents the amount of water per unit time per unit area. For example, the unit may be mm / h.

[0044] [Humidity] Humidity is time-series information on the amount of water vapor in the atmosphere near the ground surface in a designated evaluation area. The resolution of humidity can be hourly, daily, weekly, monthly, or yearly. The unit of humidity can be any unit that represents the amount of water vapor relative to the saturated water vapor amount. For example, the unit may be %.

[0045] (Spectral information) Next, we will explain multispectral information. Figure 4A shows an example of a satellite image. Figure 4B shows an example of multispectral information obtained from a satellite image. As shown in Figure 4A, the satellite image captures the fields in the evaluation area. Figure 4B, for example, shows the reflectance for each wavelength in the multispectral surface reflectance (hereinafter, when simply referred to as "spectrum" in this specification, it means multispectral reflectance) contained in this image.

[0046] As shown in Figure 4B, spectral information specifically refers to information that records the reflectance of sunlight (amount of reflected sunlight / amount of incident sunlight) of the ground surface (soil surface or plant surface) at multiple wavelengths. Furthermore, spectral information is time-series information that changes over time. In other words, spectral information in this explanation is treated as time-series data that includes certain temporal elements.

[0047] As shown in Figure 4B, in this explanation, the wavelengths of each band are classified and represented as follows. ·Wavelength B2: 490nm (visible light: blue) Wavelength B3: 560nm (Visible light: Green) ·Wavelength B4: 665nm (visible light: red) ·Wavelength B5: 704nm (RedEdg1) ·Wavelength B6: 740nm (RedEdg2) ·Wavelength B7: 783nm (RedEdg3) ·Wavelength B8: 842nm (near infrared 1) ·Wavelength B8a: 865nm (near infrared 2)

[0048] It should be noted that this wavelength classification is merely for convenience, and the wavelength classification can be chosen arbitrarily. In other words, in the illustrated example, spectral information in a specific area is recorded chronologically for each of eight wavelengths, but the classification is not limited to this. Specifically, the wavelengths to be recorded are generally several wavelengths in the visible light range (450nm~680nm), several wavelengths in the boundary region between visible light and near-infrared (680nm~780nm), and several wavelengths in the near-infrared range (780nm~900nm). However, recording may be done using any wavelength division as long as at least four wavelengths are included: blue wavelengths (480nm~490nm), green wavelengths (540nm~570nm), red wavelengths (650nm~680nm), RedEdge (700nm~780nm), and near-infrared wavelengths (790nm~900nm).

[0049] As shown in Figure 4B, eight bands are illustrated in this embodiment, but the present invention is not limited to this configuration. The observation platform (artificial satellite, drone, aircraft, fixed camera, etc.), the number of bands, and the spectral range can be flexibly selected according to the farmland and observation purpose. By utilizing multiple bands in the visible to near-infrared region, the characteristics of soil and vegetation can be captured more accurately. Furthermore, when the observation platform is a satellite, calculating the surface reflectance requires highly accurate correction for scattering and absorption by atmospheric molecules and particulate matter such as aerosols. While the influence of atmospheric particulate matter such as aerosols is approximately 10%, it is desirable to improve this to 3% or less by accurately estimating the optical thickness of aerosols.

[0050] (Feature information) Next, we will explain the characteristic information. Characteristic information is information extracted from vegetation or soil characteristics (index, spectrum, and period information) based on time-series multispectral reflectance.

[0051] Figure 5A shows an example of feature information. As shown in Figure 5A, the feature information multispectral characteristics are composed of, for example, the following data table. • Feature Index Table • Features: Spectrum table • Feature Period Table Note that the characteristic information may also be composed of other data tables. The details of each of these data tables will be explained in order.

[0052] [Feature Index Table] The feature multispectral index table stores index values ​​representing the multispectral characteristics of plants under vegetation and non-vegetation conditions. These index values ​​are used to determine cultivation information and growth information. The characteristic multispectral index table associates the following indices with each area ID. ·Photosynthetic pigment index • Surface soil moisture index Each of these items will be explained below in order.

[0053] <Photosynthetic pigment index> The "photosynthetic pigment index" is a value that serves as an indicator of the photosynthetic pigment density of vegetation in an evaluation area corresponding to an area ID. The photosynthetic pigment index is calculated from the multispectral ground surface reflectance, taking advantage of the fact that chlorophyll and carotenoids, which are photosynthetic pigments of terrestrial plants, have distinctive absorption spectral characteristics. While NDVI (Normalized Difference Vegetation Index) is commonly used as a photosynthetic pigment index, NDVI has the problem of being easily affected by the background soil spectrum in areas with low photosynthetic pigment density, and its value tends to saturate in areas with high density. Therefore, this invention employs a photosynthetic pigment index that compensates for these problems, and its details will be described later.

[0054] <Surface soil moisture index> The "surface soil moisture index" is a value that serves as an indicator of the surface soil moisture content in the evaluation area corresponding to the area ID. The surface soil moisture index is calculated from the multispectral surface reflectance by utilizing the fact that the multispectral reflectance decreases when the moisture content of the ground surface is high. The feature information estimation unit 315 calculates the surface soil moisture index by linearly interpolating the observed time-series spectrum between the dry soil spectrum and the wet soil spectrum.

[0055] [Feature Spectrum Table] The following spectra are associated with the feature spectrum table. • Spectrum during the period of maximum coverage • Minimum coverage period spectrum • Spectrum at the end of vegetation • Spectrum during the period of increasing coverage • Spectrum during the period of reduced coverage • Soil spectrum • Dry soil spectrum • Submerged soil spectrum • Wet soil spectrum Each of these items will be explained below in order.

[0056] <Spectrum at maximum coverage> The "maximum cover spectrum" is the spectrum at the time when the photosynthetic pigment index is at its maximum value, representing the state where vegetation cover is at its highest. The maximum cover spectrum is used as a basis for estimating vegetation type and calculating vegetation cover.

[0057] <Minimum Coverage Spectrum> The "minimum cover spectrum" is the spectrum at the point when the photosynthetic pigment index increases from its minimum value and exceeds 0.1. It represents the spectrum before organs such as leaves and stems begin to grow. The minimum cover spectrum is used as a basis for estimating vegetation type and calculating vegetation cover rate.

[0058] <Spectrum at the end of vegetation> The "vegetation end spectrum" is the spectrum at the point when the photosynthetic pigment index decreases from its maximum value and falls below 0.5, representing the stage when vegetation ends due to harvesting or other factors. The vegetation end spectrum is used as a basis for estimating vegetation type and calculating the vegetation period.

[0059] <Spectrum during the period of increasing coverage> The "coverage increase phase spectrum" is the spectrum at the point when the photosynthetic pigment index increases from its bottom value and reaches approximately 50% of its peak value. This spectrum represents the stage in which organs such as leaves and stems grow rapidly. The cover increase phase spectrum is used as a basis for calculating vegetation type. Furthermore, the spectrum during the coverage increase phase may be subdivided into peak values ​​of 25%, 50%, 75%, and so on.

[0060] <Spectrum during the period of decreasing coverage> The "coverage reduction phase spectrum" is the spectrum at the point when the photosynthetic pigment index decreases from its peak value to approximately 50% of the peak value. This spectrum represents the stage in which reproductive organs such as flowers and fruits are formed and chlorophyll decreases. The cover reduction phase spectrum is used as a criterion for calculating vegetation type. Furthermore, the spectrum during the coverage reduction period may be subdivided into peak values ​​of 25%, 50%, 75%, and so on.

[0061] <Soil Spectrum> A "soil spectrum" is the surface spectrum of the ground in a state without vegetation, and is the spectrum when the photosynthetic pigment index is below 0.0. Multiple soil spectra are extracted.

[0062] <Arid Soil Spectrum> A "dry soil spectrum" is a soil spectrum representing a state where water has not entered the voids between soil particles. Among the multiple spectra extracted as soil spectra, it is the spectrum with the highest average reflectance across all wavelengths. A dry soil spectrum can be presumed to represent a state where there is almost no moisture in the voids between soil particles.

[0063] <Flooded Soil Spectrum> A "flooded soil spectrum" is a soil spectrum obtained when there is a layer of water on the ground surface. From among the multiple extracted soil spectra, the spectrum in which the decrease in near-infrared reflectance is more than twice the decrease in blue reflectance compared to the dry soil spectrum is extracted as the flooded soil spectrum. This method utilizes the fact that when there is a layer of liquid water on the soil surface, it is affected by the absorption bands in the red to near-infrared region of the liquid water, and that the reflection of sky-scattered light from the water surface adds blue wavelengths.

[0064] <Wet Soil Spectrum> A "moist soil spectrum" is a soil spectrum in which water has entered the voids of soil particles. From multiple extracted soil spectra, the spectrum with the lowest average reflectance among the remaining spectra (excluding the flooded soil spectrum) is extracted as the moist soil spectrum.

[0065] [Feature Period Table] The feature period table associates the following information spectrum with each area ID. • Vegetation period • Period of increasing coverage • Period of decrease in coverage Each of these items will be explained below in order.

[0066] <Vegetation period> The "vegetation period" refers to the period during which vegetation is cultivated. It is defined as the period from when the photosynthetic pigment index increases from its minimum value and exceeds 0.1, to when the photosynthetic pigment index decreases from its maximum value and falls below 0.5. The vegetation period is used to estimate vegetation type.

[0067] <Period of increasing coverage> The "coverage increase period" refers to the period during which the vegetation cover is increasing. This period is defined as the time from when the photosynthetic pigment index rises from its minimum value to above 0.1, until when the photosynthetic pigment index reaches its maximum value. The coverage increase period is used to estimate the vegetation type.

[0068] <Period of decrease in coverage> The "period of reduced vegetation coverage" refers to the period during which the vegetation coverage decreases. This period is defined as the time from when the photosynthetic pigment index reaches its maximum value until when the index decreases from its maximum value to below 0.5. This period of reduced coverage is used to estimate the vegetation type.

[0069] (Reference Information) Next, we will explain the reference information. Reference information refers to various types of information that indicate standard activity levels, growth levels, and periods related to vegetation in the evaluation area. In System 1, known reference information is obtained and stored from user input operations, and unknown reference information is obtained and stored from the estimation process described later. System 1 then uses the stored reference information in subsequent estimation processes. In other words, in System 1, reference information is an intermediate output value obtained during various estimation processes, and may also become the final output value.

[0070] Figure 5B shows an example of reference information. As shown in Figure 5B, the reference information consists of, for example, the following data table. • Base period table • Reference spectral table • Reference characteristic table Each of these items will be explained below in order.

[0071] Note that the standard information may also be composed of other information tables. The details of each of these information tables will be explained in turn. Note that all items refer to standard values ​​for each vegetation type.

[0072] [Reference Period Table] The reference period table stores standard information regarding various periods for each vegetation type. As shown in Figure 5B, the standard period table associates the following reference values ​​with each vegetation type. • Vegetation period by vegetation type • Period of increase in cover rate by vegetation type • Period of decrease in cover rate by vegetation type Each of these items will be explained below in order.

[0073] <Vegetation period by vegetation type> "Vegetation period by vegetation type" is the average of vegetation periods extracted from multiple areas with known vegetation types. The vegetation period refers to the standard period from germination (or transplanting) to the end of growth, such as harvesting or death. Since the vegetation period for each vegetation type varies depending on environmental conditions such as temperature and solar radiation, it is desirable to calculate and store corrected values ​​using meteorological data.

[0074] <Period of increase in cover rate by vegetation type> "Coverage increase period by vegetation type" is the average of the coverage increase periods extracted from multiple areas with known vegetation types. The period of increased cover rate for each vegetation type represents the stage in which plants form vegetative organs (leaves, stems, etc.). Since this period fluctuates depending on environmental conditions such as temperature and solar radiation, it is desirable to calculate and accumulate corrected values ​​using meteorological data.

[0075] <Period of decrease in cover rate by vegetation type> "Period of decrease in cover rate by vegetation type" is the average of the periods of decrease in cover rate extracted from multiple areas with known vegetation types. The period of decrease in cover rate for each vegetation type represents the stage in which plants form reproductive organs such as flowers, fruits, and grains. Since this period fluctuates depending on environmental conditions such as temperature and solar radiation, it is desirable to calculate and accumulate corrected values ​​using meteorological data.

[0076] [Reference Spectrum Table] The reference spectral table stores standard information (reference values) regarding various multispectral reflectances for each vegetation type and vegetation history. As shown in Figure 5B, the standard spectral table associates the following information with vegetation type and vegetation history. • Spectrum of maximum cover period by vegetation type • Spectra of minimum cover period by vegetation type • Spectra at the end of vegetation by vegetation type • Spectrum of increasing cover rate by vegetation type • Spectrum of decrease in cover rate by vegetation type Each of these items will be explained below in order.

[0077] <Spectrum of maximum cover period by vegetation type> The "maximum cover period spectrum by vegetation type" is an average of the maximum cover period spectra extracted from multiple areas with known vegetation types, categorized by vegetation type. This spectrum is used to estimate unknown vegetation types.

[0078] <Spectrum of minimum cover period by vegetation type> The "minimum cover duration spectrum by vegetation type" is an average of minimum cover duration spectra extracted from multiple areas with known vegetation types, categorized by vegetation type. This spectrum is used to estimate unknown vegetation types.

[0079] <Spectrum at the end of vegetation growth by vegetation type> "Vegetation type-specific vegetation end-of-life spectra" are obtained by averaging vegetation end-of-life spectra extracted from multiple areas with known vegetation types, categorized by vegetation type. These vegetation type-specific vegetation end-of-life spectra are used to estimate unknown vegetation types.

[0080] <Spectrum of increasing vegetation coverage by vegetation type> The "vegetation type-specific coverage increase period spectrum" is an average of coverage increase period spectra extracted from multiple areas with known vegetation types, categorized by vegetation type. This vegetation type-specific coverage increase period spectrum is used to estimate unknown vegetation types.

[0081] <Spectrum of Decreasing Coverage Period by Vegetation Type> The "vegetation type-specific coverage reduction period spectrum" is an average of coverage reduction period spectra extracted from multiple areas with known vegetation types, categorized by vegetation type. This vegetation type-specific coverage reduction period spectrum is used to estimate unknown vegetation types.

[0082] [Reference Characteristics Table] This standard characteristics table (see Figure 5B) stores standard physiological and physical parameters for each vegetation type obtained from past experiments and field measurements. Information on standard activity levels can be used, for example, as predicted values ​​for vegetation types estimated from multispectral index information. Furthermore, System 1 can use these predicted values ​​in estimation processing of environmental load information and other data.

[0083] As shown in Figure 5B, the standard activity level table by vegetation type is linked to the following information for each vegetation type, vegetation history, or fertilization type. • Light utilization efficiency by vegetation type • Maintenance respiratory index by vegetation type • Growth rate and respiration index by vegetation type • Ratio of harvested carbon to net primary production by vegetation type • Yield and harvested carbon ratio by vegetation type • Nitrogen utilization efficiency by vegetation type • Aeration structure coefficient by vegetation type • N2O leaching coefficient by vegetation type • N2O emission factors by vegetation type • Nitrogen supply rate by fertilizer type • Standard fertilizer application rates by vegetation type and fertilizer type • Standard maximum photosynthetic pigment index by vegetation type and fertilization type • Standard photosynthetic pigment change rates by vegetation type and fertilization type • Standard oxygen supply based on vegetation history • Standard moisture content based on vegetation history • Soil organic carbon content by vegetation history • Aerobic decomposition rates by vegetation history • Anaerobic decomposition rates by vegetation history • Nitrification and denitrification rates by vegetation history The following sections will explain the overview of these items and their roles in this system, in order.

[0084] <Light utilization efficiency by vegetation type> "Light Utilization Efficiency (LUE) by Vegetation Type" is an index that indicates the efficiency with which plants convert absorbed photosynthetically active radiation (PAR) into carbon fixation. It is calculated by dividing a fixed amount of carbon per unit time by the amount of PAR absorbed. Each functional module of System 1 can be used for subsequent processing by referring to the corresponding vegetation type-specific light utilization efficiency based on the vegetation type being evaluated.

[0085] <Maintenance Respiratory Factors by Vegetation Type> The "vegetation type-specific maintenance respiration coefficient" is the value obtained by dividing the amount of respiration required by plants for cell maintenance and basal metabolism by the plant's carbon weight (cumulative value of net primary production). Since the maintenance respiration rate varies depending on growth conditions such as temperature, statistically processed reference values ​​are set for each vegetation type. Each functional module of System 1 can refer to the corresponding vegetation type-specific maintenance respiration coefficient based on the vegetation type being evaluated and use it for subsequent processing.

[0086] <Growth and respiration coefficients by vegetation type> The "vegetation type-specific growth respiration coefficient" is the value obtained by dividing the amount of respiration required for plant growth by the total primary production of the plant. Since the respiration rate differs depending on the growth stage, such as temperature, a statistically processed baseline value is set for each vegetation type. Each functional module of System 1 can refer to the corresponding vegetation type-specific growth respiration coefficient based on the vegetation type being evaluated and use it for subsequent processing.

[0087] <Ratio of harvested carbon to net primary production by vegetation type> The "Vegetation Type-Specific Ratio of Net Primary Production to Harvested Carbon" is the value obtained by dividing the amount of carbon contained in the harvested product by the net primary production (total primary production - respiration). Since the harvested parts (grains, fruits, roots, leaves, etc.) differ for each crop, there is a wide range in the ratio of net primary production to harvested carbon. Each functional module of System 1 can refer to the corresponding Vegetation Type-Specific Ratio of Net Primary Production to Harvested Carbon based on the vegetation type being evaluated and use it for subsequent processing.

[0088] <Yield and harvested carbon ratio by vegetation type> The "Yield-to-Carbon Harvest Ratio by Vegetation Type" is the value obtained by dividing the yield (weight of harvested produce) by the amount of carbon harvested. This value varies depending on differences in protein and water content. Each functional module of System 1 can refer to the corresponding Yield-to-Carbon Harvest Ratio by Vegetation Type, based on the vegetation type being evaluated, and use this information for subsequent processing.

[0089] <Nitrogen utilization efficiency by vegetation type> "Nitrogen utilization efficiency by vegetation type" is calculated by dividing net primary production (NPP) by the amount of nitrogen utilized by the plants. Since the amount of nitrogen required varies depending on the type of crop and its physiological characteristics (protein content, metabolic mode, etc.), standard values ​​are set for each vegetation type. Each functional module of System 1 can refer to the corresponding vegetation type-specific nitrogen utilization efficiency based on the vegetation type being evaluated and use it for subsequent processing.

[0090] <Aeration structure coefficient by vegetation type> The "vegetation type-specific aeration tissue coefficient" is the ratio of N2O released to the ground surface via the aeration tissue of vegetation to the total N2O produced in the soil. Each functional module of System 1 can refer to the corresponding vegetation type-specific aeration tissue coefficient based on the vegetation type being evaluated and use it for subsequent processing.

[0091] <N2O leaching coefficient by vegetation type> The "vegetation type-specific N2O leaching coefficient" is the ratio of the amount of ammonium ions and nitrate ions in the soil that are not absorbed by vegetation to the amount that dissolves in water, leaches out, and is directly released into the atmosphere. Each functional module of System 1 can refer to the corresponding vegetation type-specific N2O leaching coefficient based on the vegetation type being evaluated and use it for subsequent processing.

[0092] <N2O emission factors by vegetation type> The "vegetation type-specific N2O emission factor" is the ratio of nitrous oxide emissions to the total amount of ammonia nitrification and nitrate denitrification. Each functional module of System 1 can refer to the corresponding vegetation type-specific N2O emission factor based on the vegetation type being evaluated and use it for subsequent processing.

[0093] <Nitrogen supply rate by fertilizer type> "Nitrogen supply rate by fertilization type" refers to the standard ratio of nitrogen supplied per unit time by ammonium ions and nitrate ions into the soil to the amount of nitrogen applied as fertilizer. Because this value is highly dependent on soil temperature, it is desirable to store it separately for each temperature or in a format that can be used after temperature correction. Each functional module of System 1 can refer to the corresponding nitrogen supply rate by fertilization type, based on the fertilization type being evaluated, and use this information for subsequent processing.

[0094] <Standard fertilizer application rates by vegetation type and fertilization type> "Standard fertilizer application rates by vegetation type and fertilization type" refers to the standard fertilizer application rates for each vegetation type, recorded separately for each fertilization type. Standard fertilizer application rates for each vegetation type and fertilization type may differ depending on the region, such as by country or administrative division, so it may be necessary to maintain separate records for each region. Each functional module of System 1 can refer to the corresponding standard fertilizer application rates for each vegetation type and fertilization type, based on the vegetation type and fertilization type being evaluated, and use this information for subsequent processing.

[0095] <Standard maximum photosynthetic pigment index by vegetation type and fertilization type> The "Standard Maximum Photosynthetic Pigment Index by Vegetation Type and Fertilization Type" is a record of the maximum photosynthetic index shown at the peak of standard growth for each vegetation type, categorized by fertilization type. Standard maximum photosynthetic pigment indices for each vegetation type and fertilization type may vary by region, such as country or climate zone, and may therefore be maintained separately for each region. Each functional module of System 1 can refer to the corresponding standard maximum photosynthetic pigment indices for each vegetation type and fertilization type, based on the vegetation type and fertilization type being evaluated, and use this information for subsequent processing.

[0096] <Standard photosynthetic pigment change rate by vegetation type and fertilization type> "Standard photosynthetic pigment change rate by vegetation type and fertilization type" refers to the standard photosynthetic pigment change rate for each vegetation type, recorded separately for each fertilization type. Standard photosynthetic pigment change rates by vegetation type and fertilization type may vary depending on the region, such as country or climate zone, so it may be good to maintain records for each region. Each functional module of System 1 can be used for subsequent processing by referring to the corresponding standard photosynthetic pigment change rate for each vegetation type and fertilization type, based on the vegetation type and fertilization type being evaluated.

[0097] <Standard oxygen supply based on vegetation history> "Standard oxygen supply by vegetation history" refers to a value that records the standard oxygen supply for each vegetation type history (crop rotation, such as rice > wheat > rice). Each functional module of System 1 can refer to the corresponding standard oxygen supply by vegetation history based on the vegetation history being evaluated and use it for subsequent processing.

[0098] <Standard moisture content by vegetation history> "Standard moisture content by vegetation history" refers to values ​​that record the standard moisture content for each vegetation type history (crop rotation such as rice > wheat > rice). Each functional module of System 1 can refer to the corresponding standard moisture content by vegetation history based on the vegetation history being evaluated and use it for subsequent processing.

[0099] <Soil organic carbon content by vegetation history> "Soil organic carbon content by vegetation history" refers to a value that records the standard amount of organic carbon for each vegetation type history (crop rotation such as rice > wheat > rice). Each functional module of System 1 can refer to the corresponding soil organic carbon content by vegetation history based on the vegetation history being evaluated and use it for subsequent processing.

[0100] <Aerobic decomposition rates by vegetation history> "Aerobic decomposition rate by vegetation history" refers to a value that records the standard aerobic decomposition rate for each vegetation type history (crop rotation, such as rice > wheat > rice). Each functional module of System 1 can refer to the corresponding aerobic decomposition rate by vegetation history, based on the vegetation history being evaluated, and use it for subsequent processing.

[0101] <Anaerobic decomposition rates by vegetation history> "Anaerobic decomposition rate by vegetation history" refers to a value that records the standard aerobic decomposition rate for each vegetation type history (crop rotation such as rice > wheat > rice). Each functional module of System 1 can refer to the corresponding anaerobic decomposition rate by vegetation history based on the vegetation history being evaluated and use it for subsequent processing.

[0102] <Nitrification and denitrification rates by vegetation history> "Nitrification-denitrification rate by vegetation history" refers to a recorded value of the standard nitrification-denitrification rate for each vegetation type history (crop rotation, such as rice > wheat > rice). Each functional module of System 1 can refer to the corresponding nitrification-denitrification rate by vegetation history based on the vegetation history being evaluated and use it for subsequent processing.

[0103] (Cultivation information) Next, let's discuss cultivation information. Cultivation information refers to various types of information related to cultivation management in the evaluation area. In System 1, known cultivation information is acquired and stored from user input, while unknown cultivation information is acquired and stored through estimation processing, which will be described later. System 1 then uses the stored cultivation information in subsequent estimation processes. In other words, in System 1, cultivation information serves as both an intermediate output value obtained during various estimation processes and the final output value.

[0104] Figure 6A shows an example of cultivation information. As shown in Figure 6A, cultivation information is composed of, for example, the following information table. • Cultivation information table Note that cultivation information may be composed of other information tables. The details of the cultivation information table will be explained in order.

[0105] [Cultivation Information Table] The cultivation information table associates the following items with the area ID: • Cultivation type • Vegetation period • Soil exposure period • Tillage day ·Flooding day Fertilizer type ·Amount of fertilizer applied ·Crop residue amount Each of these items and its estimation process will be explained in order below. In addition to the estimation process described later, the values ​​of each item are also recorded when the user inputs actual or planned values.

[0106] <Cultivation Type> The cultivation type is a classification of the cultivation management method for the evaluation area corresponding to the area ID, based on the following cultivation parameters, and includes no-till cultivation, conservation cultivation, natural cultivation, organic cultivation, conventional cultivation, flooded cultivation, etc. The cultivation parameters are tillage day, flooding day, soil exposure period, nitrogen fertilization type, and nitrogen fertilization amount.

[0107] <Vegetation period> "Vegetation period" refers to the period during which plants are cultivated and inhabit the evaluation area corresponding to the area ID.

[0108] <Soil exposure period> "Soil exposure" refers to the period during which no plants are cultivated or growing in an evaluation area corresponding to an area ID.

[0109] <Tillage date> "Tillage date" refers to the date on which tillage work was performed in the evaluation area corresponding to the area ID. Although this specification does not use information on tillage depth, tillage date and tillage depth may be recorded and used in combination.

[0110] <Flooding day> "Flooded days" refer to time-series data indicating the days when a layer of water exists on the ground surface in the evaluation area corresponding to the area ID. Although the term "flooded days" is used in this specification, in reality, various forms of water management can be determined from this time-series data of flooded days, such as periods of continuous flooding, intermittent irrigation periods where water is removed periodically or irregularly, and periods of mid-season drainage for rice cultivation, etc.

[0111] <Fertilization type> "Fertilization type" refers to the type of nitrogen-containing fertilizer used in the evaluation area corresponding to the area ID. Specific examples include chemical fertilizers, slow-release chemical fertilizers, organic fertilizers, compost, and green manure.

[0112] <Amount of fertilizer applied> "Fertilizer application amount" refers to the nitrogen-equivalent weight of fertilizer applied in the evaluation area corresponding to the area ID from the previous observation date to the current observation date.

[0113] <Amount of crop residue> "Crop residue amount" refers to the amount of vegetation carbon remaining unharvested in the evaluation area corresponding to the area ID.

[0114] (Growth information) Next, let's discuss growth information. Growth information refers to various types of information about the growth status of vegetation in the evaluation area. In System 1, known growth information is acquired and stored from user input, while unknown growth information is acquired and stored through estimation processing, which will be described later. System 1 then uses the stored growth information in subsequent estimation processes. In other words, in System 1, growth information serves as both an intermediate output value obtained during various estimation processes and the final output value.

[0115] Figure 6B shows an example of growth information. As shown in Figure 6B, growth information is composed of, for example, the following information table. • Growth information table Furthermore, growth information may be comprised of other information tables. The details of each of these information tables will be explained in turn.

[0116] [Growth Information Table] The growth information table associates the following items with the area ID. Vegetation type • Vegetation cover rate • Gross Primary Production (GPP) • Net Primary Production (NPP) • Vegetation respiration • Vegetation carbon weight • Carbon harvested ·yield • Vegetation nitrogen demand Each of these items will be explained below in order. In addition to the estimation process described later, the values ​​of each item are also recorded when the user inputs actual or planned values.

[0117] <Vegetation Type> "Vegetation type" refers to the classification of plants cultivated and growing in the evaluation area corresponding to the area ID. This includes classifications based on, for example, photosynthetic pathways (C3, C4, CAM), leaf morphology (grasses, broadleaf, etc.), harvested parts (leafy vegetables, root vegetables, fruit vegetables, etc.), crop types (rice, wheat, corn, etc.), and varieties.

[0118] <Vegetation Coverage> "Vegetation cover rate" refers to the ratio of the area occupied by the upper part of the vegetation to the ground surface in the evaluation area corresponding to the area ID. The value is expressed as 0 to 1 or as a percentage; for example, if the area of ​​soil to vegetation is 1:1, it would be 50%. It can also be estimated from the Leaf Area Index (LAI).

[0119] <Gross Primary Production (GPP)> "Gross Primary Production (GPP)" is an index that shows the amount of carbon newly fixed from atmospheric CO2 through photosynthesis in the evaluation area corresponding to the area ID, over time. The unit is gC / m 2 / day or g-CO2 / m 2 You can use options like / day.

[0120] <Net Primary Production (NPP)> Net Primary Production (NPP) is an index that shows the net carbon stock over time, calculated by subtracting the respiration rate of vegetation (autotrophs) from GPP. It represents the amount of carbon actually stored in plants and soil, and its unit is gC / m³. 2 / day or g-CO2 / m 2 You can use options like / day.

[0121] <Vegetation respiration rate> "Autotrophic respiration" refers to information that stores time-series data on the total amount of CO2 released into the atmosphere by plants growing in the evaluation area corresponding to the area ID through respiration (maintenance respiration, growth respiration, etc.). The time resolution can be in days or hours, and the unit can be g-CO2 or gC (CO2 equivalent), etc.

[0122] <Vegetation carbon weight> "Vegetation carbon weight" refers to information that stores time-series data representing the amount of carbon accumulated in net primary production (NPP), which is calculated by subtracting vegetation respiration from photosynthesis (GPP), in the evaluation area corresponding to the area ID. The time resolution can be either daily or hourly.

[0123] <Carbon harvested> "Harvested carbon" refers to information that stores time-series data of the amount of carbon in biomass transported off farmland through harvesting operations from plants cultivated in the evaluation area corresponding to the area ID, converted to CO2. For example, in the case of fruit, the weight increased from flowering and fruiting to the harvest day is the target. The time resolution can be in days or hours, and the unit can be g-CO2 or gC (CO2 equivalent), etc.

[0124] <Yield> "Yield" refers to the mass of harvestable parts of crops grown in the evaluation area corresponding to the area ID. It includes the weight of edible or usable parts obtained through harvesting, and depending on the crop, this may include grains, fruits, roots, etc.

[0125] <Vegetation nitrogen demand> "Vegetation nitrogen demand" refers to information that stores time-series data on the amount of nitrogen required for growth and maintenance by plants growing in the evaluation area corresponding to the area ID. The time resolution can be on a daily or hourly basis.

[0126] (Soil information) Next, let's discuss soil information. Soil information refers to various types of information about the soil conditions in the evaluation area. In System 1, known soil information is acquired and stored from user input, while unknown soil information is acquired and stored through estimation processing, which will be described later. System 1 then uses the stored soil information in subsequent estimation processes. In other words, in System 1, soil information serves as both an intermediate output value obtained during various estimation processes and the final output value.

[0127] Figure 7A shows an example of soil information. As shown in Figure 7A, soil information is composed of, for example, the following information table. • Soil information table Note that soil information may be composed of other information tables. Details of each of these information tables will be explained in turn.

[0128] [Soil Information Table] The soil information table associates the following items with each area ID: Vegetation history • Soil temperature • Soil oxygen supply • Soil moisture content • Soil nitrogen supply • Excess nitrogen amount • Soil organic carbon content • Amount of soil organic matter decomposition • Aerobic decomposition rate • Anaerobic decomposition rate ·Nitrification and denitrification rate Each of these items will be explained below in order. In addition to the estimation process described later, the values ​​of each item are also recorded when the user inputs actual or planned values.

[0129] <Vegetation History> "Vegetation history" refers to information showing the changes in vegetation types that have been cultivated and grown in the evaluation area corresponding to the area ID. This allows for a comprehensive representation of crop rotation, double cropping, ground cover, and other planting patterns, as well as the history of vegetation management.

[0130] <Soil temperature> "Soil temperature" refers to information that stores the average soil temperature of the evaluation area corresponding to the evaluation ID as a time-series value. The time resolution can be either daily or hourly.

[0131] <Soil oxygen supply> "Soil oxygen supply" refers to information that shows the amount of oxygen supplied to the soil over time in the evaluation area corresponding to the evaluation ID. The time resolution can be set arbitrarily, such as days or hours, and the unit is g-O2 / m 2 / day or L-O2 / m 2 This can be used as an indicator to estimate whether the soil is in an aerobic or anaerobic state.

[0132] Actual aerobic and anaerobic conditions in soil are influenced by a multifaceted set of factors, including soil porosity, permeability, groundwater level, oxidation-reduction potential (Eh), and pH. In this embodiment, oxygen diffusion is approximately calculated based on factors such as tillage date, flooding date, and vegetation cover rate. However, if the user adds soil texture and groundwater level information, it is also possible to model the oxidation-reduction potential (Eh).

[0133] <Soil moisture content> "Soil moisture content" refers to information that shows the amount of moisture in the soil over time in the evaluation area corresponding to the evaluation ID. The time resolution can be arbitrarily set to days, hours, etc., and rainfall and tillage work are the main sources of data.

[0134] <Soil nitrogen supply> "Soil nitrogen supply" refers to information that shows the total amount of ammonium ions and nitrate ions supplied to the soil through fertilization, organic matter decomposition, nitrogen fixation, etc., in the evaluation area corresponding to the evaluation ID, over time. The time resolution can be arbitrarily set to days, hours, etc., and the unit is gN / m 2 Use / day. The amounts of ammonium ions and nitrate ions can also be handled by converting the amount of nitrogen to the weight of ammonia as needed.

[0135] <Excess Nitrogen Amount> "Excess nitrogen" refers to information that shows, in the evaluation area corresponding to the evaluation ID, the residual amount obtained by subtracting the amount estimated to be absorbed or utilized by plants from the ammonium and nitrate ions supplied to the soil (from fertilization, organic matter decomposition, nitrogen fixation, etc.), over time. The time resolution can be arbitrarily set to days, hours, etc.

[0136] <Soil organic carbon content> "Soil organic carbon content" refers to information that shows the total amount of organic carbon accumulated in the soil of the evaluation area corresponding to the evaluation ID, in a time series.

[0137] <Amount of organic matter decomposition in soil> "Soil organic matter decomposition rate" refers to information indicating the amount of carbon dioxide emitted as a result of organic matter decomposition by soil microorganisms in the evaluation area corresponding to the evaluation ID. The time resolution can be arbitrarily set to days or hours. Soil microbial respiration rate

[0138] <Aerobic decomposition rate> "Aerobic decomposition rate" refers to the rate at which aerobic microorganisms in the soil decompose organic matter in the evaluation area corresponding to the evaluation ID. The time resolution can be arbitrarily set to days, hours, etc. The activity of aerobic microorganisms varies depending on conditions such as soil temperature, soil oxygen supply, soil moisture content, and soil nitrogen content.

[0139] <Anaerobic decomposition rate> "Anaerobic decomposition rate" refers to the rate at which anaerobic microorganisms in the soil decompose organic matter in the evaluation area corresponding to the evaluation ID. The time resolution can be arbitrarily set to days, hours, etc. The activity of anaerobic microorganisms varies depending on conditions such as soil temperature, soil oxygen supply, soil moisture content, and soil nitrogen content.

[0140] <Nitrification and denitrification rate> "Nitrification-denitrification rate" refers to the rate at which aerobic microorganisms in the soil nitrify and denitrify ammonia and nitrate in the evaluation area corresponding to the evaluation ID. The time resolution can be set arbitrarily, such as days or hours. The activity of anaerobic microorganisms varies depending on conditions such as soil temperature, soil oxygen supply, soil moisture content, and soil nitrogen content.

[0141] (Environmental load information) Next, we will explain the environmental impact information. Here, "environmental impact information" refers to information indicating the degree of impact on the environment, such as greenhouse gas emissions and soil carbon stock changes in the evaluation area, and includes the values ​​that this system 1 ultimately outputs after estimation processing. That is, the present system 1 has a function of acquiring unknown environmental load information by the estimation process described later and accumulating and visualizing it in units of evaluation areas. These environmental load information are obtained as the final output of a series of estimation processes in the present system 1.

[0142] FIG. 7B is a diagram showing an example of environmental load information. As shown in FIG. 7B, the environmental load information is constituted by, for example, the following data table. · Environmental load information table Note that the environmental load information table may be constituted by other data tables. The details of these data tables will be described in order.

[0143] [Environmental load information table] In the environmental load information table, the following items are associated with the area ID. · CO2 emission · N2O emission · CH4 emission The details of these items will be described in order below.

[0144] <CO2 emission> The "CO2 emission" indicates the change in soil organic carbon stock in the evaluation area corresponding to the evaluation ID as the net emission amount of CO2. When the emission to the atmosphere exceeds the absorption (carbon sequestration), it is a positive value (net emission), and when the absorption exceeds, it is a negative value (net absorption).

[0145] <N2O emission> The "N2O emission" indicates the amount of N2O released from the ground surface into the atmosphere in the evaluation area corresponding to the evaluation ID.

[0146] <CH4 emission> The "CH4 emission" indicates the amount of CH4 released from the ground surface into the atmosphere in the evaluation area corresponding to the evaluation ID.

[0147] By evaluating CO2 emissions, N2O emissions, and CH4 emissions together, a comprehensive picture of GHG emissions at the farmland level can be obtained. The estimated results are output as a map or numerical list using the visualization function of System 1, and can be used as indicators for GHG emission reduction and improvement of cultivation management.

[0148] <4. System 1 Processing> Next, we will explain the processing of System 1. First, we will explain the process of acquiring various types of information entered by the user.

[0149] <4-1. Information Acquisition Flow> Figure 8 shows an example of an input information acquisition flow 800, which acquires information from an external source. As shown in Figure 8, in the input information acquisition flow, first, the management server 103 receives input operations for various types of information from the user terminal 102 (step S810). Specifically, the user inputs known information from among target information, standard information, cultivation information, growth information, and soil information from the user terminal 102. The various types of information input to the user terminal 102 are transmitted to the management server 103. For example, for cultivation information, growth information, and soil information, the user can input actual or planned values ​​for each item from the user terminal 102.

[0150] After step S810, the management server 103 retrieves the received information (step S820). Specifically, the input information acquisition unit 311 of the management server 103 records each piece of received information in the corresponding data table in the auxiliary storage device 302 according to its type. The process of acquiring input information is repeated each time a user makes an input operation, and a new record is recorded in each data table of the auxiliary storage device 302.

[0151] In the input information acquisition flow 800, the management server 103 acquires information from an external device (step S830). Specifically, the weather information acquisition unit 313 of the management server 103 acquires weather information from an external weather information database based on a preset sampling rate. In addition, the spectral information acquisition unit 314 of the management server 103 periodically acquires multispectral information from a multispectral acquisition means such as an artificial satellite.

[0152] After step S830, the management server 103 records the acquired information (step S840). Specifically, the weather information acquisition unit 313 of the management server 103 stores the acquired weather information in the auxiliary storage device 302. In addition, the spectrum information acquisition unit 314 of the management server 103 stores the acquired multispectral information in the auxiliary storage device 302. These processes are repeated each time information is acquired, and new records are recorded in each data table of the auxiliary storage device 302.

[0153] <4-2. Environmental Information Visualization Flow> Next, we will describe the overall visualization flow of environmental information, which is the estimation process performed by System 1. Figure 9 shows an example of the visualization flow of environmental information.

[0154] As shown in Figure 9, in the environmental information visualization flow, the management server 103 first accepts the user's specification of target information (step S910). Specifically, it accepts input operations from the user terminal 102 regarding the evaluation area and evaluation period for which the user wishes to have estimation processing performed by system 1.

[0155] After step S910, the management server 103 estimates the feature information (step S920). The spectral information estimation process by the management server 103 will be described later using Figure 10.

[0156] After step S920, the management server 103 estimates the reference information (step S930). The process of estimating the reference information by the management server 103 will be described later using Figure 11.

[0157] After step S930, the management server 103 estimates the cultivation information (step S940). The cultivation information estimation process by the management server 103 will be described later using Figure 12.

[0158] After step S940, the management server 103 estimates the growth information (step S950). The growth information estimation process by the management server 103 will be described later using Figure 13.

[0159] After step S950, the management server 103 estimates soil information (step S960). The soil information estimation process by the management server 103 will be described later using Figure 14.

[0160] After step S960, the management server 103 estimates environmental load information (step S970). The process of estimating environmental load information by the management server 103 will be described later using Figure 15.

[0161] After step S970, the management server 103 outputs estimated information (step S980). Specifically, the output unit 321 of the management server 103 outputs various types of information that have been estimated in the processing so far, from the information requested by the user, to the user terminal 102. The manner of output of the estimation process will be described later. Next, the details of the estimation process for each type of information will be explained in order.

[0162] <4-3. Feature Information Estimation Flow> Figure 10 shows an example of the feature information estimation flow. As shown in Figure 10, in the feature information estimation flow, first, the management server 103 obtains the evaluation area and evaluation period specified by the user (step S1010). Specifically, the target information acquisition unit 312 of the management server 103 obtains the evaluation area and evaluation period entered by the user.

[0163] After step S1010, the management server 103 acquires multispectral information for the evaluation area and evaluation period (step S1020). Specifically, the spectral information acquisition unit 314 of the management server 103 acquires the multispectral information for the evaluation area and evaluation period specified by the user, which was acquired in step S1010, by referring to the auxiliary storage device 302.

[0164] After step S1020, the management server 103 estimates feature information (step S1030). Specifically, the feature information estimation unit 315 of the management server 103 estimates feature information using the information acquired in step S1020. The specific estimation process by the feature information estimation unit 315 is described below in order for each item of feature information.

[0165] [Calculation of Photosynthetic Pigment Index] The feature information estimation unit 315 is: • The time-series multispectral surface reflectance of the evaluation area, including green reflectance (B3), red reflectance (B4), and near-infrared reflectance (B8), was obtained. The center wavelengths for each band, B3: 0.56 μm, B4: 0.665 μm, and B8: 0.842 μm, were obtained. The photosynthetic pigment index is calculated using the following formula: Photosynthetic Pigment Index = (Near-infrared reflectance B8 - Red reflectance B4) / (Central wavelength B8 - Central wavelength B4) - Red reflectance B4 - Green reflectance B3) / (Central wavelength B4 - Central wavelength B3).

[0166] In other words, the feature information estimation unit 315 uses the green reflectance, red reflectance, and near-infrared reflectance included in the time-series spectrum to calculate the photosynthetic pigment index by subtracting the value obtained by subtracting the red reflectance from the near-infrared reflectance by the value obtained by subtracting the red central wavelength from the near-infrared central wavelength, and then subtracting the value obtained by subtracting the green reflectance from the red central wavelength from the value obtained by subtracting the green central wavelength from the red central wavelength. Note that the value obtained by subtracting the red central wavelength from the near-infrared central wavelength and the value obtained by dividing by the value obtained by subtracting the green central wavelength from the red central wavelength can be adjusted within the range of positive numbers. To put it another way, the feature information estimation unit 315 uses the green reflectance, red reflectance, and near-infrared reflectance included in the time-series spectrum to calculate the photosynthetic pigment index based on the value obtained by subtracting the difference between the red reflectance and green reflectance multiplied by a second positive coefficient from the value obtained by multiplying the difference between the near-infrared reflectance and red reflectance by a first positive coefficient.

[0167] [Calculation of surface soil moisture index] The feature information estimation unit 315 is: • Obtain the time-series spectrum of the evaluation area, • Obtain the dry soil spectrum and wet soil spectrum included in the characteristic information of the evaluation area. • Surface soil reflectance, The surface soil moisture index is calculated using the linear interpolation formula: (average reflectance of dry soil - average reflectance at the time of observation) / (average reflectance of dry soil - average reflectance of wet soil). Furthermore, the reflectance of surface soil decreases linearly from a moisture content of approximately 0 to 0.3, but becomes almost unchanged around 0.5. Therefore, the relationship between reflectance (vertical axis) and moisture content (horizontal axis) is a downward-convex hyperbola, with an asymptote appearing around 0.5. Nonlinear interpolation, such as hyperbolas, can be used as needed.

[0168] [Spectrum during the period of maximum coverage] The feature information estimation unit 315 is: • Obtain the time-series spectrum of the evaluation area, • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, The spectrum at the point in time when the time-series photosynthetic pigment index changes from increasing to decreasing (the spectrum when the photosynthetic pigment index is at its maximum) is extracted as the spectrum of the maximum coverage period. However, depending on the vegetation type, if the seeding or transplanting density is low (for example, if the spacing between rows for open-field vegetables or between fruit trees is wide), the coverage rate may not reach 100% even at its peak. In such cases, the user or system may adopt a configuration in which it sets a maximum coverage rate (e.g., 80-100%) for each vegetation type and normalizes that peak value. In other words, the feature information estimation unit 315 extracts the maximum coverage period spectrum, which shows the spectrum when the photosynthetic pigment index is at its maximum, from the time-series spectrum of the evaluation area, based on the photosynthetic pigment index.

[0169] [Minimum Coverage Spectrum] The feature information estimation unit 315 is: • Obtain the time-series spectrum of the evaluation area, • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, The spectrum at the point when the time-series photosynthetic pigment index increases from its minimum value and exceeds 0.1 is extracted as the minimum coverage period spectrum. In other words, the feature information estimation unit 315 extracts a minimum coverage period spectrum from the time-series spectrum of the evaluation area, based on the photosynthetic pigment index, which shows a spectrum in which the photosynthetic pigment index has increased slightly from its minimum value.

[0170] [Spectrum at the end of vegetation] The feature information estimation unit 315 is: • Obtain the time-series spectrum of the evaluation area, • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, The spectrum at the point when the time-series photosynthetic pigment index decreases from its peak value and falls below 0.5 is extracted as the spectrum at the end of vegetation growth.

[0171] [Spectrum during the coverage increase phase] The feature information estimation unit 315 is: • Obtain the time-series spectrum of the evaluation area, • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, • Extract the spectrum at the point when the photosynthetic pigment index increases from its bottom value in the time series and reaches approximately 50% of its peak value, as a representative spectrum during the period of increasing coverage. Multiple spectra may be extracted, such as at 75%, 50%, and 25% of the peak value.

[0172] [Spectrum during the period of decreasing coverage] The feature information estimation unit 315 is: • Obtain the time-series spectrum of the evaluation area, • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, • The multispectral data taken when the time-series photosynthetic pigment index decreases from its peak value to approximately 50% of the peak value is extracted as a representative spectrum for the period of decreasing coverage. Multiple spectra may be extracted, such as at 75%, 50%, and 25% of the peak value. The spectrum when the photosynthetic pigment index is decreasing corresponds to the spectrum during the ripening stage in grain cultivation and is used to estimate the vegetation type. In other words, the feature information estimation unit 315 extracts a coverage reduction period spectrum from the time-series spectrum of the evaluation area, which shows the spectrum when the photosynthetic pigment index decreases.

[0173] [Soil Spectrum] The feature information estimation unit 315 is: • Obtain the time-series spectrum of the evaluation area, • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, • Spectra obtained from observation points where the time-series photosynthetic pigment index is 0.0 or less and the influence of vegetation is extremely small are extracted as soil spectra. In other words, the feature information estimation unit 315 extracts the soil spectrum from the time-series spectrum based on the photosynthetic pigment index.

[0174] [Dry soil spectrum] The feature information estimation unit 315 is: · Obtain the time-series spectrum of the evaluation area. · Obtain the time-series photosynthetic pigment index included in the feature information of the evaluation area. · Among the multiple spectra extracted as soil spectra, extract the spectrum with the highest average reflectance across all wavelengths as the dry soil spectrum. That is, the feature information estimation unit 315 extracts the dry soil spectrum from the soil spectrum based on the average reflectance across all wavelengths.

[0175] [Waterlogged soil spectrum] The feature information estimation unit 315 · Obtain the time-series spectrum of the evaluation area. · Obtain the time-series photosynthetic pigment index and dry soil spectrum included in the feature information of the evaluation area. · Among the multiple spectra extracted as soil spectra, extract the spectrum with a decrease width of near-infrared reflectance that is twice or more the decrease width of blue reflectance with respect to the dry soil spectrum as the waterlogged soil spectrum. That is, the feature information estimation unit 315 extracts the wet soil spectrum from the soil spectrum based on the average reflectance across all wavelengths.

[0176] When SWIR (short wavelength infrared) band data is available, it is also possible to improve the accuracy by using the water region determination algorithm in combination.

[0177] [Wet soil spectrum] The feature information estimation unit 315 · Obtain the time-series spectrum of the evaluation area. · Obtain the time-series photosynthetic pigment index and waterlogged soil spectrum included in the feature information of the evaluation area. From the multiple spectra extracted as soil spectra, the spectrum with the lowest average reflectance across all wavelengths is extracted as the wet soil spectrum from the remaining spectra after excluding the flooded soil spectrum. Alternatively, the wet soil spectrum may be extracted from all soil spectra without excluding the flooded soil spectrum. In other words, the feature information estimation unit 315 extracts the wet soil spectrum from the soil spectrum based on the average reflectance across all wavelengths.

[0178] [Vegetation period] The feature information estimation unit 315 is: • Obtain the time-series spectrum of the evaluation area, • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, The period from when the time-series photosynthetic pigment index increases from its minimum value and exceeds 0.1, to when the photosynthetic pigment index decreases from its maximum value and falls below 0.5, is extracted as the vegetation period.

[0179] Since the optimal threshold may vary depending on the crop type and the characteristics of the observation satellite sensor, this system includes an interface that allows users to arbitrarily set the threshold.

[0180] [Period of increasing coverage] The feature information estimation unit 315 is: • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, The period from when the time-series photosynthetic pigment index increases from its minimum value and exceeds 0.1, to when the photosynthetic pigment index reaches its maximum value (the period from the minimum to the maximum value of the photosynthetic pigment index) is extracted as the period of increased coverage. The period of increased coverage often corresponds to the vegetative growth period of the vegetation. In other words, the feature information estimation unit 315 extracts the period of increased coverage based on the photosynthetic pigment index.

[0181] [Period of decrease in coverage] The feature information estimation unit 315 is: • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, The period from when the time-series photosynthetic pigment index reaches its maximum value to when the photosynthetic pigment index decreases from its maximum value to below 0.5 (the period during which the photosynthetic pigment index decreases from its maximum value) is extracted as the period of reduced coverage. The period of reduced coverage often corresponds to the reproductive growth period of vegetation. In other words, the feature information estimation unit 315 extracts the period of reduced coverage based on the photosynthetic pigment index.

[0182] <4-4. Estimation Flow of Reference Information> Figure 11 shows an example of the estimation flow for reference information. As shown in Figure 11, in the estimation flow for reference information, first, the management server 103 obtains the evaluation area and evaluation period specified by the user (step S1110). Specifically, the target information acquisition unit 312 of the management server 103 obtains the evaluation area and evaluation period entered by the user.

[0183] After step S1110, the management server 103 acquires the information necessary for the estimation process (step S1120). Specifically, the reference information estimation unit 316 of the management server 103 identifies the reference information items for which estimation is required in this process and acquires the information necessary for that estimation. For example, if the estimation of the reference vegetation period for a specific vegetation type is required, the unit refers to the cultivation information table included in the cultivation information and acquires all the actual values ​​for the vegetation period corresponding to that type.

[0184] After step S1120, the management server 103 estimates the reference information (step S1130). Specifically, the reference information estimation unit 316 of the management server 103 estimates the reference information using the information acquired in step S1120. For example, if the estimation of the reference vegetation period for a specific vegetation type is requested, the average value of all acquired vegetation data is calculated and estimated as the reference vegetation period for that vegetation type. The estimated reference information is recorded as a new record in the vegetation type-specific reference period table in the auxiliary storage device 302.

[0185] [Vegetation period by vegetation type] The reference information estimation unit 316 is, · Obtain the vegetation period included in the feature information of the evaluation area where the vegetation type is known. · Obtain the temperature and solar radiation amount included in the meteorological information of the evaluation area where the vegetation type is known. · Calculate the vegetation period for each vegetation type by calculating the average value of the vegetation period for each vegetation type extracted. The obtained vegetation period may be corrected and then the average value may be calculated by comparing the obtained temperature and solar radiation amount with the standard temperature and solar radiation amount.

[0186] [Coverage rate increase period for each vegetation type] The reference information estimation unit 316 · Obtain the coverage rate increase period included in the feature information of the evaluation area where the vegetation type is known. · Obtain the temperature and solar radiation amount included in the meteorological information of the evaluation area where the vegetation type is known. · Calculate the coverage rate increase period for each vegetation type by calculating the average value of the extracted coverage rate increase period. The obtained vegetation period may be corrected and then the average value may be calculated by comparing the obtained temperature and solar radiation amount with the standard temperature and solar radiation amount.

[0187] [Coverage rate decrease period for each vegetation type] The reference information estimation unit 316 · Obtain the coverage rate decrease period included in the feature information of the evaluation area where the vegetation type is known. · Obtain the temperature and solar radiation amount included in the meteorological information of the evaluation area where the vegetation type is known. · Calculate the coverage rate decrease period for each vegetation type by calculating the average value of the extracted coverage rate decrease period for each vegetation type. The obtained vegetation period may be corrected and then the average value may be calculated by comparing the obtained temperature and solar radiation amount with the standard temperature and solar radiation amount.

[0188] [Maximum coverage period spectrum for each vegetation type] The reference information estimation unit 316 · Obtain the time-series spectrum of the evaluation area where the vegetation type is known. • Obtain the maximum cover period spectrum included in the characteristic information of the evaluation area where the vegetation type is known. • Obtain temperature and solar radiation, which are included in the weather information for evaluation areas with known vegetation types. • The maximum cover period spectrum for each vegetation type is calculated by determining the average value of the extracted maximum cover period spectra for each vegetation type.

[0189] [Spectrum at the end of vegetation by vegetation type] The reference information estimation unit 316 is, • Obtain time-series spectra of evaluation areas with known vegetation types. • Obtain the vegetation end spectrum, which is included in the characteristic information of the evaluation area where the vegetation type is known. • Obtain temperature and solar radiation, which are included in the weather information for evaluation areas with known vegetation types. • By calculating the average value of the extracted vegetation end spectra for each vegetation type, the vegetation end spectra for each vegetation type are calculated.

[0190] [Spectrum of increasing vegetation coverage by vegetation type] The reference information estimation unit 316 is, • Obtain time-series spectra of evaluation areas with known vegetation types. • Obtain the coverage increase phase spectrum, which is included in the characteristic information of the evaluation area where the vegetation type is known. • Obtain temperature and solar radiation, which are included in the weather information for evaluation areas with known vegetation types. • By calculating the average value of the extracted coverage increase period spectra for each vegetation type, the coverage increase period spectra for each vegetation type are calculated.

[0191] [Spectrum of Decline in Vegetation Coverage by Vegetation Type] The reference information estimation unit 316 is, • Obtain time-series spectra of evaluation areas with known vegetation types. • Obtain the spectrum of the period of decrease in vegetation coverage, which is included in the characteristic information of the evaluation area where the vegetation type is known. • Obtain temperature and solar radiation, which are included in the weather information for evaluation areas with known vegetation types. • By calculating the average value of the extracted coverage increase period spectra for each vegetation type, the coverage decrease period spectra for each vegetation type are calculated.

[0192] [Maintenance Respiratory Index by Vegetation Type] The reference information estimation unit 316 calculates the maintenance respiration coefficient for each vegetation type by calculating the average value of the maintenance respiration rate and vegetation carbon weight measured for each vegetation type from areas where the vegetation type is known.

[0193] [Growth and respiration coefficients by vegetation type] The reference information estimation unit 316 calculates the vegetation type-specific growth respiration coefficient by calculating the average value of the growth respiration rate and total primary production rate measured from areas where the vegetation type is known.

[0194] [Ratio of harvested carbon to net primary production] The reference information estimation unit 316 calculates the ratio of harvested carbon to net primary production by vegetation type by calculating the average value of the amount of carbon included in the harvested yield and the net primary production from areas where the vegetation type is known.

[0195] [Yield and harvested carbon ratio by vegetation type] The reference information estimation unit 316 calculates the yield-to-harvested carbon ratio by vegetation type by calculating the average value of the harvest yield and harvested carbon amount measured from areas where the vegetation type is known.

[0196] [Nitrogen utilization efficiency by vegetation type] The reference information estimation unit 316 calculates nitrogen utilization efficiency by vegetation type by calculating the average value of measured nitrogen demand and net primary production from areas where the vegetation type is known. Since nitrogen utilization efficiency by vegetation type changes depending on the growth stage of the vegetation, nitrogen utilization efficiency by vegetation type is calculated as time-series data.

[0197] [Light utilization efficiency by vegetation type] The reference information estimation unit 316 calculates the light utilization efficiency for each vegetation type by calculating the average value of the measured light utilization efficiency from areas where the vegetation type is known.

[0198] [Aeration structure coefficient by vegetation type] The reference information estimation unit 316 records the standard ratio of N2O released to the ground surface via the aeration tissue of vegetation to the total N2O produced in the soil, calculated from measured values ​​from past tests.

[0199] [N2O leaching coefficient by vegetation type] The reference information estimation unit 316 records the standard ratio of the amount of ammonium ions and nitrate ions in the soil that are not absorbed by vegetation, to the amount that is released into the atmosphere or leached out in water, as well as the amount that is released directly into the atmosphere, calculated from measured values ​​from past tests.

[0200] [N2O emission factors by vegetation type] The reference information estimation unit 316 records the standard ratio of nitrous oxide emissions to the total amount of ammonia nitrification and nitrate denitrification, calculated from measured values ​​from past tests.

[0201] [Nitrogen supply rate by fertilizer type] The reference information estimation unit 316 records the standard ratio of the amount of ammonium ions and nitrate ions supplied to the soil per unit time relative to the amount of fertilizer applied, calculated from measured values ​​from past tests.

[0202] [Standard fertilizer application rates by vegetation type and fertilizer type] The standard information estimation unit 316 records standard values ​​for each fertilization type, which are calculated from past surveys and represent the standard amount of fertilizer applied for each fertilization type. Standard values ​​for fertilizer application rates by vegetation type and fertilization type may vary depending on the region, such as national or administrative divisions; therefore, it may be helpful to record them separately for each region.

[0203] [Standard maximum photosynthetic pigment index by vegetation type and fertilization type] The reference information estimation unit 316 records standard values ​​for the maximum photosynthetic index for each vegetation type, calculated from past estimation results, for each fertilization type. Standard maximum photosynthetic pigment indexes for different vegetation types and fertilization types may vary by region, such as country or administrative division; therefore, it may be helpful to record them separately for each region.

[0204] [Standard photosynthetic pigment change rate by vegetation type and fertilization type] The reference information estimation unit 316 records standard values ​​for the standard photosynthetic pigment change rate for each vegetation type, calculated from past estimation results, for each fertilization type. Since the standard photosynthetic pigment change rates for each vegetation type and fertilization type may differ depending on the region, such as country or climate zone, they may also be recorded by region.

[0205] [Standard oxygen supply based on vegetation history] The reference information estimation unit 316 records standard values ​​of soil oxygen supply calculated from actual values ​​from past tests, according to the history of vegetation type (history of crop rotation, such as rice > wheat > rice).

[0206] [Standard moisture content by vegetation history] The reference information estimation unit 316 records standard values ​​of soil moisture content calculated from actual values ​​from past tests, according to the history of vegetation type (history of crop rotation, such as rice > wheat > rice).

[0207] [Soil organic carbon content by vegetation history] The reference information estimation unit 316 records standard values ​​of soil organic carbon content calculated from measured values ​​from past tests, according to the history of vegetation type (history of crop rotation, such as rice > wheat > rice).

[0208] [Aerobic decomposition rates by vegetation history] The reference information estimation unit 316 records the values ​​of the aerobic decomposition rate under standard temperature conditions, calculated from measured values ​​from past tests, for each vegetation type history (crop rotation history, such as rice > wheat > rice).

[0209] [Anaerobic decomposition rates by vegetation history] The reference information estimation unit 316 records the values ​​of the anaerobic decomposition rate under standard temperature conditions, calculated from measured values ​​from past tests, for each vegetation type history (crop rotation history, such as rice > wheat > rice).

[0210] <4-5. Estimation Flow of Cultivation Information> Figure 12 shows an example of the cultivation information estimation flow. As shown in Figure 12, in the cultivation information estimation flow, first, the management server 103 obtains the evaluation area and evaluation period specified by the user (step S1210). Specifically, the target information acquisition unit 312 of the management server 103 obtains the evaluation area and evaluation period entered by the user.

[0211] After step S1210, the management server 103 acquires the information necessary for the estimation process (step S1220). Specifically, the cultivation information estimation unit 317 of the management server 103 identifies the items of cultivation information that are required to be estimated in this process and acquires the information necessary for that estimation. For example, if the estimation of the vegetation type in a specific evaluation area is required as cultivation information, the cultivation information estimation unit 317 acquires the photosynthetic pigment index from the characteristic information of the evaluation area.

[0212] After step S1220, the management server 103 estimates the cultivation information (step S1230). Specifically, the cultivation information estimation unit 317 of the management server 103 estimates the cultivation information using the information acquired in step S1220. The specific estimation process by the cultivation information estimation unit 317 is described below in order for each item of cultivation information.

[0213] The cultivation information estimation unit 317 and the growth information estimation unit 318 are: • Obtain the spectrum during the coverage increase phase, the spectrum during the coverage decrease phase, and the spectrum during the maximum coverage phase, which are included in the characteristic information of the evaluation area. • Obtain the vegetation type-specific coverage increase period spectrum, vegetation type-specific coverage decrease period spectrum, and vegetation type-specific maximum coverage period spectrum included in the standard information for the evaluation area. Based on the degree of agreement between these extracted feature spectra and pre-stored reference spectra, the vegetation type in the evaluation area may be estimated. Alternatively, the vegetation type in the evaluation area may be estimated by combining the degree of spectral agreement and the degree of duration agreement. In other words, the feature information estimation unit 315 extracts a feature spectrum that includes the maximum coverage period spectrum and the coverage rate reduction period spectrum, and the growth information estimation unit 318 can estimate the vegetation type in the evaluation area based on the degree of agreement between the extracted feature spectrum and the pre-stored standard spectra for each vegetation type.

[0214] [Estimated tillage date] The cultivation information estimation unit 317 is, • Obtain solar radiation, precipitation, and humidity, which are included in the weather information for the evaluation area. • Obtain the time-series surface soil moisture index included in the characteristic information of the evaluation area, The tillage day is estimated to be the point at which the time-series change in the extracted surface soil moisture index exceeds the change in surface soil moisture index estimated based on precipitation and solar radiation since the last observation. The cultivation information estimation unit 317 may further estimate the tillage day using humidity. Furthermore, the tillage day may be estimated as the point at which the time-series change in the spatial distribution of the surface soil moisture index exceeds the assumed change in the surface soil moisture index estimated based on the precipitation, humidity, and solar radiation of the previous observation. This method utilizes the phenomenon in which tillage changes the spatial distribution of voids within the soil surface, and the amount of moisture from the lower layers reaching the surface changes due to the void structure, resulting in a change in the spatial distribution of the surface soil moisture index.

[0215] [Estimated date of flooding] The cultivation information estimation unit 317 is, • Obtain the time-series spectrum of the evaluation area, • Obtain the dry soil spectrum included in the characteristic information of the evaluation area, - A flooded day is determined when the near-infrared reflectance of the observed time-series spectrum becomes 1 / 2 or less compared to the near-infrared reflectance of the dry soil spectrum. This utilizes the fact that the red to near-infrared band of incident reflected light is present due to the liquid water on the surface of the soil. Alternatively, the cultivation information estimation unit 317 may calculate the rate of decrease in the near-infrared reflectance and the rate of decrease in the blue reflectance of the observed time-series spectrum relative to the dry soil spectrum, and estimate a flooded day when the ratio of the rate of decrease in near-infrared reflectance to the rate of decrease in blue reflectance exceeds a predetermined threshold. The predetermined threshold is a value obtained from actual measurements.

[0216] [Estimation of nitrogen fertilization type] The cultivation information estimation unit 317 is, • Obtain solar radiation and temperature data included in the weather information for the evaluation area. • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, • Obtain the vegetation type included in the growth information for the evaluation area, • Obtain the standard photosynthetic pigment index change rate by vegetation type and fertilization type, which is included in the standard information for the evaluation area. The maximum time-series rate of change of the photosynthetic pigment index is corrected for solar radiation and temperature to calculate the maximum rate of change of the photosynthetic pigment index. The fertilization type is estimated based on the degree of agreement between the maximum value of the corrected rate of change in photosynthetic pigment index and the standard rate of change in photosynthetic pigment index for each vegetation type and fertilization type. In other words, the cultivation information estimation unit 317 corrects the maximum time-series rate of change of the photosynthetic pigment index by solar radiation and temperature to calculate the maximum rate of change of the photosynthetic pigment index, and estimates the fertilization type based on the degree of agreement between the maximum rate of change of the photosynthetic pigment index and the standard rate of change of the photosynthetic pigment index for each vegetation type and fertilization type.

[0217] [Estimation of nitrogen fertilizer application amount] The cultivation information estimation unit 317 is, • Obtain solar radiation and temperature data included in the weather information for the evaluation area. • Obtain the time-series photosynthetic pigment index included in the characteristic information of the evaluation area, • Obtain the vegetation type and fertilization type included in the growth information for the evaluation area. • Obtain the standard maximum photosynthetic index and standard fertilizer application rate for each vegetation type, which are included in the standard information for the evaluation area. • The maximum value of the time-series photosynthesis index is corrected for solar radiation and temperature. The amount of nitrogen fertilizer applied is estimated based on a value obtained by multiplying the ratio of the corrected maximum photosynthetic index to the standard maximum photosynthetic index for each vegetation type and fertilization type by the standard fertilization amount for each vegetation type and fertilization type. In other words, the cultivation information estimation unit 317 corrects the maximum value of the photosynthetic pigment index with the amount of solar radiation and temperature to calculate the maximum photosynthetic pigment index, and estimates the amount of fertilizer to be applied based on the ratio of the maximum photosynthetic pigment index to the standard maximum photosynthetic index for each vegetation type and fertilization type.

[0218] [Estimation of crop residue amount] The cultivation information estimation unit 317 is, • Obtain the vegetation carbon weight and harvested carbon amount included in the growth information for the evaluation area. The amount of crop residue is estimated by subtracting the harvested carbon weight from the vegetation carbon weight.

[0219] <4-6. Flowchart for Estimating Growth Information> Figure 13 shows an example of the growth information estimation flow. As shown in Figure 13, in the growth information estimation flow, first, the management server 103 obtains the evaluation area and evaluation period specified by the user (step S1310). Specifically, the target information acquisition unit 312 of the management server 103 obtains the evaluation area and evaluation period entered by the user.

[0220] After step S1310, the management server 103 acquires the information necessary for the estimation process (step S1320). Specifically, the growth information estimation unit 318 of the management server 103 identifies the items of growth information that are required to be estimated in this process and acquires the information necessary for that estimation. For example, if the estimation of vegetation cover rate in a specific evaluation area is required as growth information, the growth information estimation unit 318 acquires the photosynthetic pigment index and the maximum cover period spectrum and minimum cover period spectrum from the characteristic information of the evaluation area.

[0221] After step S1320, the management server 103 estimates the growth information (step S1330). Specifically, the growth information estimation unit 318 of the management server 103 estimates the growth information using the information acquired in step S1320. The specific estimation process by the growth information estimation unit 318 is described below in order for each item of growth information.

[0222] [Estimation of vegetation type] The cultivation information estimation unit 317 and the growth information estimation unit 318 are: • Obtain and extract feature spectra, including the maximum coverage period spectrum and the coverage reduction period spectrum, which are included in the characteristic information of the evaluation area. • Obtain the feature period, including the period of coverage increase and the period of coverage decrease, which is included in the feature information of the evaluation area. The vegetation type is estimated based on the degree of agreement between the extracted feature spectrum and the pre-stored reference spectrum for each vegetation type, and the degree of agreement between the extracted feature period and the pre-stored reference period for each vegetation type. In other words, the feature information estimation unit 315 extracts feature periods including periods of increased coverage and periods of decreased coverage based on the photosynthetic pigment index of the evaluation area, and the growth information estimation unit 318 estimates the vegetation type in the evaluation area based on the degree of agreement between the extracted feature periods and pre-stored standard periods for each vegetation type. The growth information estimation unit 318 may estimate the vegetation type in the evaluation area based solely on the degree of agreement between the extracted feature spectrum and the pre-stored standard spectrum for each vegetation type. Alternatively, the growth information estimation unit 318 may estimate the vegetation type in the evaluation area based solely on the degree of agreement between the extracted feature period and the pre-stored standard feature period for each vegetation type.

[0223] [Estimation of vegetation cover] The growth information estimation unit 318 is, • Obtain the maximum coverage spectrum and minimum coverage spectrum included in the characteristic information of the evaluation area. The vegetation cover rate in the evaluation area is calculated by linearly interpolating the observed multispectral reflectance (spectral value) between the previously extracted maximum cover period spectrum and minimum cover period spectrum.

[0224] [Estimate of total primary production] The growth information estimation unit 318 is, • Obtain solar radiation, temperature, and precipitation, which are included in the weather information for the evaluation area. • Obtain the vegetation type and vegetation cover rate included in the growth information for the evaluation area. • Obtain the light utilization efficiency by vegetation type, which is included in the standard information for the evaluation area. • Calculate photosynthetically active radiation (PAR) from solar radiation. The absorbed photosynthetically active radiation is calculated by multiplying the calculated photosynthetically active radiation by the vegetation cover rate and correcting this value by the maximum value of the time-series photosynthetic pigment index. The total primary production is calculated by multiplying the calculated absorbed photosynthetically active radiation by the light utilization efficiency for each vegetation type and integrating the result over the evaluation period.

[0225] [Estimation of vegetation respiration] The growth information estimation unit 318 is, • Obtain the temperature included in the weather information for the evaluation area. • Obtain the vegetation type, total primary production, and vegetation carbon weight included in the growth information for the evaluation area. • Obtain the growth and respiration coefficients by vegetation type and the maintenance and respiration coefficients by vegetation type, which are included in the standard information for the evaluation area. • The growth and respiration rate is calculated by multiplying the gross primary production (GPP) by the growth and respiration coefficient for each vegetation type. • The maintenance respiration rate is calculated by multiplying the vegetation carbon weight by the maintenance respiration coefficient for each vegetation type. • Vegetation respiration is calculated by adding growth respiration and maintenance respiration. Maintenance respiration and growth respiration may be corrected for temperature.

[0226] [Estimate of net primary production] The growth information estimation unit 318 is, • Obtain the total primary production and vegetation respiration included in the growth information for the evaluation area. • Net primary production is estimated by subtracting vegetation respiration from total primary production.

[0227] [Estimation of harvested carbon] The growth information estimation unit 318 is, • Obtain the vegetation type and net primary production volume included in the growth information for the evaluation area. • Obtain the yield index by vegetation type, which is included in the standard information for the evaluation area. The amount of harvested carbon is calculated by multiplying the net primary production by a vegetation type-specific yield index (such as the Harvest Index) and integrating the result over the relevant period.

[0228] [Yield estimation] The growth information estimation unit 318 is, • Obtain the vegetation type and harvested carbon amount included in the growth information for the evaluation area. • Obtain the yield-to-carbon ratio by vegetation type, which is included in the standard information for the evaluation area. The yield of the crop is estimated by multiplying the acquired harvested carbon amount by the yield-to-harvested carbon amount ratio for each vegetation type.

[0229] [Estimation of vegetation nitrogen demand] The growth information estimation unit 318 is, • Obtain the vegetation type and net primary production volume included in the growth information for the evaluation area. • Obtain nitrogen utilization efficiency by vegetation type, which is included in the standard information for the evaluation area. • Vegetation nitrogen demand is calculated by dividing net primary production (NPP) by nitrogen utilization efficiency for each vegetation type.

[0230] [Estimation of vegetation carbon weight] The growth information estimation unit 318 is, • Obtain the vegetation cover rate and net primary production, which are included in the growth information for the evaluation area. • The vegetation carbon weight in the area is estimated by integrating net primary production over the observation period from the point in time when vegetation cover is at its minimum.

[0231] <4-7. Estimation Flow of Soil Information> Figure 14 shows an example of the soil information estimation flow. As shown in Figure 14, in the soil information estimation flow, first, the management server 103 obtains the evaluation area and evaluation period specified by the user (step S1410). Specifically, the target information acquisition unit 312 of the management server 103 obtains the evaluation area and evaluation period entered by the user.

[0232] After step S1410, the management server 103 acquires the information necessary for the estimation process (step S1420). Specifically, the soil information estimation unit 319 of the management server 103 identifies the items of soil information that are required to be estimated in this process and acquires the information necessary for that estimation. For example, if the estimation of soil temperature in a specific evaluation area is required as soil information, the soil information estimation unit 319 acquires vegetation cover rate information from the growth information of the evaluation area and temperature, solar radiation, and humidity from the weather information of the evaluation area.

[0233] After step S1420, the management server 103 estimates soil information (step S1430). Specifically, the soil information estimation unit 319 of the management server 103 estimates soil information using the information acquired in step S1420. The specific estimation process by the soil information estimation unit 319 is described below in order for each item of soil information.

[0234] [Estimation of soil temperature] The soil information estimation unit 319 is • Obtain temperature, solar radiation, and humidity, which are included in the weather information for the evaluation area. • Obtain the vegetation cover rate included in the growth information for the evaluation area. Based on a numerical model with temperature, solar radiation, humidity, and vegetation cover as input variables, soil temperature change values ​​were estimated. The soil temperature is calculated by adding the calculated soil temperature change to the previous soil temperature. The reason for including vegetation cover as an input variable is to reflect the fact that when the proportion covered by vegetation is high (high vegetation cover), solar energy does not easily reach the soil, and the temperature does not rise easily. A concrete example of a numerical model is to multiply the temperature by a value proportional to the amount of solar radiation and a value inversely proportional to the vegetation cover.

[0235] [Estimation of soil oxygen supply] The soil information estimation unit 319 is • Obtain the weather information included in the evaluation area, • Obtain the vegetation type and vegetation cover rate included in the growth information for the evaluation area. • Obtain the tillage date and flooding date included in the cultivation information for the evaluation area. • Obtain the standard oxygen supply amount by vegetation history included in the standard information for the evaluation area, The soil information estimation unit 319 estimates the soil oxygen supply by adding the physical oxygen supply due to tillage and the oxygen supply associated with vegetation cover to the standard oxygen supply amount for each vegetation history, which is set from the history of vegetation types cultivated in the past.

[0236] Furthermore, soil texture (clay content, permeability), groundwater level, evapotranspiration, and soil aggregate structure are also significant influencing factors. If this additional data (such as soil classification information and groundwater level data) can be obtained, it is possible to model soil oxygen supply with greater precision.

[0237] [Estimation of soil moisture content] The soil information estimation unit 319 is • Obtain precipitation and solar radiation data included in the weather information for the evaluation area. • Obtain the vegetation cover rate included in the growth information for the evaluation area, • Obtain the standard moisture content by vegetation history included in the standard information for the evaluation area, Based on a numerical model with precipitation, solar radiation, humidity, and vegetation cover as input variables, the amount of water supplied is calculated. • Soil moisture content is determined by adding the water supply amount to the standard moisture content for each vegetation history.

[0238] Furthermore, soil moisture content is greatly influenced by factors such as soil texture (sandy, clayey, loamy, etc.), permeability, and groundwater level. In this embodiment, a field is provided where the user can register soil classification and groundwater level information, and it is also possible to implement a model that corrects the soil moisture retention curve and drainage coefficient using this information.

[0239] [Estimation of soil nitrogen supply] The soil information estimation unit 319 is • Obtain temperature and solar radiation data included in the weather information for the evaluation area. • Obtain the fertilizer type and fertilizer amount included in the cultivation information for the evaluation area. • Obtain the soil moisture content included in the soil information for the evaluation area, • Obtain the nitrogen supply ratio by fertilization type, which is included in the standard information for the evaluation area. By correcting the nitrogen supply ratio for each fertilization type for temperature and soil moisture content, the time-series nitrogen supply ratio is estimated. The amount of nitrogen supplied is estimated based on the value obtained by multiplying the amount of nitrogen fertilizer applied by the time-series nitrogen supply ratio.

[0240] [Estimation of soil organic carbon content] The soil information estimation unit 319 is • Obtain the net primary production, harvested carbon, and soil organic matter decomposition amount included in the growth information for the evaluation area. • Obtain the amount of soil organic carbon at the previous point in time, which is included in the soil information for the evaluation area. • Obtain the soil organic carbon content by vegetation history, which is included in the standard information for the evaluation area. • The change in soil organic carbon content is calculated by subtracting the amount of harvested carbon and the amount of soil organic matter decomposition from the net primary production. • The amount of soil organic carbon is calculated by adding the change in soil organic carbon to the amount of soil organic carbon at the previous point in time. If the soil organic carbon content value for the previous period is unavailable, the soil organic carbon content is calculated by adding the change in soil organic carbon content to the soil organic carbon content value for each vegetation history.

[0241] [Estimation of aerobic decomposition rate] The soil information estimation unit 319 is • Obtain temperature and solar radiation data included in the weather information for the evaluation area. • Obtain soil oxygen supply, soil moisture content, and soil temperature, which are included in the soil information for the evaluation area. • Obtain the aerobic decomposition rate by vegetation history, which is included in the standard information for the evaluation area. The aerobic decomposition rate for each vegetation type is estimated by correcting it for soil oxygen supply, soil moisture content, soil temperature, and soil nitrogen supply.

[0242] [Estimation of anaerobic decomposition rate] The soil information estimation unit 319 is • Obtain temperature and solar radiation data included in the weather information for the evaluation area. • Obtain soil oxygen supply, soil moisture content, and soil temperature, which are included in the soil information for the evaluation area. • Obtain the anaerobic decomposition rate by vegetation history, which is included in the standard information for the evaluation area. The anaerobic decomposition rate for each vegetation type is estimated by correcting it for soil oxygen supply, soil moisture content, soil temperature, and soil nitrogen supply.

[0243] [Estimation of nitrification-denitrification rates] The soil information estimation unit 319 is • Obtain temperature and solar radiation data included in the weather information for the evaluation area. • Obtain soil oxygen supply, soil moisture content, and soil temperature, which are included in the soil information for the evaluation area. • Obtain the nitrification-denitrification rates by vegetation history, which are included in the standard information for the evaluation area. The nitrification-denitrification rate is estimated by correcting the anaerobic decomposition rate for each vegetation type using soil oxygen supply, soil moisture content, soil temperature, and soil nitrogen supply.

[0244] [Estimation of soil organic matter decomposition rate] The soil information estimation unit 319 is • Obtain the soil organic carbon content, aerobic decomposition rate, and anaerobic decomposition rate included in the soil information of the evaluation area. The amount of soil organic matter decomposed is calculated by adding the value obtained by multiplying the amount of soil organic carbon by the aerobic decomposition rate to the value obtained by multiplying the amount of soil organic carbon by the aerobic decomposition rate.

[0245] [Estimation of excess nitrogen in soil] The soil information estimation unit 319 is • Obtain the vegetation nitrogen demand included in the growth information for the evaluation area, • Obtain the amount of soil nitrogen supply included in the soil information of the evaluation area, • Subtract the vegetation nitrogen demand from the soil nitrogen supply to calculate the excess soil nitrogen.

[0246] <4-8. Flowchart for Estimating Environmental Impact Information> Figure 15 shows an example of the estimation flow for environmental load information. As shown in Figure 15, in the estimation flow for environmental load information, first, the management server 103 obtains the evaluation area and evaluation period specified by the user (step S1510). Specifically, the target information acquisition unit 312 of the management server 103 obtains the evaluation area and evaluation period entered by the user.

[0247] After step S1510, the management server 103 acquires the information necessary for the estimation process (step S1520). Specifically, the environmental load information estimation unit 320 of the management server 103 identifies the items of environmental load information that are required to be estimated in this process and acquires the information necessary for that estimation. For example, if the estimation of the increase or decrease in SOC in a specific evaluation area is required as environmental load information, the environmental load information estimation unit 320 acquires the total primary production, harvested carbon, and vegetation respiration included in the growth information of the evaluation area, as well as the amount of soil organic matter decomposition included in the soil information.

[0248] After step S1520, the management server 103 estimates the environmental load information (step S1530). Specifically, the environmental load information estimation unit 320 of the management server 103 estimates the environmental load information using the information acquired in step S1520. The specific estimation process by the environmental load information estimation unit 320 is described below in order for each item of environmental load information.

[0249] [Estimated CO2 emissions] The environmental load information estimation unit 320 is: • Obtain the total primary production and vegetation respiration included in the growth information for the evaluation area. • Obtain the amount of harvested carbon included in the cultivation information for the evaluation area. • Obtain the amount of soil organic matter decomposition included in the soil information of the evaluation area, Obtain, The CO2 emissions in the evaluation area are calculated by adding vegetation respiration, soil organic matter decomposition, and harvested carbon, subtracting the total primary production, and accumulating these values ​​over the evaluation period.

[0250] [Estimated N2O emissions] The environmental load information estimation unit 320 is: • Obtain the vegetation type and vegetation nitrogen demand included in the growth information for the evaluation area. • Obtain soil nitrogen supply and nitrification-denitrification rate included in the soil information of the evaluation area. Based on the vegetation type, obtain the N2O leaching and runoff coefficients and N2O emission coefficients for each vegetation type, which are included in the standard information for the evaluation area. • Subtract the vegetation nitrogen demand from the soil nitrogen supply to calculate the excess nitrogen amount. The indirect N2O emissions were calculated based on the value obtained by multiplying the calculated excess nitrogen amount by the N2O leaching coefficient for each vegetation type and integrating the result over the evaluation period. The direct N2O emissions are calculated by multiplying the calculated excess nitrogen amount by the nitrification-denitrification rate and the N2O emission factor for each vegetation type, and accumulating these values ​​over the evaluation period. • The calculated direct N2O emissions are added to the indirect N2O emissions to determine the total N2O emissions. In other words, the environmental load information estimation unit 320 calculates the excess nitrogen amount by subtracting the vegetation nitrogen demand amount from the soil nitrogen supply amount, and estimates the N2O emission amount based on the value obtained by multiplying the excess nitrogen amount by the nitrification-denitrification rate.

[0251] [Estimated CH4 emissions] The environmental load information estimation unit 320 is: • Obtain the vegetation type included in the growth information for the evaluation area, • Obtain the amount of crop residue included in the cultivation information for the evaluation area. • Obtain the anaerobic decomposition rate and aerobic decomposition rate included in the soil information of the evaluation area. Based on the vegetation type, obtain the aeration tissue coefficient for each vegetation type, which is included in the standard information for the evaluation area. The amount of decomposed crop residue is calculated by multiplying the amount of crop residue by the aerobic decomposition rate. • Subtract the amount of decomposed crop residue from the amount of crop residue to calculate the amount of undecomposed crop residue. • The amount of undecomposed crop residue is multiplied by the anaerobic decomposition rate to calculate the amount of CH4 produced. The calculated CH4 generation amount is multiplied by the aeration tissue coefficient for each vegetation type to calculate the amount of CH4 discharged via the aeration tissue. The amount of CH4 oxidation is calculated by subtracting the amount of CH4 emissions via the aeration tissue from the calculated amount of CH4 generated, multiplying this value by the aerobic decomposition rate, and then accumulating the values ​​obtained by subtracting the amount of CH4 oxidation from the amount of CH4 generated over the evaluation period to calculate the amount of CH4 emissions in the evaluation area. In other words, the environmental load information estimation unit 320 calculates the amount of undecomposed crop residue by subtracting from the amount of crop residue the value obtained by multiplying the amount of crop residue by the aerobic decomposition rate, and estimates the amount of CH4 emissions based on the value obtained by multiplying the amount of undecomposed crop residue by the anaerobic decomposition rate.

[0252] Thus, the present invention is a system for visualizing the environmental impact of agricultural land, A target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to visualization of environmental impact, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A weather information acquisition unit that acquires weather information including solar radiation, temperature, and precipitation, A feature information estimation unit estimates feature information including a photosynthetic pigment index indicating the photosynthetic pigment density in the evaluation area and a surface soil moisture index indicating the amount of moisture on the ground surface in the evaluation area, based on a time-series spectrum. Based on characteristic information, a growth information estimation unit estimates growth information indicating the growth state of vegetation in the evaluation area, Based on characteristic information, a cultivation information estimation unit estimates cultivation information indicating the cultivation status of vegetation in the evaluation area, A soil information estimation unit that estimates soil information indicating the soil condition in the evaluation area based on characteristic information, An environmental load information estimation unit estimates environmental load information, including at least one of CO2 emissions, N2O emissions, and CH4 emissions in the evaluation area, based on at least one of weather information, growth information, soil information, and cultivation information. This is an environmental load visualization system for farmland, characterized by comprising an output unit that visualizes and displays the calculated environmental load information. In this way, System 1 can visualize various environmental burdens of agriculture. Furthermore, it can estimate not only environmental burden information but also various types of information necessary for field management.

[0253] It should be noted that the present invention is not limited to the embodiments described above, and various modifications are included. For example, the embodiments described above are described in detail to make the present invention easier to understand, and are not necessarily limited to those having all the configurations described. Furthermore, it is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add configurations from other embodiments to the configuration of one embodiment. In addition, it is possible to add, delete, or replace parts of the configuration of each embodiment with other configurations.

[0254] Furthermore, each of the above configurations, functions, processing units, and processing means may be implemented in hardware, either partially or entirely, by designing them as integrated circuits, for example. Alternatively, each of the above configurations and functions may be implemented in software by having the processor interpret and execute programs that implement each function. Information such as programs, tables, and files that implement each function can be stored in memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0255] Furthermore, the control lines and information lines shown are those deemed necessary for explanatory purposes, and not all control lines and information lines are necessarily shown in the actual product. In reality, it is safe to assume that almost all components are interconnected. Furthermore, the above-described embodiments disclose at least the configuration described in the claims. Furthermore, the above-mentioned embodiments disclose at least the following: (1) This is a system for visualizing the environmental impact of agricultural land. A target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to visualization of environmental impact, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A weather information acquisition unit that acquires weather information including solar radiation, temperature, and precipitation, A feature information estimation unit estimates feature information including a photosynthetic pigment index indicating the photosynthetic pigment density in the evaluation area and a surface soil moisture index indicating the amount of moisture on the ground surface in the evaluation area, based on the aforementioned time-series spectrum. Based on the aforementioned characteristic information, a growth information estimation unit estimates growth information indicating the growth state of vegetation in the evaluation area, Based on the aforementioned characteristic information, a cultivation information estimation unit estimates cultivation information indicating the cultivation status of vegetation in the evaluation area, A soil information estimation unit estimates soil information indicating the soil condition in the evaluation area based on the aforementioned characteristic information, An environmental load information estimation unit estimates environmental load information, including at least one of CO2 emissions, N2O emissions, and CH4 emissions in the evaluation area, based on at least one of the aforementioned weather information, growth information, soil information, and cultivation information. A system for visualizing the environmental impact of agricultural land, characterized by comprising: an output unit that visualizes and displays calculated environmental impact information. (2) (1) A system for visualizing the environmental impact of agricultural land, The feature information estimation unit, Using the green reflectance, red reflectance, and near-infrared reflectance included in the aforementioned time-series spectrum, A system for visualizing the environmental burden of agricultural land, characterized in that it calculates the photosynthetic pigment index based on a value obtained by subtracting a value obtained by multiplying the difference between the red reflectance and the green reflectance by a second positive coefficient from a value obtained by multiplying the difference between the near-infrared reflectance and the red reflectance by a first positive coefficient. (3) (1) A system for visualizing the environmental impact of agricultural land, The feature information estimation unit, From the aforementioned time-series spectrum, a soil spectrum is extracted based on the photosynthetic pigment index. From the aforementioned soil spectrum, dry soil spectra and wet soil spectra are extracted based on the average reflectance across the entire wavelength range. A system for visualizing the environmental load of agricultural land, characterized by calculating the surface soil moisture index by linearly interpolating the observed time-series spectrum between the dry soil spectrum and the wet soil spectrum. (4) (1) A system for visualizing the environmental impact of agricultural land, The feature information estimation unit, From the time-series spectra of the evaluation area, the maximum coverage period spectrum, which shows the spectrum when the photosynthetic pigment index is at its maximum, From the time-series spectrum of the evaluation area, a characteristic spectrum is extracted that includes a coverage reduction phase spectrum showing the spectrum when the photosynthetic pigment index decreases. The aforementioned growth information estimation unit is, A system for visualizing the environmental impact of agricultural land, characterized by estimating the vegetation type in the evaluation area based on the degree of agreement between the extracted feature spectrum and a pre-stored standard spectrum for each vegetation type. (5) (1) A system for visualizing the environmental impact of agricultural land, The feature information estimation unit, Based on the photosynthetic pigment index of the evaluation area, a characteristic period including the period of increasing coverage and the period of decreasing coverage is extracted. The aforementioned growth information estimation unit is, A system for visualizing the environmental impact of agricultural land, characterized by estimating the vegetation type in the evaluation area based on the degree of agreement between the extracted characteristic period and a pre-stored standard period for each vegetation type. (6) (1) A system for visualizing the environmental impact of agricultural land, The feature information estimation unit, From the time-series spectrum of the evaluation area, the spectrum of the maximum coverage period and the spectrum of the minimum coverage period are estimated. The aforementioned growth information estimation unit estimates the vegetation cover rate by linearly interpolating the observed spectral values ​​between the maximum cover period spectrum and the minimum cover period spectrum, thereby providing a system for visualizing the environmental load of agricultural land. (7) (1) A system for visualizing the environmental impact of agricultural land, The cultivation information estimation unit, A system for visualizing the environmental burden on farmland, characterized in that the time-series change in the surface soil moisture index exceeds the change in the surface soil moisture index that can be expected from the amount of precipitation and the amount of solar radiation, and the point at which this change is estimated to be the tillage day. (8) (1) A system for visualizing the environmental impact of agricultural land, The feature information estimation unit, From the aforementioned time-series spectrum, based on the surface soil moisture index, a dry soil spectrum showing the spectrum at the minimum of the surface soil moisture index is extracted. The cultivation information estimation unit, A system for visualizing the environmental load of agricultural land, characterized by calculating the rate of decrease in near-infrared reflectance and the rate of decrease in blue reflectance of the observed time-series spectrum with respect to the dry soil spectrum, and estimating the point in time when the ratio of the rate of decrease in near-infrared reflectance and the rate of decrease in blue reflectance exceeds a predetermined threshold as a flooded day. (9) (1) A system for visualizing the environmental impact of agricultural land, The aforementioned growth information estimation unit estimates total primary production, vegetation respiration, and harvested carbon. The soil information estimation unit estimates the amount of soil organic matter decomposition, The aforementioned environmental load information estimation unit, A system for visualizing the environmental burden of agricultural land, characterized by estimating CO2 emissions based on a value obtained by subtracting the total primary production from a value obtained by adding the amount of soil organic matter decomposition and the amount of harvested carbon to the amount of vegetation respiration. (10) (1) A system for visualizing the environmental impact of agricultural land, The aforementioned growth information estimation unit estimates the vegetation nitrogen demand, The aforementioned soil information estimation unit estimates the soil nitrogen supply amount and the nitrification-denitrification rate. The aforementioned environmental load information estimation unit, The amount of excess nitrogen is calculated by subtracting the amount of vegetation nitrogen demand from the amount of soil nitrogen supply. A system for visualizing the environmental burden of agricultural land, characterized by estimating N2O emissions based on a value obtained by multiplying the excess nitrogen amount by the nitrification-denitrification rate. (11) (1) A system for visualizing the environmental impact of agricultural land, The cultivation information estimation unit estimates the amount of crop residue, The aforementioned soil information estimation unit estimates the anaerobic decomposition rate and the aerobic decomposition rate. The aforementioned environmental load information estimation unit, The amount of undecomposed crop residue is calculated by subtracting the amount of crop residue multiplied by the aerobic decomposition rate from the amount of crop residue. A system for visualizing the environmental burden on farmland, characterized by estimating CH4 emissions based on a value obtained by multiplying the amount of undecomposed crop residue by the anaerobic decomposition rate. (12) (1) A system for visualizing the environmental impact of agricultural land, A farmland environmental load visualization system, further comprising a reference information estimation unit that estimates standard characteristic values ​​for at least one type of information, such as vegetation type, fertilization type, and vegetation history, in the aforementioned evaluation area. (13) (12) A system for visualizing the environmental impact of agricultural land, The aforementioned growth information estimation unit estimates the vegetation type and vegetation cover rate, The aforementioned reference information estimation unit acquires light utilization efficiency by vegetation type based on the vegetation type, The aforementioned growth information estimation unit calculates the photosynthetically active radiation based on the amount of solar radiation, Based on the value obtained by multiplying the aforementioned photosynthetically active radiation by the vegetation cover rate and correcting it with the maximum value of the time-series photosynthetic pigment index, the absorbed photosynthetically active radiation is calculated. A system for visualizing the environmental impact of farmland, characterized by calculating the total primary production by integrating the value obtained by multiplying the absorbed photosynthetically active radiation by the light utilization efficiency for each vegetation type over the evaluation period. (14) (12) A system for visualizing the environmental impact of agricultural land, The aforementioned growth information estimation unit estimates the vegetation type, total primary production, and vegetation carbon weight. The aforementioned reference information estimation unit obtains the vegetation type-specific growth respiration coefficient and the vegetation type-specific maintenance respiration coefficient based on the vegetation type. The aforementioned growth information estimation unit is, Based on the value obtained by multiplying the total primary production by the growth-respiration coefficient for each vegetation type, the growth-respiration rate is calculated. Based on the value obtained by multiplying the vegetation carbon weight by the vegetation type-specific maintenance respiration coefficient, the maintenance respiration rate is calculated. A system for visualizing the environmental burden of agricultural land, characterized by estimating vegetation respiration based on a value obtained by adding the growth respiration rate to the maintenance respiration rate. (15) (12) A system for visualizing the environmental impact of agricultural land, The aforementioned growth information estimation unit estimates the vegetation type, The aforementioned reference information estimation unit obtains the rate of change of standard photosynthetic pigment index for each vegetation type and fertilization type based on the vegetation type, The cultivation information estimation unit corrects the maximum time-series rate of change of the photosynthetic pigment index using the amount of solar radiation and the temperature to calculate the maximum rate of change of the photosynthetic pigment index. A system for visualizing the environmental load of agricultural land, characterized by estimating the fertilization type based on the degree of agreement between the maximum photosynthetic pigment index change rate and the standard photosynthetic pigment index change rate for each vegetation type and fertilization type. (16) (12) A system for visualizing the environmental impact of agricultural land, The aforementioned growth information estimation unit estimates the vegetation type, The cultivation information estimation unit estimates the fertilization type, The standard information estimation unit obtains the standard maximum photosynthetic index for each vegetation type and fertilization type based on the vegetation type and the fertilization type. The cultivation information estimation unit corrects the maximum value of the photosynthetic pigment index with the amount of solar radiation and the temperature to calculate the maximum photosynthetic pigment index. A system for visualizing the environmental burden of agricultural land, characterized by estimating the amount of fertilizer to be applied based on the ratio of the maximum photosynthetic pigment index to the standard maximum photosynthetic index for each vegetation type and fertilization type. [Explanation of symbols]

[0256] 1…Environmental load visualization system, 103…Management server, 311…Input information acquisition unit, 312…Target information acquisition unit, 313…Weather information acquisition unit, 314…Spectrum information acquisition unit, 315…Feature information estimation unit, 316…Reference information estimation unit, 317…Cultivation information estimation unit, 318…Growth information estimation unit, 319…Soil information estimation unit, 320…Environmental load information estimation unit, 321…Output unit

Claims

1. A system for estimating the environmental impact of agricultural land, A target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to environmental load estimation, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A growth information estimation unit estimates growth information including at least one of vegetation type or vegetation cover rate based on the aforementioned time-series spectrum, Based on the aforementioned time-series spectrum, a cultivation information estimation unit estimates cultivation information including the flooding period and tillage date, Based on the aforementioned growth information and the cultivation information including the flooding period and tillage date, the CH in the evaluation area ４ An environmental load information estimation unit that estimates environmental load information including emissions, A system for estimating the environmental impact of agricultural land, characterized by comprising the following features.

2. A system for estimating the environmental impact of agricultural land, A target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to environmental load estimation, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A growth information estimation unit estimates growth information including at least one of vegetation type or vegetation cover rate based on the aforementioned time-series spectrum, Based on the aforementioned time-series spectrum, a cultivation information estimation unit estimates cultivation information including tillage date and fertilizer application amount, Based on the aforementioned growth information and the cultivation information including the tillage date and the amount of fertilizer applied, N in the evaluation area ２ An environmental load information estimation unit that estimates environmental load information including emissions, A system for estimating the environmental impact of agricultural land, characterized by comprising the following features.

3. A system for estimating the environmental impact of agricultural land, A target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to environmental load estimation, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A growth information estimation unit estimates growth information including at least one of vegetation type or vegetation cover rate based on the aforementioned time-series spectrum, Based on the aforementioned time-series spectrum, a cultivation information estimation unit estimates cultivation information including the tillage date and flooding period, Based on the aforementioned growth information and the cultivation information including the tillage date and the flooding period, the CO2 in the evaluation area ２ An environmental load information estimation unit that estimates environmental load information including emissions, A system for estimating the environmental impact of agricultural land, characterized by comprising the following features.

4. A system for estimating the environmental impact of agricultural land, A target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to environmental load estimation, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A growth information estimation unit estimates growth information including at least one of vegetation type or vegetation cover rate based on the aforementioned time-series spectrum, Based on the aforementioned time-series spectrum, a cultivation information estimation unit estimates cultivation information including the tillage date and flooding period, An environmental load information estimation unit estimates environmental load information, including soil organic carbon content, in the evaluation area based on the aforementioned growth information and cultivation information including the tillage date and the flooding period. A system for estimating the environmental impact of agricultural land, characterized by comprising the following features.

5. A system for estimating the environmental impact of agricultural land, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A cultivation information estimation unit estimates the flooded state based on the rate of decrease in the reflectance in the visible light range of the aforementioned time-series spectrum, Equipped with, The cultivation information estimation unit estimates intermittent irrigation, in which water is released periodically or irregularly, based on the rate of decrease in the reflectance of the visible light region of the time-series spectrum. A system for estimating the environmental impact of agricultural land, characterized by the following features.

6. A farmland environmental load estimation system according to claim 5, The cultivation information estimation unit estimates the water level based on the rate of decrease in the reflectance of the visible light region of the time-series spectrum, and estimates intermittent irrigation, which involves periodically or irregularly releasing water, based on the fluctuation range of the water level. A system for estimating the environmental impact of agricultural land, characterized by the following features.

7. A system for estimating the environmental impact of agricultural land, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A cultivation information estimation unit estimates the flooded state based on the rate of decrease in the reflectance in the visible light range of the aforementioned time-series spectrum, Equipped with, The cultivation information estimation unit estimates the flooded state based on the rate of decrease in the reflectance in the visible light range of the time-series spectrum, and estimates the period for mid-season drainage, which is the period when the field is not flooded. A system for estimating the environmental impact of agricultural land, characterized by the following features.

8. A system for estimating the environmental burden of agricultural land, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A cultivation information estimation unit estimates the surface soil moisture content based on the reflectance in the visible light range of the aforementioned time-series spectrum, and estimates the flooded state based on the surface soil moisture content. Equipped with, The cultivation information estimation unit estimates the surface soil moisture content based on the reflectance in the visible light range of the time-series spectrum, estimates the flooded state based on the surface soil moisture content, and estimates the period for mid-season drainage, which is the period when the soil is not flooded. A system for estimating the environmental impact of agricultural land, characterized by the following features.

9. A system for estimating the environmental impact of agricultural land, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A cultivation information estimation unit estimates the tillage date based on the rate of decrease in the reflectance in the visible light region of the aforementioned time-series spectrum, A system for estimating the environmental impact of agricultural land, characterized by comprising the following features.

10. The agricultural land environmental load estimation system according to claim 9, The cultivation information estimation unit estimates the surface soil moisture content based on the rate of decrease in the visible light reflectance of the time-series spectrum, and estimates the tillage date based on the range of change in the surface soil moisture content. A system for estimating the environmental impact of agricultural land, characterized by the following features.

11. A system for estimating the environmental impact of agricultural land, A spectral information acquisition unit that acquires a time-series spectrum including time-series multispectral ground surface reflectance, A cultivation information estimation unit estimates the vegetation type and photosynthetic pigment index based on the aforementioned time-series spectrum, and estimates the amount of nitrogen fertilizer based on the aforementioned vegetation type and photosynthetic pigment index. A system for estimating the environmental impact of agricultural land, characterized by comprising the following features.

12. A method for estimating the environmental burden of agricultural land, The target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to environmental load estimation. The spectral information acquisition unit acquires a time-series spectrum including the time-series multispectral ground surface reflectance. The growth information estimation unit estimates growth information, including at least one of vegetation type or vegetation cover rate, based on the time-series spectrum. The cultivation information estimation unit estimates cultivation information, including the flooding period and tillage date, based on the time-series spectrum. The environmental load information estimation unit estimates environmental load information, including CH4 emissions in the evaluation area, based on the growth information and the cultivation information, including the flooding period and the tillage date. A method for estimating the environmental impact of agricultural land, characterized by the features described above.

13. A method for estimating the environmental burden of agricultural land, The target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to environmental load estimation. The spectral information acquisition unit acquires a time-series spectrum including the time-series multispectral ground surface reflectance. The growth information estimation unit estimates growth information, including at least one of vegetation type or vegetation cover rate, based on the time-series spectrum. The cultivation information estimation unit estimates cultivation information, including the tillage date and fertilizer application amount, based on the time-series spectrum. The environmental load information estimation unit estimates environmental load information, including N2O emissions, in the evaluation area based on the growth information and the cultivation information, which includes the tillage date and the amount of fertilizer applied. A method for estimating the environmental impact of agricultural land, characterized by the features described above.

14. A method for estimating the environmental burden of agricultural land, The target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to environmental load estimation. The spectral information acquisition unit acquires a time-series spectrum including the time-series multispectral ground surface reflectance. The growth information estimation unit estimates growth information, including at least one of vegetation type or vegetation cover rate, based on the time-series spectrum. The cultivation information estimation unit estimates cultivation information, including the tillage date and flooding period, based on the time-series spectrum. The environmental load information estimation unit estimates environmental load information, including CO2 emissions in the evaluation area, based on the growth information and the cultivation information, including the tillage date and the flooding period. A method for estimating the environmental impact of agricultural land, characterized by the features described above.

15. A method for estimating the environmental burden of agricultural land, The target information acquisition unit acquires target information including the evaluation period and evaluation area that are subject to environmental load estimation. The spectral information acquisition unit acquires a time-series spectrum including the time-series multispectral ground surface reflectance. The growth information estimation unit estimates growth information, including at least one of vegetation type or vegetation cover rate, based on the time-series spectrum. The cultivation information estimation unit estimates cultivation information, including the tillage date and flooding period, based on the time-series spectrum. The environmental load information estimation unit estimates environmental load information, including the amount of soil organic carbon in the evaluation area, based on the growth information and the cultivation information, including the tillage date and the flooding period. A method for estimating the environmental impact of agricultural land, characterized by the features described above.

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