PROGRAM, INFORMATION PROCESSING APPARATUS, METHOD, AND SYSTEM

Abstract

Improve the accuracy of estimating non-flooded periods. [Solution] A program to be executed by a computer having a processor and a memory. The program causes the processor to execute the steps of acquiring address information indicating the address of the paddy field to identify a target paddy field, acquiring satellite images and water level information of the target paddy field each time a predetermined timing occurs within a predetermined period, calculating a first index indicating the flooded state of a section in the target paddy field corresponding to an image cell of the target paddy field for each of a plurality of image cells of a plurality of satellite images based on the image cell and the water level information, calculating a statistical value of the first index for each of the plurality of satellite images as a second index indicating the flooded state of the target paddy field, and estimating a non-flooded period of the target paddy field for a predetermined period based on a time-series change in the second index calculated for each of the plurality of satellite images.

Description

[Technical field]

[0001] The present disclosure relates to a program, an information processing device, a method, and a system. [Background technology]

[0002] In recent years, research and development into technology to estimate greenhouse gas emissions has become more active with the aim of creating carbon credits.

[0003] For example, Patent Document 1 discloses a technique for calculating a daily water index for each of a plurality of water management compartments included in a paddy field based on satellite data of the paddy field, and classifying the daily status of each of the plurality of water management compartments based on the satellite data and the calculated water index. The technique disclosed in Patent Document 1 also estimates non-flooded periods using the classified status. Furthermore, the technique disclosed in Patent Document 1 estimates daily water levels based on satellite data learned using water level measurement results as training data, and estimates daily greenhouse gas emissions based on the daily water levels. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 7460228 Summary of the Invention [Problem to be solved by the invention]

[0005] The technology disclosed in Patent Document 1 estimates the total greenhouse gas emissions based on the estimation results of the non-flooded period and the estimation results of the daily greenhouse gas emissions. However, the technology disclosed in Patent Document 1 has room for improvement in the estimation accuracy of the non-flooded period, which is a premise for estimating the total greenhouse gas emissions.

[0006] An object of the present disclosure is to improve the accuracy of estimating non-flooded periods. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, a program according to one aspect of the present disclosure is a program to be executed by a computer having a processor and a memory. The program causes the processor to execute the steps of acquiring address information indicating the address of the paddy field and specifying a target paddy field to be estimated, acquiring a satellite image of the target paddy field and water level information indicating the water level of the target paddy field at each predetermined timing in a predetermined period, calculating a first index indicating the flooded state of a section in the target paddy field corresponding to the image cell of each of the acquired satellite images based on the image cell and the water level information for each of the acquired satellite images, calculating a statistical value of the calculated first index in units of the target paddy field for each of the acquired satellite images as a second index indicating the flooded state of the target paddy field, and estimating a non-flooded period of the target paddy field in a predetermined period based on a time-series change in the second index calculated for each of the acquired satellite images. Effect of the Invention

[0008] According to the present disclosure, it is possible to improve the accuracy of estimating non-flooded periods. [Brief description of the drawings]

[0009] [Figure 1] 1 is a block diagram showing an example of the overall configuration of a system 1. FIG. [Diagram 2] 2 is a block diagram showing an example of the configuration of a terminal device 10 shown in FIG. [Diagram 3] 2 is a block diagram showing an example of the configuration of a server 20 shown in FIG. 1. [Figure 4] 4 is a diagram showing a data structure of a polygon table 2021 shown in FIG. 3. [Diagram 5] 13 is a flowchart showing an example of the operation of the server 20 when estimating a mid-drying period. [Figure 6]13 is a schematic diagram showing an example of a screen on the display 141 when application documents are presented to a user. FIG. [Figure 7] FIG. 13 is a schematic diagram showing another example of the screen of the display 141 when application documents are presented to the user. [Figure 8] FIG. 2 is a block diagram showing the basic hardware configuration of a computer 90. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. In all the drawings explaining the embodiment, the same reference numerals are given to common components, and repeated explanations are omitted. Note that the following embodiment does not unduly limit the contents of the present disclosure described in the claims. In addition, not all components shown in the embodiment are necessarily essential components of the present disclosure. In addition, each figure is a schematic diagram and is not necessarily illustrated strictly.

[0011] [1. Overview] The system according to the present embodiment acquires address information of the paddy field to identify the target paddy field. The system according to the present embodiment acquires SAR images of the target paddy field and water level information of the target paddy field at a predetermined timing each time a predetermined time period arrives. The system according to the present embodiment inputs the image cell and water level information for each of the plurality of image cells constituting the SAR image for each of the plurality of acquired SAR images into a trained machine learning model, and outputs a first index from the machine learning model. The system according to the present embodiment calculates a statistical value of the calculated first index for each of the plurality of acquired SAR images in units of the target paddy field, thereby calculating the statistical value as a second index. The system according to the present embodiment estimates the non-flooded period of the target paddy field in a predetermined period based on the time-series change of the second index calculated for each of the plurality of acquired SAR images.

[0012] [2. Overall system configuration] FIG. 1 is a block diagram showing an example of the overall configuration of system 1. System 1 is a system for providing a service for estimating the mid-drying period of a target paddy field (hereinafter, the estimation service). The target paddy field is a paddy field that is the subject of estimation by system 1.

[0013] In this embodiment, an example in which the system 1 estimates the mid-drainage period will be described, but the estimation by the system 1 is not limited to the mid-drainage period. The system 1 may estimate, for example, a non-flooded period after planting, a non-flooded period before harvesting, a non-flooded period after fertilization, a non-flooded period after pest control, etc. In other words, the system 1 may estimate the non-flooded period of the target paddy field.

[0014] 1 includes, for example, a terminal device 10, a server 20, an AI system 30, and an artificial satellite 40. The terminal device 10, the server 20, and the AI ​​system 30 are communicatively connected, for example, via a network 80. The artificial satellite 40 transmits, for example, various types of satellite data to a ground station (not shown). The ground station is communicatively connected to the network 80, and, for example, receives a transmission request from the server 20 and transmits the satellite data to the server 20 via the network 80.

[0015] 1 shows an example in which the system 1 includes one terminal device 10, but for example, the system 1 may include two or more terminal devices 10. In FIG. 1, an example in which the system 1 includes one server 20, but for example, a collection of multiple devices may be one server 20. The manner in which multiple functions required to realize the server 20 are allocated to one or multiple pieces of hardware can be determined appropriately depending on the processing capacity of each piece of hardware and / or the specifications required for the server 20, etc.

[0016] 1 shows an example in which the system 1 includes one AI system 30, but the system 1 may include two or more AI systems 30. Also, while FIG. 1 shows an example in which the AI ​​system 30 is independent from the server 20, the server 20 may include the functions of the AI ​​system 30. In other words, the server 20 may store a machine learning model (described in detail below) included in the AI ​​system 30.

[0017] The terminal device 10 is, for example, an information processing device operated by a user. The user is, for example, a user of the estimation service. An example of the user of the estimation service is a person in charge of a mid-drying project.

[0018] A mid-drying project is a project that creates carbon credits by, for example, extending the mid-drying period of target paddy fields during the rice cultivation season by a specified number of days from the usual period and suppressing methane emissions from the soil. There are various types of mid-drying projects, including mid-drying projects under the "J-Credit Scheme" where credits are certified by the government, and any type of mid-drying project can be subject to System 1.

[0019] The person in charge of the mid-drying project, for example, will be in charge of managing and operating the mid-drying project, as well as managing the farmers who participate in the project. In addition, people with a variety of backgrounds, such as managers of agriculture-related companies, engineers or researchers with specialized agricultural knowledge, farmers, and experts in water management or environmental protection, can become the person in charge of the mid-drying project.

[0020] Users of the estimation service are not limited to those in charge of mid-drainage projects. Anyone who is involved in estimating the non-flooded period of the target paddy field can become a user of the estimation service.

[0021] The terminal device 10 is realized by, for example, a mobile terminal such as a smartphone or a tablet. In this embodiment, the terminal device 10 is a smartphone. The terminal device 10 may be realized by, for example, a stationary PC (Personal Computer), a laptop PC, or the like.

[0022] The terminal device 10 includes a communication IF (Interface) 12, an input device 13, an output device 14, a memory 15, a storage 16, and a processor 19. The input device 13 is a device for receiving an input operation from a user (for example, a touch panel, a touch pad, a pointing device such as a mouse, a keyboard, etc.). The output device 14 is a device for presenting information to a user (a display, a speaker, etc.). In this embodiment, the terminal device 10 includes a touch panel in which the input device 13 and the output device 14 are integrated.

[0023] The server 20 is, for example, an information processing device for managing and operating an inference service, and is an information processing device realized by a computer connected to a network 80. As shown in Fig. 1, the server 20 includes a communication IF 22, an input / output IF 23, a memory 25, a storage 26, and a processor 29. The input / output IF 23 functions as an interface for an input device for receiving an input operation from a manager / operator of the inference service, and an output device for outputting information to the manager / operator.

[0024] The AI ​​system 30 is a system including a trained machine learning model (hereinafter, abbreviated as "machine learning model"). The machine learning model is, for example, a decision tree algorithm or a neural network such as a convolutional neural network (CNN) or a recurrent neural network (RNN). In addition, for example, the machine learning model is a multimodal generative AI model.

[0025] The teacher data for the machine learning model included in the AI ​​system 30 is composed of, for example, the actual measurement value of the water level of the target section, a photograph of the target section, or the result of a person such as a user determining the water level of the target section, and an SAR image. The target section and the SAR image will be described in detail later.

[0026] The AI ​​system 30 may include, for example, one or more machine learning models. Furthermore, for example, when the AI ​​system 30 includes multiple machine learning models, the machine learning models may be of the same type, or may be of different types, such as one being a neural network and the other being a multimodal generative AI model.

[0027] The AI ​​system 30 receives the image cells and water level information transmitted from the server 20, inputs them into the machine learning model, and outputs a first index from the machine learning model. An image cell is a unit that constitutes a satellite image (hereinafter abbreviated as "satellite image") of a target paddy field. In this embodiment, an image cell is one pixel, but for example, an image cell may be composed of multiple pixels. The AI ​​system 30 transmits the first index output from the machine learning model to the server 20. The water level information and the first index will be described in detail later.

[0028] The artificial satellite 40 acquires satellite images as satellite data and transmits them to a ground station. In Fig. 1, an example in which the system 1 includes one artificial satellite 40 is shown, but for example, the system 1 may include two or more artificial satellites 40. When two or more artificial satellites 40 are included, the types of the artificial satellites 40 may be the same or different from each other.

[0029] In this embodiment, the artificial satellite 40 acquires an SAR image as a satellite image and transmits it to the server 20 via a ground station. The SAR image is a satellite image acquired by a synthetic aperture radar (SAR). That is, in this embodiment, the artificial satellite 40 is equipped with a SAR. The artificial satellite 40 acquires the SAR image by irradiating an object with microwaves (electromagnetic waves) from the SAR and receiving the reflected (backscattered) signal by the SAR.

[0030] SAR images are generated using microwaves (electromagnetic waves), so they are usable even in bad weather or at night. In addition, SAR images are generated based on synthetic aperture technology, so they have high resolution and are useful for obtaining detailed information about the ground and water surfaces.

[0031] The vibration characteristics of the microwaves (electromagnetic waves) irradiated from the SAR to the target object may be single-polarized, dual-polarized, or quadruple-polarized. In addition, the combination of the transmission polarization and the reception polarization can be set arbitrarily.

[0032] The server 20 acquires SAR images from a ground station in, for example, a Ground Range Detected (GRD) or Single Look Complex (SLC) file format. However, the server 20 may acquire SAR images from a ground station in, for example, a Polarimetric SAR (PolSAR) or Hierarchical Data Format version 5 (HDF5) file format.

[0033] The satellite images transmitted by the artificial satellite 40 to the server 20 via the ground station are not limited to SAR images. The artificial satellite 40 may transmit, for example, optical satellite images (visible light images, near-infrared images, etc.), spectral satellite images, or topographical satellite images (DEM: Digital Elevation Model), etc.

[0034] Each information processing device, such as the terminal device 10, the server 20, and the AI ​​system 30, is configured by a computer 90 (see FIG. 8) equipped with an arithmetic unit and a storage device. The basic hardware configuration of the computer 90 and the basic functional configuration of the computer 90 realized by the basic hardware configuration will be described later. Note that for each of the terminal device 10, the server 20, and the AI ​​system 30, descriptions that overlap with the basic hardware configuration of the computer 90 and the basic functional configuration of the computer will be omitted.

[0035] <2.1 Terminal device configuration> Fig. 2 is a block diagram showing an example of the configuration of the terminal device 10 shown in Fig. 1. As shown in Fig. 2, the terminal device 10 includes a communication unit 120, an input device 13, an output device 14, an audio processing unit 170, a microphone 171, a speaker 172, a camera 160, a position information sensor 150, an acceleration sensor 155, a storage unit 180, and a control unit 190. The blocks included in the terminal device 10 are electrically connected to each other, for example, by a bus or the like.

[0036] The communication unit 120 performs processes such as modulation and demodulation processes for communication between the terminal device 10 and an external device (for example, the server 20). The communication unit 120 performs transmission processes on signals generated by the control unit 190 and transmits the signals to the external device. The communication unit 120 performs reception processes on signals received from the external device and outputs the signals to the control unit 190.

[0037] The input device 13 is a device for a user to input instructions or information. The input device 13 is realized, for example, by a touch-sensitive device 131 in which an instruction is input by touching an operation surface. When the terminal device 10 is a PC or the like, the input device 13 may be realized by a reader, a keyboard, a mouse, or the like. The input device 13 converts an instruction input by a user into an electrical signal and outputs it to the control unit 190. The input device 13 may include, for example, a receiving port that receives an electrical signal input from an external input device.

[0038] The output device 14 is a device for presenting information to a user. The output device 14 is realized, for example, by a display 141. The display 141 displays various information according to the control of the control unit 190. The display 141 is realized, for example, by an LCD (Liquid Crystal Display) or an organic EL (Electro-Luminescence) display.

[0039] The audio processing unit 170 performs, for example, digital-analog conversion processing of an audio signal. The audio processing unit 170 converts a signal provided from the microphone 171 into a digital signal and provides the converted signal to the control unit 190. The audio processing unit 170 also provides the audio signal to the speaker 172. The audio processing unit 170 is realized, for example, by a processor for audio processing. The microphone 171 accepts audio input and provides an audio signal corresponding to the audio input to the audio processing unit 170. The speaker 172 converts the audio signal provided from the audio processing unit 170 into audio and outputs the audio to the outside of the terminal device 10.

[0040] Camera 160 is an imaging device that captures an image using visible light. In other words, camera 160 is a device that receives visible light with a light receiving element and outputs image data as an image capture signal. Camera 160 captures an image of a subject in a certain direction and within a certain image capture range relative to terminal device 10, and outputs image data as the image capture result. If camera 160 has a function that allows the image capture range, or more precisely, the angle of view, to be adjustable, camera 160 also outputs information regarding this angle of view. Such a function is known as a zoom function.

[0041] The position information sensor 150 is a sensor that detects the position of the terminal device 10, and is generally a GNSS device, for example, a GPS module. The GPS module is a receiving device used in a satellite positioning system. In the satellite positioning system, signals are received from at least three or four satellites, and the current position of the terminal device 10 equipped with the GPS module is detected as a coordinate value based on the received signals. The position information sensor 150 may detect the current position of the terminal device 10 from the position of a wireless base station to which the terminal device 10 is connected via the communication unit 120.

[0042] The acceleration sensor 155 is a sensor that detects the acceleration given to the terminal device 10. Preferably, the acceleration sensor 155 has a function of detecting the inclination about each axis (X-axis, Y-axis, Z-axis) of a three-dimensional coordinate system with the position of the terminal device 10 as the origin. The acceleration sensor 155 having such a function can detect the attitude of the terminal device 10, that is, the direction with respect to the X-axis, Y-axis, and Z-axis, by detecting the gravitational acceleration of the gravitational force with respect to the earth.

[0043] 1, and stores data and programs used by the terminal device 10. The programs include application programs such as a web browser application.

[0044] The control unit 190 is realized, for example, by the processor 19 reading a program stored in the storage unit 180 and executing instructions included in the program. The control unit 190 controls the operation of the terminal device 10. The control unit 190 performs the functions of an operation reception unit 191, a transmission / reception unit 192, and a presentation control unit 193 by operating according to the read program.

[0045] The operation reception unit 191 performs a process for receiving an instruction or information input from the input device 13. Specifically, the operation reception unit 191 receives an instruction or information input from the touch-sensitive device 131. The transmission / reception unit 192 performs a process for the terminal device 10 to transmit and receive data between the terminal device 10 and an external device in accordance with a communication protocol. Specifically, the transmission / reception unit 192 transmits an instruction or information input from a user to the server 20. The transmission / reception unit 192 receives information transmitted from the server 20. The presentation control unit 193 controls the output device 14 to present various information to the user.

[0046] <2.2 Server configuration> Fig. 3 is a block diagram showing an example of the configuration of the server 20 shown in Fig. 1. As shown in Fig. 3, the server 20 performs the functions of a communication unit 201, a storage unit 202, and a control unit 203.

[0047] The communication unit 201 performs processing for the server 20 to communicate with an external device (e.g., the terminal device 10). The storage unit 202 is realized by the memory 25 and the storage 26, and stores data and programs used by the server 20. The programs include application programs such as a web browser application. The storage unit 202 stores, for example, a polygon table 2021 and an app 2022.

[0048] The polygon table 2021 is a table that stores polygon information. The polygon information is information about the target paddy field, and includes at least address information. The polygon information will be described in detail later.

[0049] The address information is information indicating the address of the target paddy field. The address of the target paddy field indicated by the address information is, for example, an address declared by a user, and may not match the registered address registered in the registry. In addition, both the address of the target paddy field indicated by the address information and the registered address of the target paddy field registered in the registry may be the same for the target paddy field having multiple addresses, or the target paddy field and one or more paddies adjacent to the target paddy field may have the same address.

[0050] The application 2022 is an application for managing the use of the estimation service by the user. The application 2022 runs, for example, in the background of other applications installed in the server 20 and monitors the processing executed by the user. The user can access the application 2022 in the server 20 by using a web browser application installed in the terminal device 10.

[0051] The server 20 may, for example, grasp and manage the usage status of the application 2022 and execute a predetermined analysis process. In addition, for example, the application 2022 may be installed in the terminal device 10 and stored in the storage unit 180.

[0052] The control unit 203 is realized by the processor 29 reading a program stored in the storage unit 202 and executing instructions included in the program. The control unit 203 controls the operation of the server 20. The control unit 203 operates according to the read program to fulfill the functions of a reception control module 2031, a transmission control module 2032, a presentation control module 2033, and an estimation processing module 2034.

[0053] The reception control module 2031 controls the process in which the server 20 receives signals from an external device in accordance with a communication protocol. The reception control module 2031 receives, for example, address information transmitted from the terminal device 10. Also, for example, the reception control module 2031 receives SAR images and water level information transmitted from the artificial satellite 40 via a ground station each time a predetermined timing arrives within a predetermined period.

[0054] The water level information is information that indicates the water level of the target paddy field, and is a concept that includes water fall (water level is zero). In the water level information, the standard for high and low water levels (water level 0) is, for example, the ground surface. The water level information is measured continuously for a predetermined period of time, for example, by a water level gauge, water tube, or water level sensor (neither of which are shown) installed in the target paddy field.

[0055] The water level information may be temporarily stored in the terminal device 10 as a confirmation result of the display, for example, by a user who has confirmed the display of the water level gauge or water tube. Then, for example, the terminal device 10 that has accepted a transmission request from the server 20 may transmit the water level information to the server 20. Also, for example, the water level information may be transmitted to the server 20 via the terminal device 10 by a water level sensor that has accepted a transmission request from the server 20, or may be transmitted directly to the server 20.

[0056] The predetermined period is a period set for estimating the non-flooding period of the target paddy field, and may be any period long enough to allow estimation of the non-flooding period. In the present embodiment, as an example, the predetermined period is a period set for estimating the mid-drying period of the target paddy field. For example, if the user is to receive certification for credit application using the "J-Credit System", the predetermined period may be a period extended by 7 days or more from the average number of days of mid-drying implementation in the target paddy field over the past two or more years before the implementation of the mid-drying project (the mid-drying period required to receive certification). Hereinafter, the predetermined period is referred to as the "estimated implementation period".

[0057] The predetermined timing may be any timing as long as the server 20 can acquire the number of SAR images and water level information required to estimate the non-flooding period of the target paddy field during the estimation implementation period. In the present embodiment, as an example, the predetermined timing is a timing when the server 20 can acquire the number of SAR images and water level information required to estimate the mid-drying period of the target paddy field during the estimation implementation period. The predetermined timing may be, for example, a fixed cycle. In addition, the predetermined timing when the SAR images are acquired and the predetermined timing when the water level information is acquired are synchronized in principle, but they do not necessarily need to be synchronized. Hereinafter, the predetermined timing will be referred to as the "acquisition timing."

[0058] The estimated implementation period and the acquisition timing may be, for example, hard-coded in advance in the app 2022. In addition, for example, the server 20 may accept a setting operation for the estimated implementation period and the acquisition timing, and the estimated implementation period and the acquisition timing may be set by editing the program code of the app 2022.

[0059] The transmission control module 2032 controls the process in which the server 20 transmits a signal to an external device in accordance with a communication protocol. The presentation control module 2033 controls the process in which various information is presented to the user.

[0060] The estimation processing module 2034 calculates a first index for each of a plurality of image cells constituting the SAR image for each of a plurality of SAR images received by the reception control module 2031, based on the image cell and water level information. The first index is an index indicating the flooding state of the section corresponding to the image cell in the target paddy field. Hereinafter, the section corresponding to the image cell is referred to as the "target section."

[0061] In this embodiment, the first index is the probability of flooding of the target section. The probability of flooding is a ratio that indicates how much water is contained in the target section. For example, if the target section is flooded, the probability of flooding is "0". Note that an index other than the probability of flooding may be used as the first index. For example, the first index may be a discrete index in which a flooded state (regardless of the degree of flooding) is represented by "0" and a non-flooded state is represented by "1". The same applies to the second index described below.

[0062] For example, the estimation processing module 2034 may calculate the first index every time the reception control module 2031 receives a SAR image and water level information. Also, for example, the estimation processing module 2034 may calculate the first index all at once after the reception control module 2031 has once received all of the SAR images and water level information that it can receive during the estimation execution period.

[0063] In this embodiment, the estimation processing module 2034 inputs the image cell and the water level information to a machine learning model included in the AI ​​system 30, and causes the machine learning model to output a first index. When the machine learning model is a multimodal generative AI model, a prompt instructing the output of the first index is also input to the machine learning model. The prompt may be hard-coded in a program stored in the AI ​​system 30, for example. Also, for example, an input device (not shown) provided in the server 20 may accept an input operation of the prompt, and the server 20 may transmit the prompt to the AI ​​system 30. Alternatively, the prompt may be stored in advance in the storage unit 202 or the AI ​​system 30.

[0064] The estimation processing module 2034 may calculate the first index by, for example, rule-based processing instead of a machine learning model. Specifically, for example, the estimation processing module 2034 calculates the amount of water filled in the target paddy field by analyzing the SAR image and the water level information by a known analysis method, taking into account the variety of rice present in the target paddy field, the density of rice in the target paddy field, and the like. The estimation processing module 2034 may, for example, read out the maximum water retention amount (saturated water amount) of the target paddy field stored in advance in the storage unit 202 from the storage unit 202, and may divide the calculated value of the water amount by the maximum water retention amount to obtain a numerical value expressed as a percentage (%) as the first index (the flooding probability of the target paddy field). The maximum water retention amount of the target paddy field may be acquired by the server 20, for example, by the terminal device 10 transmitting an actual value measured in advance by a user to the server 20.

[0065] The estimation processing module 2034 calculates the calculated first index as a second index by taking a statistical value for each of the multiple SAR images received by the reception control module 2031 on a target paddy field basis. The second index is an index that indicates the flooded state of the target paddy field, and is the same type of index as the first index. In this embodiment, the second index is a statistical value obtained by taking a statistical value for the flooding probability of the target section on a target paddy field basis. There is no particular limitation on the type of statistical value, and it may be any of the average value, median value, and mode value.

[0066] The estimation processing module 2034 estimates a non-flooded period of the target paddy field during the estimation implementation period, based on a time-series change in the second index calculated for each of the multiple SAR images received by the reception control module 2031. In the present embodiment, as an example, the estimation processing module 2034 estimates a mid-drying period of the target paddy field during the estimation implementation period.

[0067] There are no particular limitations on the method of estimating the inter-drainage period of the target paddy field by the estimation processing module 2034. In this embodiment, the estimation processing module 2034, for example, sequentially compares all of the calculated second indexes with a reference value in the order of acquisition timing, and when there are a predetermined number of consecutive second indexes that are equal to or lower than the reference value, estimates the period in which these second indexes exist as the inter-drainage period. In this estimation process, the reference value and the predetermined number can be set arbitrarily depending on the characteristics of the target paddy field, the level of estimation accuracy required, etc.

[0068] In this embodiment, the estimation processing module 2034 performs pre-processing on the SAR image to calculate the first index. For example, as pre-processing for calculating the first index, the estimation processing module 2034 corrects the influence of the topography of the target paddy field for each of the multiple SAR images received by the reception control module 2031 (hereinafter, correction processing). Also, for example, as pre-processing for calculating the first index, the estimation processing module 2034 performs polarization decomposition on each of the multiple SAR images received by the reception control module 2031 and reflects the estimation result of the scattering characteristics of the target paddy field in the SAR image (hereinafter, polarization decomposition processing).

[0069] Specifically, for example, the estimation processing module 2034 performs correction processes on the SAR image, such as geometry correction, line of sight correction or altitude correction using a digital elevation model (DEM: Digital Elevation Model) of the target rice field, ambient correction, radiometric correction, or a combination of at least two or more of these.

[0070] Furthermore, for example, the estimation processing module 2034 performs polarization decomposition such as basis decomposition, Cloude-Pottier decomposition, Freeman-Durden decomposition, or integral transformation on the SAR image as a polarization decomposition process. As a result, the estimation processing module 2034 estimates the scattering characteristics of the target paddy field. Examples of the scattering characteristics include surface scattering, double reflection, and volume scattering. Surface scattering is scattering caused by a wide flat terrain such as a water surface, ground, or snow field. Double reflection is scattering caused by structures such as buildings and bridges. Volume scattering is scattering caused by objects in which scattering occurs multiple times, such as forests and farmland. Then, the estimation processing module 2034 reflects the estimation result of the scattering characteristics in the SAR image to generate a polarization decomposed image. The polarization decomposed image is a SAR image in which the estimation result of the scattering characteristics of the target paddy field by polarization decomposition is displayed. There is no particular limitation on the display mode of the estimation result in the polarization decomposed image. For example, a polarization-resolved image may be an SAR image in which objects present in a target rice field are displayed with different colors for objects with the same scattering characteristics.

[0071] In this embodiment, the estimation processing module 2034 performs both correction processing and polarimetric decomposition processing on the SAR image. Specifically, the estimation processing module 2034 first performs correction processing on each of the multiple SAR images received by the reception control module 2031 to reduce the influence of the topography of the target section on the SAR image. Next, the estimation processing module 2034 performs polarimetric decomposition processing on the SAR image after the correction processing to generate a polarimetric decomposition image. Then, the estimation processing module 2034 calculates a first index based on the generated polarimetric decomposition image and water level information.

[0072] As described above, by performing correction processing and polarimetry processing on the SAR image as preprocessing for calculating the first index, the accuracy of estimating the flooded state of the target plot indicated by the first index is improved. In turn, the accuracy of estimating the flooded state of the target paddy field indicated by the second index is improved, and the accuracy of estimating the non-flooded period is further improved.

[0073] It is not essential that the estimation processing module 2034 performs the above-mentioned two pre-processing processes on the SAR image. The estimation processing module 2034 may perform, for example, only one of the correction process or the polarimetric decomposition process on the SAR image. In addition, for example, the estimation processing module 2034 may directly input the SAR image received by the reception control module 2031 to the machine learning model without performing any pre-processing on the SAR image.

[0074] [3 Data Structure] Fig. 4 is a diagram showing the data structure of a table stored in the server 20. Note that Fig. 4 is merely an example, and does not exclude data that is not listed. In addition, even data that is listed in the same table may be stored in separate storage areas in the storage unit 202.

[0075] Fig. 4 is a diagram showing the data structure of the polygon table 2021. The polygon table 2021 shown in Fig. 4 is a table having columns of registered address information, project information, image information, water level information, and estimation results, with polygon IDs as keys.

[0076] The item "polygon ID" is an item that stores an identifier for uniquely identifying the target paddy field. The item "registered address information" is an item that stores registered address information. The details of registered address information will be described later. The item "project information" is an item that stores various information related to the mid-drainage project. Examples of various information related to the mid-drainage project include the project implementation body, participating bodies, purpose, summary of implementation content, and implementation period. The item "image information" is an item that stores various information related to the SAR image. There is no particular limitation on the content of the various information related to the SAR image. In this embodiment, the scattering characteristics displayed in the polarized resolved image are quantified and stored in the item "image information". Examples of the scattering characteristics quantified (hereinafter, "numerical values ​​indicating scattering characteristics") include the specular scattering coefficient, the volume scattering coefficient, and the threshold scattering coefficient. The item "water level information" is an item that stores water level information of the target paddy field. The item "estimation result" is an item for storing the result of estimation of the mid-drying period by the estimation processing module 2034 (estimated mid-drying period described later).

[0077] In this embodiment, the terminal device 10 that has accepted a transmission request from the user transmits the project information to the server 20, and the server 20 receives the project information, whereby the project information is stored in the item "project information." In this case, the project information may be stored in advance in the storage unit 180, or may be input to the input device 13 by a user's input operation. Note that the project information may be stored in the item "project information" by, for example, a facsimile machine on the manager / operator side receiving scanned data of a document (on which the project information is written) transmitted from a facsimile machine on the user side, and the server 20 accepting an input operation of the project information by the manager / operator.

[0078] In this embodiment, regarding various pieces of information related to the SAR image, the estimation processing module 2034 analyzes the polarization resolved image at each acquisition timing, calculates values ​​indicating scattering characteristics, and stores the values ​​in the item "image information."

[0079] In this embodiment, the water level information is stored in the item "water level information" when the terminal device 10, which has received a transmission request from the server 20 at each acquisition timing, transmits the water level information to the server 20 and the server 20 receives the water level information. In this case, all water level information during the estimation implementation period may be stored in advance in the storage unit 180, or may be input to the input device 13 by a user's input operation. Note that, for example, a water level sensor, which has received a transmission request from the server 20, may transmit water level information to the server 20 at each acquisition timing, and the server 20 may receive the water level information and store it in the item "water level information".

[0080] [4 actions] An example of the operation of the server 20 when estimating the mid-drying period will be described. Fig. 5 is a flowchart showing an example of the operation of the server 20 when estimating the mid-drying period. Note that the example of the operation of the server 20 shown in Fig. 5 is not limited to the estimation of the mid-drying period, but applies to the estimation of the non-flooding period in general.

[0081] In step S11 shown in FIG. 5, the server 20 acquires address information and identifies the target paddy field (identifying step).

[0082] Specifically, for example, the operation reception unit 191 receives a request from a user to transmit address information. The transmission / reception unit 192, for example, reads out the address information from the storage unit 180 and transmits it to the server 20. The reception control module 2031, for example, receives the address information transmitted from the terminal device 10. As a result, the server 20 acquires the address information.

[0083] The reception control module 2031, for example, compares the address information received from the terminal device 10 with the registered address information stored in a public database such as EMAFF (Ministry of Agriculture, Forestry and Fisheries Joint Application Service). The registered address information is information indicating the registered address of the paddy field registered in the registry. It is not essential to use a public database for this comparison process. Any database can be used for this comparison process as long as it stores the registered address information.

[0084] In this embodiment, before matching the address information with the registered address, the reception control module 2031 inputs the address information together with a prompt (an instruction sentence instructing to correct the spelling variation of the address of the target paddy field) to a generative AI model (not shown), and causes the generative AI model to output the address information with the spelling variation corrected. The generative AI model is, for example, an LLM (Large Language Model), and is stored together with the prompt in the storage unit 202 or the AI ​​system 30.

[0085] By correcting the spelling variations in this way, the server 20 can quickly and accurately identify the target paddy field. Note that the correction of spelling variations using a generative AI model is not essential.

[0086] The reception control module 2031, for example, identifies registered address information whose contents match the address information whose spelling variation has been corrected. The reception control module 2031, for example, identifies a paddy field corresponding to the identified registered address information as a target paddy field. The reception control module 2031, for example, stores the identified registered address information in the item "registered address information" of the polygon table 2021.

[0087] 5, the server 20 executes the process of step S11 and the process of step S12 consecutively, but this is not limited to the above. For example, the server 20 may execute the process of step S11 separately from the processes of step S12 and after. This is because, basically, the process of step S11 is executed before the estimated implementation period, and the processes of step S12 and after are executed after the start of the estimated implementation period.

[0088] In step S12, the server 20 acquires SAR images and water level information each time an acquisition timing arrives during the estimation implementation period (a step of acquiring satellite images and water level information).

[0089] Specifically, for example, the transmission control module 2032 transmits transmission request information indicating a transmission request for the SAR image to the ground station every time the acquisition timing arrives. The reception control module 2031 receives the SAR image from the ground station that accepted the transmission request every time the acquisition timing arrives. In this way, the server 20 acquires the SAR image every time the acquisition timing arrives.

[0090] The transmission control module 2032 transmits transmission request information indicating a request to transmit water level information to the terminal device 10, for example, each time the acquisition timing arrives. The reception control module 2031 receives water level information from the terminal device 10 that has accepted the transmission request, for example, each time the acquisition timing arrives. In this way, the server 20 acquires water level information each time the acquisition timing arrives.

[0091] 5, the server 20 executes the process of step S12 and the process of step S13 consecutively, but this is not limited to the above. For example, the server 20 may execute the process of step S12 separately from the processes of step S13 and subsequent steps. This is because, basically, the process of step S12 is executed during the estimated implementation period, and the processes of step S13 and subsequent steps are executed after the end of the estimated implementation period.

[0092] In step S13, the server 20 calculates a first index for each of a plurality of image cells constituting each of the acquired SAR images based on the image cell and water level information (step of calculating a first index).

[0093] Specifically, for example, before calculating the first index, the estimation processing module 2034 performs correction processing and polarimetric decomposition processing on each of the multiple SAR images received by the reception control module 2031 during the estimation execution period. That is, the estimation processing module 2034 first performs correction processing on the SAR image, and then performs polarimetric decomposition processing on the SAR image after the correction processing to generate a polarimetric decomposition image.

[0094] The estimation processing module 2034, for example, reads out all water level information during the estimation implementation period from the polygon table 2021. The estimation processing module 2034 transmits, for example, the generated multiple polarimetric resolved images and water level information acquired at the same time as each of the multiple polarimetric resolved images to the AI ​​system 30.

[0095] For example, for each of the multiple polarization-resolved images received from the server 20, the AI ​​system 30 inputs the image cell and the water level information received from the server 20 for each of the multiple image cells constituting the polarization-resolved image into a machine learning model. For example, for each of the multiple polarization-resolved images received from the server 20, the AI ​​system 30 causes the machine learning model to output a first index corresponding to each of the multiple image cells. For example, the AI ​​system 30 transmits all of the first indexes output from the machine learning model to the server 20.

[0096] The reception control module 2031 receives, for example, the first index transmitted from the AI ​​system 30. As a result, the server 20 calculates the first index for each of the multiple image cells constituting the SAR image for each of the multiple acquired SAR images.

[0097] In step S14, the server 20 calculates the statistical value of the calculated first index for each of the acquired multiple SAR images in units of the target paddy field, thereby calculating the statistical value as the second index (step of calculating the second index).

[0098] Specifically, for example, the estimation processing module 2034 calculates, as a second index, a statistical value of the first index corresponding to each of a plurality of image cells constituting the SAR image, for the first index received by the reception control module 2031. For example, the estimation processing module 2034 performs this calculation process for all SAR images acquired during the estimation execution period.

[0099] In step S15, the server 20 estimates the mid-drying period of the target paddy field in the estimation implementation period based on the time-series change in the second index calculated for each of the acquired multiple SAR images (estimating step).

[0100] Specifically, for example, the estimation processing module 2034 reads information indicating a reference value from the storage unit 202, and sequentially compares all calculated second indexes with the reference value according to the acquisition timing. The information indicating the reference value may be stored in the storage unit 202 in advance, for example, or may be stored in the storage unit 202 by receiving an input operation by the manager and inputting it to the server 20. In addition, for example, the reference value may be hard-coded in the app 2022. For example, when a predetermined number of second indexes that are equal to or less than the reference value are present consecutively, the estimation processing module 2034 estimates the period during which these second indexes exist as the mid-drying period. The predetermined number is hard-coded in the app 2022, for example.

[0101] In step S16, the server 20 presents the estimation result of the non-flooding period to at least one of the user and the manager. Specifically, for example, the presentation control module 2033 presents the mid-drying period estimated by the estimation processing module 2034 (hereinafter, the "estimated mid-drying period") to at least one of the user and the manager.

[0102] When presenting the estimated interim drying period to the user, the transmission control module 2032, for example, transmits information for displaying the estimated interim drying period to the terminal device 10. The transmitting / receiving unit 192, for example, receives information for displaying the estimated interim drying period from the server 20. For example, when receiving a presentation request from the user, the presentation control unit 193 causes the display 141 to display the estimated interim drying period.

[0103] When presenting the estimated mid-drying period to the management operator, the presentation control module 2033, for example, upon receiving a presentation request from the management operator, displays the estimated mid-drying period on a display (not shown) of an output device provided in the server 20.

[0104] In addition, when the output device of the output device 14 and the server 20 is a printer, the presentation control module 2033 may, for example, print out a paper medium on which the estimated interim drying period is printed from the output device of the output device 14 and the server 20. In addition, it is not essential that the presentation control module 2033 presents the estimated interim drying period to at least one of the user and the administrator.

[0105] [5 Summary] As described above, in this embodiment, the terminal device 10 accepts a request from a user to transmit address information and transmits the address information to the server 20. The reception control module 2031 collates the address information received from the terminal device 10 with registered address information stored in a public database, and identifies registered address information whose contents match the address information. The reception control module 2031 identifies the paddy field corresponding to the identified registered address information as the target paddy field.

[0106] Each time an acquisition timing arrives, the reception control module 2031 receives an SAR image from a ground station that has accepted a transmission request from the transmission control module 2032. Each time an acquisition timing arrives, the reception control module 2031 receives water level information from the terminal device 10 that has accepted a transmission request from the transmission control module 2032. Before calculating the first index, the estimation processing module 2034 first performs a correction process on each of the multiple SAR images received by the reception control module 2031 during the estimation implementation period, and performs a polarization decomposition process on the corrected SAR image to generate a polarization decomposed image.

[0107] The estimation processing module 2034 transmits, for example, the generated multiple polarization-resolved images and water level information acquired at the same time as each of the multiple polarization-resolved images to the AI ​​system 30. For each of the multiple polarization-resolved images received from the server 20, the AI ​​system 30 inputs the image cell and the water level information received from the server 20 to a machine learning model for each of the multiple image cells constituting the polarization-resolved image. The AI ​​system 30 causes the machine learning model to output first indices corresponding to each of the multiple image cells, and transmits them to the server 20.

[0108] The estimation processing module 2034 calculates a statistical value of the first indexes received by the reception control module 2031, corresponding to each of a plurality of image cells constituting the SAR image, as a second index. The estimation processing module 2034 sequentially compares all of the calculated second indexes with a reference value according to the acquisition timing. When a predetermined number of second indexes are consecutively equal to or less than the reference value, the estimation processing module 2034 estimates the period during which these second indexes exist as a mid-drying period.

[0109] This allows the server 20 to estimate the flooding condition of the entire target paddy field as the second index, using the first index that estimates the flooding condition of each target section that makes up the target paddy field. Therefore, the server 20 can estimate the flooding condition of the entire target paddy field by taking into account the finer characteristics of each area of ​​the target paddy field more than when the flooding condition of the entire target paddy field is directly estimated without using the first index. Therefore, the server 20 can improve the estimation accuracy of the non-flooded period.

[0110] [6. Modifications] In this embodiment, an example in which the server 20 presents the estimated mid-drying period is taken up as an example of using the estimated mid-drying period. However, the server 20 may adopt various other examples of use other than presenting the estimated mid-drying period. In other words, the system 1 may provide various other useful services in the estimation service other than presenting the estimated mid-drying period.

[0111] Hereinafter, an example of creating a document for applying for the issuance of carbon credits (hereinafter, "application document") will be described as an example of a utilization service that can be provided by the system 1. That is, the server 20 may create the application document based on, for example, an estimated mid-drying period.

[0112] First, the server 20 may acquire, for example, reporting information regarding the interim drainage period reported by the user (step of acquiring reporting information). The reporting information may include, for example, information for proving the interim drainage period reported by the user. Information for proving the interim drainage period reported by the user may be, for example, scanned data of a logbook (daily journal) in which the dates of flooding, drainage, etc. during the estimated implementation period are recorded. The logbook may be created, for example, by the farmer who owns the target paddy field. The user may, for example, receive a logbook from the farmer and store the reporting information obtained by scanning the logbook in the terminal device 10 in advance.

[0113] Specifically, for example, the operation reception unit 191 may receive a request to transmit declaration information from a user. The transmission / reception unit 192 may, for example, read out the declaration information from the storage unit 180 and transmit it to the server 20. The reception control module 2031 may, for example, receive the declaration information transmitted from the terminal device 10. As a result, the server 20 may acquire the declaration information.

[0114] In addition, the server 20 may acquire the declaration information, for example, by having a facsimile machine on the management operator's side receive scanned data of the logbook sent from a facsimile machine on the user's or farmer's side, and then accepting the input operation of the declaration information by the management operator.

[0115] The reception control module 2031 may, for example, store the received declaration information in the polygon table 2021. In this case, for example, the polygon table 2021 may be provided with an item "declaration information" for storing declaration information, and the reception control module 2031 may store the received declaration information in the item "declaration information." Also, for example, the reception control module 2031 may store the received declaration information in the item "project information."

[0116] Next, the server 20 may verify the degree of reliability of the declared information based on, for example, the acquired declared information and a time-series change in the second index (verification step).

[0117] Specifically, for example, the estimation processing module 2034 may compare each date of flooding, drainage, etc. included in the declaration information with the second index corresponding to each of the dates in chronological order. Alternatively, the estimation processing module 2034 may estimate a chronological change in the flooded state of the target paddy field from each date of flooding, drainage, etc. included in the declaration information, and compare this estimation result with a chronological change in the second index. For example, the estimation processing module 2034 may verify the degree of reliability of the declaration information based on the comparison result.

[0118] Specifically, for example, if the rate of agreement between the time-series change in the flooded state understood from the declared information and the time-series change in the second index is equal to or higher than a reference rate, the estimation processing module 2035 may determine that the reliability of the declared information is high. On the other hand, if the aforementioned rate is less than the reference rate, the estimation processing module 2035 may determine that the reliability of the declared information is low. The reference rate can be set arbitrarily depending on the characteristics of the target paddy field, the level of reliability required for the declared information, and the like.

[0119] When the estimation processing module 2034 determines that the reliability of the declaration information is high as a result of verifying the degree of reliability of the declaration information, the estimation processing module 2034 may determine to use the declaration information in the preparation of the declaration documents. On the other hand, when the estimation processing module 2034 determines that the reliability of the declaration information is low, the estimation processing module 2034 may, for example, display a verification result indicating that the reliability of the declaration information is low on a display of an output device provided in the server 20. In this case, for example, the management operator may inquire of the user or the like about the reliability of the declaration information by grasping the verification result displayed on the display. Then, the management operator may, for example, appropriately correct the declaration information in response to the user or the like's response to the inquiry, and input the corrected declaration information into an input device provided in the server 20. For example, the estimation processing module 2034 may determine to use the corrected declaration information in the preparation of the declaration documents by accepting the corrected declaration information.

[0120] Next, the server 20 may, for example, create application documents using the declaration information (creating step).

[0121] Specifically, for example, the estimation processing module 2034 may refer to the project information stored in the polygon table 2021 and read out the format of the application documents corresponding to the mid-drainage project from a format table (not shown). The format table may store, for example, a format for each type of mid-drainage project. The format table may be stored in the storage unit 202, for example.

[0122] The estimation processing module 2034 may, for example, input the declaration information into the corresponding items of the format read from the format table. The estimation processing module 2034 may, for example, input the corresponding information stored in the polygon table 2021 for the items other than the corresponding items in the format. In this manner, the estimation processing module 2034 may create the application documents.

[0123] The above-mentioned application document creation process is merely an example, and various other creation processes are envisioned. For example, the estimation processing module 2034 may input the declaration information together with the relevant information stored in the polygon table 2021 and a prompt (an instruction sentence instructing the creation of the application document) to the generative AI model, and output the application document from the generative AI model. The generative AI model may be, for example, an LLM, and may be stored in the storage unit 202 or the AI ​​system 30 together with the prompt.

[0124] Next, the server 20 may present the created application documents to the user. That is, the presentation control module 2033 may present the application documents created by the inference processing module 2034 to the user.

[0125] Specifically, for example, the transmission control module 2032 may transmit information for displaying the application documents to the terminal device 10. The transmitting / receiving unit 192 may receive information for displaying the application documents from the server 20, for example. The presentation control unit 193 may display the application documents on the display 141 when receiving a presentation request from a user, for example. In this way, the server 20 may present the application documents to the user.

[0126] The presentation control module 2033 may control the presentation control unit 193 to display the application documents on the display 141 in an editable state. In this case, for example, the operation reception unit 191 may receive an editing operation by a user, and the presentation control unit 193 may edit the application documents displayed on the display 141 to contents corresponding to the editing operation. For example, the presentation control module 2033 may present the application documents created by the estimation processing module 2034 to the administrator. For example, when the output device 14 is a printer, the presentation control module 2033 may print out the application documents from the output device 14. Furthermore, it is not essential that the presentation control module 2033 presents the application documents to the user. In this case, the administrator may mail the application documents printed out from the output device of the server 20 to the user.

[0127] In this way, according to this modification, the user only needs to provide the address information and the declaration information to the server 20, and the server 20 can automatically create the application documents. This improves the convenience for the user when using the estimation service.

[0128] Hereinafter, an example of a screen on the display 141 when application documents are presented to the user will be described with reference to Fig. 6 and Fig. 7. Fig. 6 is a schematic diagram showing an example of a screen on the display 141 when application documents are presented to the user. Fig. 7 is a schematic diagram showing another example of a screen on the display 141 when application documents are presented to the user.

[0129] In the screen example of FIG. 6, a registration application form 1411 is displayed on the display 141 as an application document. The registration application form 1411 has items such as application category, utilization of support funds, project information, applicant information, participation in a carbon neutral action plan, and review information. Corresponding information is displayed in the input field of each item. The presentation control module 2033 reads out the corresponding information from, for example, the polygon table 2021, and displays the corresponding information in the input field. Here, the corresponding information of each item of utilization of support funds, applicant information, participation in a carbon neutral action plan, and review information may be stored in, for example, the item "project information" of the polygon table 2021.

[0130] Also, for example, an edit button 1412 and a confirm button 1413 are displayed in a display area directly below the registration application form 1411 on the display 141. For example, when the operation acceptance unit 191 accepts a pressing operation of the edit button 1412, the corresponding information in the input field of each item becomes editable. Also, for example, when the operation acceptance unit 191 accepts a pressing operation of the confirm button 1413, the corresponding information in the input field of each item becomes confirmed. Then, even if the user presses the edit button 1412 after pressing the confirm button 1413, the corresponding information in the input field of each item remains in an uneditable state.

[0131] In the example screen of FIG. 7, a project plan 1414 is displayed on the display 141 as an application document. The project plan 1414 includes, for example, items such as project name, project implementer name, review information, project overview, reduction activity methodology, and data management. Corresponding information is displayed in the input field of each item. The presentation control module 2033 reads out the corresponding information from, for example, the polygon table 2021, and displays the corresponding information in the input field. Here, the corresponding information of each item such as project name, project implementer name, review information, project overview, reduction activity methodology, and data management may be stored in, for example, the item "project information" of the polygon table 2021.

[0132] Also, for example, an edit button 1415 and a confirm button 1416 are displayed in a display area directly below the project plan 1414 on the display 141. For example, the function of the edit button 1415 is the same as that of the edit button 1412, and the function of the confirm button 1416 is the same as that of the confirm button 1413.

[0133] The screen examples of Fig. 6 and Fig. 7 are merely examples, and various variations are assumed for the presented contents and the presented manner of the application documents. For example, the presentation control module 2033 may display only one of the registration application form 1411 or the project plan 1414 on the display 141. For example, the presentation control module 2033 may display application documents in a format in which the contents of the registration application form 1411 and the contents of the project plan 1414 are integrated into one on the display 141. For example, the presentation control module 2033 may add, delete, change, or the like each item of the registration application form 1411 and each item of the project plan 1414 and display them on the display 141. Furthermore, the presentation control module 2033 may display application documents in a format different from the registration application form 1411 and the project plan 1414 on the display 141.

[0134] The creation of application documents described in this modified example can also be applied when the system 1 provides an estimation service for non-flooding periods other than inter-drainage periods. In other words, the server 20 may create application documents based on the estimation results for the entire non-flooding period.

[0135] [7 Basic Computer Hardware Configuration] 8 is a block diagram showing the basic hardware configuration of a computer 90. The computer 90 includes at least a processor 901, a main storage device 902, an auxiliary storage device 903, and a communication IF 991 (interface). These are electrically connected to each other by a communication bus 921.

[0136] The processor 901 is hardware for executing an instruction set described in a program, and is composed of an arithmetic unit, a register, a peripheral circuit, and the like.

[0137] The main memory device 902 is for temporarily storing programs, data to be processed by the programs, etc. For example, it is a volatile memory such as a DRAM (Dynamic Random Access Memory).

[0138] The auxiliary storage device 903 is a storage device for saving data and programs, such as a flash memory, a hard disk drive (HDD), a magneto-optical disk, a CD-ROM, a DVD-ROM, or a semiconductor memory.

[0139] The communication IF 991 is an interface for inputting and outputting signals for communicating with other computers via a network using a wired or wireless communication standard.

[0140] The network is composed of the Internet, a LAN, various mobile communication systems constructed by wireless base stations, etc. For example, the network includes 3G, 4G, 5G mobile communication systems, LTE (Long Term Evolution), wireless networks that can connect to the Internet via a specified access point (e.g., Wi-Fi (registered trademark)), etc. In the case of wireless connection, communication protocols include, for example, Z-Wave (registered trademark), ZigBee (registered trademark), Bluetooth (registered trademark), etc. In the case of wired connection, the network also includes a network that is directly connected by a USB (Universal Serial Bus) cable or the like.

[0141] It should be noted that the computer 90 can be virtually realized by distributing all or part of each hardware configuration among multiple computers 90 and connecting them together via a network. In this way, the computer 90 is a concept that includes not only a computer 90 housed in a single housing or case, but also a virtualized computer system.

[0142] [8 Basic Functional Configuration of Computer 90] A description will now be given of the functional configuration of a computer realized by the basic hardware configuration (FIG. 8) of a computer 90. The computer comprises at least the functional units of a control unit, a storage unit, and a communication unit.

[0143] The functional units of the computer 90 can also be realized by distributing all or part of the functional units among multiple computers 90 connected to each other via a network. The computer 90 is a concept that includes not only a single computer 90 but also a virtualized computer system.

[0144] The control unit is realized by the processor 901 reading out various programs stored in the auxiliary storage device 903, expanding the programs in the main storage device 902, and executing processes according to the programs. The control unit can realize functional units that perform various information processing depending on the type of program. In this way, the computer is realized as an information processing device that performs information processing.

[0145] The storage unit is realized by a main storage device 902 and an auxiliary storage device 903. The storage unit stores data, various programs, and various databases. Furthermore, the processor 901 can secure a storage area corresponding to the storage unit in the main storage device 902 or the auxiliary storage device 903 in accordance with a program. Furthermore, the control unit can cause the processor 901 to execute processes of adding, updating, and deleting data stored in the storage unit in accordance with the various programs.

[0146] The term database refers to a relational database, which is used to manage sets of data called masters and tables in a tabular format structurally defined by rows and columns, by associating them with each other. In a database, a table is called a table or master, a column in a table is called a column, and a row in a table is called a record. In a relational database, relationships between tables and masters can be set and associated.

[0147] Usually, a column that serves as a primary key for uniquely identifying a record is set in each table and each master, but setting a primary key in a column is not essential. The control unit can cause the processor 901 to add, delete, or update records in a specific table or master stored in the storage unit according to various programs.

[0148] Furthermore, by storing data, various programs, and various databases in the storage unit, it can be considered that the information processing device and information processing system according to the present disclosure have been manufactured.

[0149] In addition, the database and master in this disclosure may include any data structure (such as a list, a dictionary, an associative array, or an object) in which information is structurally defined. The data structure also includes data that can be considered as a data structure by combining data with a function, class, method, or the like written in any programming language.

[0150] The communication unit is realized by the communication IF 991. The communication unit realizes a function of communicating with other computers 90 via a network. The communication unit can receive information transmitted from other computers 90 and input the information to the control unit. The control unit can cause the processor 901 to execute information processing on the received information in accordance with various programs. In addition, the communication unit can transmit information output from the control unit to other computers 90.

[0151] In addition, the above-mentioned configurations, functions, processing units, processing means, etc. may be realized in part or in whole by hardware, for example, by designing them as integrated circuits. The present invention can also be realized by software program code that realizes the functions of the embodiments. In this case, a storage medium on which the program code is recorded is provided to a computer, and a processor included in the computer reads the program code stored in the storage medium. In this case, the program code itself read from the storage medium realizes the functions of the above-mentioned embodiments, and the program code itself and the storage medium storing it constitute the present invention. Examples of storage media for supplying such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, SSDs, optical disks, magneto-optical disks, CD-Rs, magnetic tapes, non-volatile memory cards, ROMs, etc.

[0152] In addition, the program code for realizing the functions described in this embodiment can be implemented in a wide range of program or script languages, such as assembler, C / C++, perl, Shell, PHP, Java (registered trademark), JavaScript, and TypeScript.

[0153] Furthermore, the program code of software that realizes the functions of the embodiments may be distributed over a network and stored in a storage means such as a computer's hard disk or memory, or in a storage medium such as a CD-RW or CD-R, and the processor of the computer may read out and execute the program code stored in the storage means or storage medium.

[0154] The functions performed by the components described herein may be implemented in circuitry or processing circuitry, including general purpose processors, application specific processors, integrated circuits, ASICs (Application Specific Integrated Circuits), CPUs (Central Processing Units), conventional circuits, and / or combinations thereof, programmed to perform the functions described. Processors include transistors and other circuits and are considered to be circuitry or processing circuitry. A processor may be a programmed processor that executes a program stored in a memory.

[0155] In this specification, a circuitry, unit, or means is hardware that is programmed to realize or performs the described functions, which may be any hardware disclosed in this specification or any hardware known to be programmed to realize or perform the described functions.

[0156] If the hardware is a processor considered to be a type of circuitry, the circuitry, means, or unit is a combination of the hardware and software used to configure the hardware and / or processor.

[0157] Although several embodiments of the present disclosure have been described above, these embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and modifications are within the scope of the invention and its equivalents as described in the claims, as well as the scope and spirit of the invention.

[0158] [9 Notes] The matters described in the above embodiments will be supplemented below.

[0159] <Appendix 1> A program to be executed by a computer having a processor and a memory, the program causing the processor to execute the following steps: acquiring address information indicating the address of the paddy field and identifying a target paddy field to be estimated; acquiring satellite images of the target paddy field and water level information indicating the water level of the target paddy field each time a specified timing occurs within a specified period; calculating, for each of the multiple acquired satellite images, a first index indicating the flooded state of a section in the target paddy field corresponding to the image cell constituting the satellite image based on the image cell and the water level information; taking a statistical value of the calculated first index on a target paddy field unit basis for each of the multiple acquired satellite images, and calculating the statistical value as a second index indicating the flooded state of the target paddy field; and estimating the non-flooded period of the target paddy field during a specified period based on the chronological change in the second index calculated for each of the multiple acquired satellite images.

[0160] <Appendix 2> The satellite image is a SAR image.

[0161] <Appendix 3> The program described in Appendix 2 further causes the processor to execute a step of correcting the influence of the topography of the target rice field for each of the multiple acquired SAR images as a preprocessing step for calculating the first index.

[0162] <Appendix 4> The program described in (Appendix 2) or (Appendix 3) further causes the processor to execute a step of subjecting each of the acquired multiple SAR images to polarization decomposition and reflecting the estimated results of the scattering characteristics of the target rice field in the SAR images as a preprocessing step for calculating the first index.

[0163] <Appendix 5> In the step of calculating the first index, the image cells and water level information are input into a trained machine learning model, and the first index is output from the machine learning model.A program described in any one of (Appendix 1) to (Appendix 4).

[0164] <Appendix 6> A program described in any one of (Appendix 1) to (Appendix 5), further causing the processor to execute a step of preparing documents for applying for issuance of carbon credits based on the estimated results of the non-flooded period.

[0165] <Appendix 7> The non-flooding period is a mid-drying period, and the creation step includes a step of acquiring declared information regarding the mid-drying period declared by the user, and a step of verifying the degree of reliability of the declared information based on the acquired declared information and the time-series changes in the second index (a program described in Appendix 6).

[0166] <Appendix 8> An information processing device comprising a control unit and a storage unit, the control unit executing all steps in the program according to any one of (Supplementary Note 1) to (Supplementary Note 7).

[0167] <Appendix 9> A method executed by a computer having a processor and a memory, wherein the processor executes all the steps of a program described in any one of (Appendix 1) to (Appendix 7).

[0168] <Appendix 10> A system comprising means for executing all steps in the program described in any one of (Appendix 1) to (Appendix 7). [Explanation of symbols]

[0169] 1. System 10...Terminal device 120…Communications Department 13...Input device 14...Output device 15…Memory 16…Storage 19…Processor 20…Server 22…Communication IF 23... Input / Output IF 25…Memory 26…Storage 29…Processor 30…AI system 40...Artificial satellite

Claims

1. A program to be executed by a computer having a processor and a memory, The program causes the processor to: A step of acquiring address information indicating an address of a paddy field and identifying a target paddy field to be estimated; acquiring a satellite image of the target paddy field and water level information indicating a water level of the target paddy field at a predetermined timing within a predetermined period; calculating, for each of the acquired plurality of satellite images, a first index indicating a flooded state of a section in the target paddy field corresponding to the image cell for each of a plurality of image cells constituting the satellite image, based on the image cell and the water level information; A step of calculating a statistical value of the calculated first index for each of the plurality of acquired satellite images in units of the target paddy field as a second index indicating the flooded state of the target paddy field; estimating a non-flooded period of the target paddy field during the predetermined period based on a time-series change in the second index calculated for each of the acquired multiple satellite images; A program that executes the following.

2. The program according to claim 1 , wherein the satellite image is a SAR image.

3. The program according to claim 2 , further causing the processor to execute a step of correcting the influence of the topography of the target paddy field for each of the acquired multiple SAR images as a preprocessing step for calculating the first index.

4. The program according to claim 2, further causing the processor to execute a step of subjecting each of the acquired multiple SAR images to polarization decomposition as a preprocessing step for calculating the first index, and reflecting the estimated results of the scattering characteristics of the target paddy field in the SAR image.

5. The program according to claim 1 , wherein in the step of calculating the first index, the image cell and the water level information are input into a trained machine learning model, and the first index is output from the machine learning model.

6. The program according to claim 1 , further causing the processor to execute a step of preparing documents for applying for issuance of carbon credits based on the estimation result of the non-waterlogged period.

7. The non-flooded period is a mid-drying period, The creating step includes: A step of acquiring declared information regarding the mid-drying period declared by a user; verifying the degree of reliability of the declared information based on the acquired declared information and a time-series change of the second indicator; The program according to claim 6 .

8. 8. An information processing apparatus comprising: a control unit; and a storage unit, the control unit executing all steps of the program according to claim 1.

9. A method implemented on a computer having a processor and a memory, the processor executing all the steps of a program according to any one of claims 1 to 7.

10. A system comprising means for executing all the steps of the program according to any one of claims 1 to 7.

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