Programs, information processing devices, methods, and systems

Abstract

To accurately assess the reliability of forest credit quantities. [Solution] This is a program to be executed by a computer equipped with a processor and memory. The program causes the processor to perform the following steps: acquire first image data of a first forest area and second image data of a second forest area; calculate a first vegetation index of the first forest area based on the first image data and calculate a second vegetation index of the second forest area based on the second image data; select a second location within the second forest area where the trend of the second vegetation index approximates the trend of the first vegetation index at the first location; acquire third image data relating to the first forest area and calculate a third vegetation index at the first location and acquire fourth image data relating to the second forest area and calculate a fourth vegetation index at the second location; and evaluate the reliability of the amount of forest credit based on the third and fourth vegetation indices.

Description

[Technical Field]

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

[0002] In recent years, as part of activities to promote the reduction of greenhouse gas emissions, research and development of technologies related to forest credits has been active. For example, Patent Document 1 discloses a technology that analyzes image data of an inspection area to determine whether the inspection area is a forest area and also determine whether the inspection area is a thinning area. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent No. 7521096 [Summary of the Invention] [Problems to be Solved by the Invention]

[0004] However, Patent Document 1 does not make any mention of the setting and verification of a baseline that serves as a calculation standard for the amount of forest credits. Therefore, the technology disclosed in Patent Document 1 has room for improvement in terms of accurately evaluating the reliability of the amount of forest credits.

[0005] An object of the present disclosure is to evaluate the reliability of the amount of forest credits with high accuracy. [Means for Solving the Problems]

[0006] To solve the aforementioned problems, a program according to one aspect of this disclosure is a program to be executed by a computer having a processor and memory. The program includes the steps of: obtaining first image data of a first forest area that is the target of forest credit creation and second image data of a second forest area located around the first forest area for a predetermined period in the past; selecting an arbitrary point within the first forest area as the first point; calculating a first vegetation index in the first forest area for a predetermined period in the past based on the first image data for a predetermined period in the past, and calculating a second vegetation index in the second forest area for a predetermined period in the past based on the second image data for a predetermined period in the past; and during the predetermined period in the past The system performs the following steps: selecting a specific location within the second forest area as the second location where the trend of the second vegetation index approximates the trend of the first vegetation index over a predetermined period in the past at the first location; calculating the third vegetation index for the first location each time third image data related to the first forest area is periodically acquired, and calculating the fourth vegetation index for the second location each time fourth image data related to the second forest area is periodically acquired, starting from the start of forest credit creation; and evaluating the reliability of the amount of forest credit created based on the periodically calculated third and fourth vegetation indices. [Effects of the Invention]

[0007] According to this disclosure, the reliability of the amount of forest credit can be assessed with high accuracy. [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing an example of the overall configuration of System 1. [Figure 2] This block diagram shows an example configuration of the terminal device 10 shown in Figure 1. [Figure 3] Figure 1 is a block diagram showing an example configuration of server 20. [Figure 4] Figure 3 shows the data structure of the Forest Database 2021. [Figure 5]This flowchart shows an example of how server 20 operates when evaluating the reliability of forest credit amounts. [Figure 6] This is a schematic diagram showing an example of the display 141 screen when the user is presented with the first to fourth transitions. [Figure 7] A block diagram showing the basic hardware configuration of Computer 90. [Modes for carrying out the invention]

[0009] The embodiments of this disclosure will be described below with reference to the drawings. In all the drawings illustrating the embodiments, common components are denoted by the same reference numerals, and repeated explanations are omitted. The following embodiments are not intended to unduly limit the content of this disclosure as described in the claims. Not all components shown in the embodiments are necessarily essential components of this disclosure. Also, each drawing is a schematic diagram and is not necessarily a strict illustration.

[0010] [1. Overview] The system according to this embodiment acquires first image data relating to the first forest area, which is the target of forest credit creation, and second image data relating to the second forest area, for a predetermined period in the past. The system according to this embodiment selects an arbitrary point within the first forest area as the first point. Based on the first image data acquired for the predetermined period in the past, the system according to this embodiment calculates the first vegetation index for the predetermined period in the first forest area. Based on the second image data acquired for the predetermined period in the past, the system according to this embodiment calculates the second vegetation index for the predetermined period in the second forest area. The system according to this embodiment selects a specific point within the second forest area as the second point, where the trend of the second vegetation index during the predetermined period in the past approximates the trend of the first vegetation index during the predetermined period in the past at the first point. From the start of forest credit creation, the system according to this embodiment calculates the third vegetation index at the first point each time third image data relating to the first forest area is acquired periodically. From the start of forest credit creation, the system according to this embodiment calculates the fourth vegetation index at the second point each time fourth image data relating to the second forest area is acquired periodically. The system according to this embodiment evaluates the reliability of the amount of forest credit created based on a third vegetation index and a fourth vegetation index calculated periodically.

[0011] [2. Overall System Configuration] Figure 1 is a block diagram showing an example of the overall configuration of System 1. System 1 is a system for providing a service (hereinafter referred to as the evaluation service) that evaluates the reliability of the amount of forest credit in the first forest area.

[0012] The first forest area is the forest area that is eligible for the creation of forest credits. When a user applies to use the evaluation service, they specify the first forest area and apply to the evaluation service administrator. Users are, for example, the person in charge of a project aimed at creating forest credits (hereinafter referred to as a forest project), the owner of the first forest area, etc.

[0013] Those in charge of forest projects, for example, are responsible for the management and operation of the project, as well as managing the owners of the forest areas participating in the project. Furthermore, individuals with diverse backgrounds can become forest project managers, including managers of forestry-related companies, engineers or researchers with specialized forestry knowledge, and environmental protection specialists.

[0014] The amount of forest credits is the amount of greenhouse gas reduction certified as forest credits. The certification body for forest credits subject to System 1 may be a public institution such as a national or local government, or a private certification body. Hereinafter, the amount of forest credits will be referred to as "amount of forest credits."

[0015] In this specification, the reliability of forest credit amounts is defined as "the amount of forest credits being genuinely generated by greenhouse gas emission reduction activities (e.g., the aforementioned forest projects), and that such reduction activities are actually verifiable and sustainable."

[0016] Furthermore, this specification considers additionality and conservative and realistic baseline setting as reliability evaluation factors. Additionality refers, for example, to the fact that the revenue from forest credits obtained from greenhouse gas emission reduction activities makes those reduction activities feasible. Conservative and realistic baseline setting means, for example, when setting the trend (baseline) of greenhouse gas reduction amounts that serves as the basis for evaluating the amount of forest credits, setting a value that avoids overestimating reduction amounts and allows for a realistic and careful evaluation.

[0017] Note that, in addition to the two evaluation factors described above, for example, at least one of durability and disclosure of information on credit activities may be used as an evaluation factor for reliability. Durability refers to, for example, the ability of a greenhouse gas emission reduction activity to maintain the greenhouse gas reduction effect over a long period of time. Specifically, for example, if the reduction effect is stably maintained even after the end of the reduction activity, and the greenhouse gas reduction is not canceled over time (e.g., forests are logged, destroyed by fire or disease), the durability is evaluated as high. Disclosure of information on credit activities refers to the comprehensive and transparent disclosure of various information related to greenhouse gas emission reduction activities, and also includes the disclosure of information on activity results. Specifically, for example, it is required to comprehensively and transparently disclose information on activity content, calculation methods for greenhouse gas emissions, methods and results of monitoring after activity initiation, results of verification of reduction activities by third-party organizations, as well as risks and uncertain factors such as natural disasters and illegal logging.

[0018] In the present embodiment, the carbon dioxide absorption amount certified as forest credits is regarded as the forest credit amount. Also, in the present embodiment, the greenhouse gas emission reduction activity is an activity (including afforestation activities) that protects and manages a predetermined forest area for the purpose of promoting carbon dioxide absorption by forests. In other words, in the present embodiment, the greenhouse gas emission reduction activity is a forest project. Note that the forest credit certification target evaluated by the system 1 may be greenhouse gases other than carbon dioxide. Examples of greenhouse gases that are subject to forest credit certification other than carbon dioxide include methane, nitrous oxide, and black carbon.

[0019] The system 1 shown in Figure 1 includes, for example, a terminal device 10, a server 20, and an artificial satellite 30. The terminal device 10 and the server 20 are communicatively connected via, for example, a network 80. The artificial satellite 30 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, accepts a transmission request from the server 20 and transmits the satellite data to the server 20 via the network 80.

[0020] Although FIG. 1 shows an example in which system 1 includes one terminal device 10, system 1 may include two or more terminal devices 10, for example. Although FIG. 1 shows an example in which system 1 includes one server 20, an aggregate of a plurality of devices may be used as one server 20, for example. The method of allocating the plurality of functions required to implement the server 20 to one or more pieces of hardware can be appropriately determined according to the processing capacity of each piece of hardware and / or the specifications required for the server 20, etc.

[0021] The terminal device 10 is, for example, an information processing device operated by a user. The terminal device 10 is implemented by, for example, a mobile terminal such as a smartphone or a tablet. In the present embodiment, it is assumed that the terminal device 10 is a smartphone. The terminal device 10 may be implemented 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 accepting input operations 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 the present embodiment, it is assumed that 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 evaluation service, and is an information processing device implemented 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 accepting input operations from an administrator / operator and an output device for outputting information to the administrator / operator.

[0024] The artificial satellite 30 acquires, for example, a first satellite image, a second satellite image, a third satellite image, and a fourth satellite image as satellite data and transmits them to a ground station. The first satellite image is an example of first image data relating to one aspect of this disclosure. The second satellite image is an example of second image data relating to one aspect of this disclosure. The third satellite image is an example of third image data relating to one aspect of this disclosure. The fourth satellite image is an example of fourth image data relating to one aspect of this disclosure.

[0025] The first satellite image is a satellite image of the first forest area before the creation of forest credits. In this embodiment, "before the creation of forest credits" refers to any period prior to the start of the forest project. The second satellite image is a satellite image of the second forest area before the creation of forest credits. The second forest area is the forest area surrounding the first forest area. The second forest area is also a forest area used to define a counterfactual area (hereinafter referred to as the counterfactual area) that shows approximately the same vegetation index progression as the first forest area if the forest project were not implemented. The "forest area surrounding the first forest area" is not a concept that refers only to the forest area adjacent to the first forest area, but also includes, for example, the forest area encompassed within a radius of 100 km centered on the first point within the first forest area. Of course, "radius of 100 km" is merely an example and may change as appropriate depending on the area of ​​the first forest area, etc. Details of the vegetation index and the first point will be described later.

[0026] The third satellite image is a satellite image of the first forest area, taken after the start of forest credit creation. In this embodiment, "start of forest credit creation" refers to the start of the forest project. The fourth satellite image is a satellite image of the second forest area, taken after the start of forest credit creation.

[0027] Figure 1 shows an example where System 1 includes one satellite 30, but System 1 may include two or more satellites 30. If it includes two or more satellites, the types of satellites 30 may be the same or they may be different.

[0028] In this embodiment, the satellite 30 acquires SAR images or optical satellite images (visible light images, near-infrared images, etc.) as the first to fourth satellite images and transmits them to the server 20 via a ground station. SAR images are satellite images acquired by SAR (Synthetic Aperture Radar). In other words, in this embodiment, the satellite 30 is equipped with SAR. The satellite 30 acquires SAR images by irradiating an object with microwaves (electromagnetic waves) from the SAR and receiving the reflected (backscattered) signals.

[0029] Because SAR images are generated using microwaves (electromagnetic waves), they are perfectly usable even if generated in bad weather or at night. Furthermore, because SAR images are generated based on synthetic aperture technology, they are high-resolution and useful for obtaining detailed information about the Earth's surface and water surface.

[0030] The vibration characteristics of the microwaves (electromagnetic waves) irradiated onto the target object by the SAR may be single-polarization, dual-polarization, or quadruple-polarization. Furthermore, the combination of transmitting and receiving polarizations can be arbitrarily set.

[0031] Server 20 acquires SAR images from a ground station in the file format GRD (Ground Range Detected) or SLC (Single Look Complex), for example. However, Server 20 may also acquire SAR images from a ground station in the file format Polarimetric SAR (PolSAR) or HDF5 (Hierarchical Data Format version 5), for example.

[0032] The first to fourth satellite images transmitted by the satellite 30 to the server 20 via a ground station are not limited to SAR images or optical satellite images. The satellite 30 may transmit, for example, spectral satellite images or topographic satellite images (DEM: Digital Elevation Model). Alternatively, instead of the first to fourth satellite images, aerial images of the first forest area and aerial images of the second forest area, taken by a drone or helicopter capable of aerial photography, may be transmitted to the server 20. In this case, the aforementioned drone or helicopter would constitute System 1 in place of the satellite 30. In this case, the aerial images of the first forest area would be an example of the first and third image data according to one aspect of this disclosure, and the aerial images of the second forest area would be an example of the second and fourth image data according to one aspect of this disclosure.

[0033] Each information processing device, such as the terminal device 10 and the server 20, is composed of a computer 90 (see Figure 7) equipped with an arithmetic unit and a memory device. The basic hardware configuration of the computer 90 and the basic functional configuration of the computer 90 realized by this basic hardware configuration will be described later. Note that explanations of the terminal device 10 and the server 20 that overlap with the basic hardware configuration of the computer 90 and the basic functional configuration of the computer will be omitted.

[0034] <2-1 Configuration of the terminal device> Figure 2 is a block diagram showing an example configuration of the terminal device 10 shown in Figure 1. As shown in Figure 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. Each block included in the terminal device 10 is electrically connected, for example, by a bus.

[0035] The communication unit 120 performs processing such as modulation and demodulation processing for the terminal device 10 to communicate with an external device (for example, a server 20). The communication unit 120 performs transmission processing on the signal generated by the control unit 190 and transmits it to the external device. The communication unit 120 performs reception processing on the signal received from the external device and outputs it to the control unit 190.

[0036] The input device 13 is a device for the user to input instructions or information. The input device 13 can be implemented, for example, by a touch-sensitive device 131 on which instructions are input by touching the operating surface. If the terminal device 10 is a PC or the like, the input device 13 may be implemented by a reader, keyboard, mouse, etc. The input device 13 converts the instructions input by the user into electrical signals and outputs them to the control unit 190. The input device 13 may also include, for example, a receiving port that accepts electrical signals input from an external input device.

[0037] The output device 14 is a device for presenting information to the user. The output device 14 is implemented, 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 implemented, for example, by an LCD (Liquid Crystal Display) or an organic EL (Electro-Luminescence) display.

[0038] The audio processing unit 170 performs, for example, digital-to-analog conversion processing of the audio signal. The audio processing unit 170 converts the 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 implemented, for example, by an audio processing processor. The microphone 171 receives an audio input and provides the audio signal corresponding to that 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.

[0039] Camera 160 is an imaging device that captures images using visible light. In other words, camera 160 is a device that receives visible light using a photodetector and outputs image data as a shooting signal. Camera 160 captures subjects in a certain direction and within a certain shooting range relative to the terminal device 10 and outputs image data as a result of the capture. If camera 160 has a function that allows adjustment of the shooting range, or more precisely, the angle of view, camera 160 also outputs information regarding this angle of view. Such a function is called a zoom function.

[0040] The location information sensor 150 is a sensor that detects the position of the terminal device 10, and is generally a GNSS device, such as a GPS module. A GPS module is a receiving device used in a satellite positioning system. In a satellite positioning system, signals are received from at least three or four satellites, and based on the received signals, the current position of the terminal device 10, which is equipped with a GPS module, is detected in coordinate values. The location information sensor 150 may also 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.

[0041] The acceleration sensor 155 is a sensor that detects the acceleration applied to the terminal device 10. Preferably, the acceleration sensor 155 has the function of detecting the tilt around 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. An acceleration sensor 155 having such a function can detect the orientation of the terminal device 10, that is, its direction with respect to the X, Y, and Z axes, by detecting the gravitational acceleration of the Earth's gravity.

[0042] The storage unit 180 is implemented by the memory 15 and storage 16 shown in Figure 1, and stores data and programs used by the terminal device 10. The programs include application programs such as web browser applications.

[0043] The control unit 190 is implemented, for example, by the processor 19 reading a program stored in the memory unit 180 and executing the instructions contained in the program. The control unit 190 controls the operation of the terminal device 10. By operating according to the loaded program, the control unit 190 performs the functions of an operation reception unit 191, a transmission / reception unit 192, and a presentation control unit 193.

[0044] The operation reception unit 191 processes instructions or information input from the input device 13. Specifically, the operation reception unit 191 receives instructions or information input from the touch-sensitive device 131. The transmission / reception unit 192 processes data for the terminal device 10 to send and receive data with an external device according to a communication protocol. Specifically, the transmission / reception unit 192 sends instructions or information input from the user to the server 20. The transmission / reception unit 192 receives information sent from the server 20. The presentation control unit 193 controls the output device 14 to present various information to the user.

[0045] <2-2 Server Configuration> Figure 3 is a block diagram showing an example configuration of the server 20 shown in Figure 1. As shown in Figure 3, the server 20 performs the functions of a communication unit 201, a storage unit 202, and a control unit 203.

[0046] The communication unit 201 performs processing for the server 20 to communicate with an external device (e.g., terminal device 10). The storage unit 202 is implemented by memory 25 and storage 26 and stores data and programs used by the server 20. The programs include application programs such as web browser applications. The storage unit 202 stores, for example, a forest database 2021 and an application 2022.

[0047] The Forest Database 2021 is a table that stores the first, second, third, and fourth satellite images, as well as the first and second filtering information, etc. Details of the Forest Database 2021 will be described later.

[0048] The first filtering information is information that indicates the conditions for extracting areas suitable for generating forest credits from the first forest area. Examples of the first filtering information include whether or not the area is of the same type as the forest area targeted for generating forest credits, and whether or not it falls under an administrative area designated by the national or local government. "Same type of forest area" includes forest areas of the same type in a broad sense, such as tropical forests, temperate forests, mangroves, or alpine forests, as well as forest areas with the same tree species. Whether or not an area falls under an administrative area is determined according to the content of the forest credits, etc.

[0049] The second filtering information is information that indicates the conditions for extracting areas suitable for baseline setting from the second forest area. Examples of the second filtering information include whether or not it is the same type of forest category as the forest category for which forest credits are to be generated, whether or not it falls under an administrative category designated by the national or local government, and whether or not it is within a predetermined distance from the first forest area (e.g., within a radius of 100 km). In this embodiment, the second filtering information is treated as different information from the first filtering information, but the second filtering information may be completely identical to the first filtering information.

[0050] App 2022 is an application for managing user usage of the evaluation service. App 2022 runs in the background of other applications installed on server 20, for example, and monitors processes performed by users. Users can access App 2022 on server 20 using a web browser application installed on terminal device 10.

[0051] The server 20 may, for example, monitor and manage the usage status of application 2022 and perform predetermined analysis processing. Alternatively, application 2022 may be installed on the terminal device 10 and stored in the storage unit 180.

[0052] The control unit 203 is realized when the processor 29 reads a program stored in the memory unit 202 and executes the instructions contained in that program. The control unit 203 controls the operation of the server 20. By operating according to the read program, the control unit 203 performs the functions of the receive control module 2031, the transmit control module 2032, the presentation control module 2033, and the evaluation processing module 2034.

[0053] The receiving control module 2031 controls the process by which the server 20 receives signals from external devices according to a communication protocol. The receiving control module 2031 receives, for example, first filtering information and second filtering information transmitted from the terminal device 10. Also, for example, the receiving control module 2031 receives first to fourth satellite images transmitted from the artificial satellite 30 via a ground station for a predetermined period of time in the past. The first filtering information and second filtering information may be uploaded directly to the server 20, for example.

[0054] The "predetermined past period" specifically refers to any period prior to the start of forest credit creation, based on the start date of the project. In this embodiment, the "predetermined past period" is set as the past 10 years based on the start date of the forest project, but it is not limited to this period.

[0055] For each of the first to fourth satellite images, the number of past images for a predetermined period can be arbitrarily set. Furthermore, the span over which the receiving control module 2031 acquires the first to fourth satellite images and the first to fourth filtering information during the predetermined past period can also be arbitrarily set.

[0056] The transmission control module 2032 controls the process by which the server 20 transmits signals to external devices according to a communication protocol. The presentation control module 2033 controls the process of presenting various information to the user.

[0057] The evaluation processing module 2034 selects any point within the first forest area as the first point before the creation of forest credits. There is no particular limit to the number of first points; one location within the first forest area may be selected as the first point, or multiple locations within the first forest area may be selected as the first point.

[0058] The evaluation processing module 2034 calculates the first vegetation index for the first forest area for a predetermined period based on the first satellite imagery for a predetermined period in the past. The evaluation processing module 2034 also calculates the second vegetation index for the second forest area for a predetermined period based on the second satellite imagery for a predetermined period in the past.

[0059] The first vegetation index is an indicator that shows the state of forest biomass present in the first forest area before forest credit creation. The second vegetation index is an indicator that shows the state of forest biomass present in the second forest area before forest credit creation. Examples of the first and second vegetation indices include the Normalized Difference Vegetation Index (NDVI), the backscattering coefficient, and estimates of forest biomass.

[0060] In this embodiment, the evaluation processing module 2034 optimizes the first satellite image using first filtering information before calculating the first vegetation index. Specifically, the evaluation processing module 2034 uses the first filtering information to extract the image portion (hereinafter referred to as the first image portion) from the first satellite image in which areas suitable for forest credit creation have been captured. Furthermore, the evaluation processing module 2034 optimizes the second satellite image using second filtering information before calculating the second vegetation index. Specifically, the evaluation processing module 2034 uses the second filtering information to extract the image portion (hereinafter referred to as the second image portion) from the second satellite image in which areas suitable for baseline setting have been captured.

[0061] In other words, in this embodiment, the evaluation processing module 2034 calculates a first vegetation index based on the first image portion obtained by optimizing the first satellite image using first filtering information. The evaluation processing module 2034 also calculates a second vegetation index based on the second image portion obtained by optimizing the second satellite image using second filtering information. Note that optimizing the satellite image using filtering information is not a mandatory process.

[0062] Furthermore, in this embodiment, the evaluation processing module 2034 calculates a first vegetation index each time it receives a first satellite image and calculates a second vegetation index each time it acquires a second satellite image. However, the evaluation processing module 2034 may, for example, receive all of the first and second satellite images for a predetermined period in the past and then calculate the first and second vegetation indices for that predetermined period all at once.

[0063] Specifically, for example, if both the first and second satellite images are optical satellite images, the evaluation processing module 2034 may calculate the NDVI as the first and second vegetation indices. That is, the evaluation processing module 2034 may, for example, obtain the reflectance (or radiant intensity) of the red band and the near-infrared band from the first and second image portions respectively, and substitute these values ​​into a general formula for calculating the NDVI to calculate the NDVI of the first forest area and the NDVI of the second forest area.

[0064] For example, if both the first and second satellite images are SAR images, the evaluation processing module 2034 may calculate backscattering coefficients as the first and second vegetation indices. That is, the evaluation processing module 2034 may, for example, acquire intensity images from each of the first and second image portions and convert the digital numbers of the intensity images into backscattering coefficients.

[0065] Alternatively, the evaluation processing module 2034 may input the first image portion into a pre-trained machine learning model (hereinafter abbreviated as "machine learning model") and have the machine learning model output an estimate of forest biomass as the first vegetation index. The evaluation processing module 2034 may also input the second image portion into the machine learning model and have the machine learning model output an estimate of forest biomass as the second vegetation index.

[0066] The machine learning model may be stored in, for example, the memory unit 202, or in an AI system not shown. The machine learning model may be, for example, a regression model, or a neural network such as a convolutional neural network (CNN) or a recurrent neural network (RNN). The training data for the machine learning model may consist, for example, satellite images of an arbitrary forest area and measured values ​​of forest biomass present in that arbitrary forest area. There may be, for example, one or more machine learning models. If multiple machine learning models are used, they may be of the same type, or they may be different types of machine learning models, such as one being a neural network and the other a multimodal generative AI model.

[0067] For example, the machine learning model may be a multimodal generation AI model. If the machine learning model is a multimodal generation AI model, prompts instructing the output of an estimate of forest biomass are also input to the machine learning model. The prompts may be hardcoded, for example, in a program stored in the memory unit 202. Alternatively, for example, an input device (not shown) provided on the server 20 may accept an input operation for the prompt, thereby inputting the prompt to the multimodal generation AI model. Alternatively, for example, the prompts may be pre-stored in the memory unit 202.

[0068] It should be noted that using a machine learning model to calculate the estimated forest biomass is not mandatory. The evaluation processing module 2034 may, for example, analyze the first and second satellite images using a rule-based analysis method with a known algorithm to calculate the estimated forest biomass for each.

[0069] The evaluation processing module 2034 selects a specific location within the second forest area as the second location if the trend of the second vegetation index over a predetermined period in the past (hereinafter referred to as the second trend) is similar to the trend of the first vegetation index over a predetermined period in the past at the first location (hereinafter referred to as the first trend).

[0070] The second location has technical significance as the base location for baseline setting. In other words, by selecting the second location, the evaluation processing module 2034 satisfies the various conditions included in the second filtering information and sets the forest area including the second location as a counterfactual virtual area.

[0071] Specifically, for example, the evaluation processing module 2034 extracts the first vegetation index at the first location from each of the first vegetation indexes for a predetermined period in the past in the first forest area. The evaluation processing module 2034 then grasps the first trend by, for example, arranging each of the first vegetation indexes for a predetermined period in the past at the first location in chronological order. The evaluation processing module 2034 then grasps the second trend at the arbitrary location by, for example, selecting an arbitrary location from the second forest area and performing the same processing as for the first location.

[0072] The evaluation processing module 2034 determines whether the second trend at any identified location is similar to the first trend by comparing it with the first trend, which has also been identified. Specifically, for example, the evaluation processing module 2034 selects multiple second forest areas. For each of the selected second forest areas, the evaluation processing module 2034 calculates the difference between the year-by-year trend that constitutes the second trend and the year-by-year trend that constitutes the second trend, and then sums the squares of the differences for each year. For example, the evaluation processing module 2034 selects a predetermined number (arbitrarily set) of second forest areas in ascending order of this sum, starting with the second forest area with the smallest sum. For example, the evaluation processing module 2034 sets the final selected predetermined number of second forest areas as the second forest areas to be selected for the second location.

[0073] In other words, the evaluation processing module 2034 determines, for example, that the second transition is similar to the first transition for the second forest regions, starting from the second forest region with the smallest sum value and continuing in ascending order until a predetermined number of values ​​are reached. Note that the method for determining whether the second transition is similar to the first transition is not limited to the example above and various methods can be employed.

[0074] If the evaluation processing module 2034 determines, for example, that the locations are similar, it selects an arbitrary location it has identified as the second location, and also selects another arbitrary location from within the second forest area and performs the same processing as described above. On the other hand, if it determines that the locations are not similar, the evaluation processing module 2034 selects another arbitrary location from within within the second forest area and performs the same processing as described above. The evaluation processing module 2034 selects one or more second locations by repeatedly performing the above series of processes.

[0075] There are no particular limitations on how many times the evaluation processing module 2034 repeats the above series of processes. For example, the evaluation processing module 2034 may perform the above series of processes for all points within the second forest area until the comparison between the first transition and the second transition is completed. Alternatively, for example, the evaluation processing module 2034 may perform the above series of processes a predetermined number of times (arbitrarily configurable). Alternatively, for example, the evaluation processing module 2034 may perform the above series of processes targeting a predetermined area (arbitrarily configurable) within the second forest area.

[0076] The evaluation processing module 2034 calculates the third vegetation index for the first location each time the third satellite image is periodically acquired, starting from the beginning of forest credit creation. Furthermore, the evaluation processing module 2034 calculates the fourth vegetation index for the second location each time the fourth satellite image is periodically acquired, starting from the beginning of forest credit creation.

[0077] There are no particular limitations on the timing at which the evaluation processing module 2034 periodically acquires the third and fourth satellite images. In this embodiment, the evaluation processing module 2034 periodically acquires the third and fourth satellite images once a year.

[0078] The third vegetation indicator is an indicator that shows the state of forest biomass present in the first forest area after the start of forest credit creation. The fourth vegetation indicator is an indicator that shows the state of forest biomass present in the second forest area after the start of forest credit creation. The specific examples for the third and fourth vegetation indicators are the same as the specific examples for the first and second vegetation indicators.

[0079] In this embodiment, the evaluation processing module 2034 calculates a third vegetation index for the first forest area based on a third satellite image, and then extracts the third vegetation index for the first location from the third vegetation index of the first forest area. The evaluation processing module 2034 also calculates a fourth vegetation index for the second forest area based on a fourth satellite image, and then extracts the fourth vegetation index for the second location from the fourth vegetation index of the second forest area. Here, the calculation method for the third vegetation index of the first forest area and the fourth vegetation index of the second forest area is the same as the calculation method for the first vegetation index of the first forest area and the second vegetation index of the second forest area. In this embodiment, the evaluation processing module 2034 sets the trend of the fourth vegetation index when the fourth vegetation index of the second location, which is calculated periodically, is arranged in a time series as the baseline. In other words, the evaluation processing module 2034 sets the trend of the fourth vegetation index in a counterfactual virtual area as the baseline.

[0080] The evaluation processing module 2034 assesses the reliability of the generated forest credit amount based on the third vegetation index at the first site and the fourth vegetation index at the second site, which are calculated periodically.

[0081] There are no particular limitations on the method for evaluating reliability based on the third and fourth vegetation indices. In this embodiment, the evaluation processing module 2034 calculates the increase in forest biomass by subtracting the amount of forest biomass present in the second forest area (the amount used to calculate the fourth vegetation indice) from the amount of forest biomass present in the first forest area (the amount used to calculate the third vegetation indice). The amount of forest biomass present in the first forest area is stored, for example, in the forest database 2021. The amount of forest biomass present in the second forest area is calculated or estimated, for example, based on the amount of forest biomass present in the first forest area, and the ratio of the third vegetation indice to the fourth vegetation indice. In relation to the calculation of the increase in forest biomass, the calculation of the third vegetation indice and the calculation of the fourth vegetation indice occur at the same time.

[0082] The evaluation processing module 2034 converts the amount of forest credits from the calculated increase in forest biomass and compares the amount of forest credits with a pre-set first baseline value. The first baseline value is a value that serves as a standard for whether the amount of forest credits satisfies additionality to a certain extent, and can be arbitrarily set according to the degree of strictness of the reliability evaluation. The first baseline value may be, for example, the amount of issued forest credits obtained from reports submitted by the user. The evaluation processing module 2034 evaluates the reliability as higher because the greater the extent to which the comparison value exceeds the first baseline value, the higher the additionality. On the other hand, the reliability as lower the extent to which the comparison value falls below the first baseline value, the lower the additionality.

[0083] The evaluation processing module 2034 may, for example, perform the above evaluation processing each time it calculates the third vegetation index for the first site and the fourth vegetation index for the second site. Alternatively, for example, the evaluation processing module 2034 may perform the above evaluation processing all at once after it has completed the process of periodically calculating the third vegetation index for the first site and the fourth vegetation index for the second site. Alternatively, for example, the evaluation processing module 2034 may comprehensively evaluate reliability by comprehensively considering the evaluation results of all evaluation processes that have been performed periodically.

[0084] The amount of forest biomass used to calculate the comparative value (the "amount of forest biomass present in the first forest area" described later) may be estimated, for example, based on measurements obtained by the user directly measuring the diameter, height, etc., of trees on-site. Alternatively, the amount of forest biomass used to calculate the comparative value may be estimated based on LiDAR (Light Detection and Ranging) or satellite imagery. Furthermore, the amount of forest biomass used to calculate the comparative value may be estimated based on the machine learning model described above.

[0085] [3 Data Structure] Figure 4 shows the data structure of a table stored by server 20. Note that Figure 4 is merely an example and does not exclude data that is not shown. Also, even data listed in the same table may be stored in separate memory areas in storage unit 202.

[0086] Figure 4 shows the data structure of the Forest Database 2021. The Forest Database 2021 shown in Figure 4 is a table with the Forest ID as the key and the following columns: 1st Basic Information, 1st Location Information, 1st Important Information, 3rd Important Information, 2nd Basic Information, 2nd Location Information, 2nd Important Information, 4th Important Information, and Evaluation Results.

[0087] The "Forest ID" field stores, for example, an identifier to uniquely identify the first forest area. The "First Basic Information" field stores, for example, basic information about the first forest area, first filtering information, and project information. The basic information about the first forest area includes, for example, location information (latitude and longitude, administrative division, etc.), total area covered by the forest, tree species, distribution of each tree species, age composition and structure of the trees, type and amount of forest biomass, protected area information, logging history, etc. Project information is information about the forest project and includes, for example, the implementing body, participating bodies, objectives, outline of implementation, and implementation period.

[0088] The item "First Location Information" is, for example, an item that stores basic information about the first location. Basic information about the first location includes, for example, location information (latitude, longitude, etc.), total area occupied by the forest, types of trees, distribution of each tree species, age composition and structure of the trees, types and amount of forest biomass, logging history, etc.

[0089] The item "First Important Information" is, for example, an item that stores information about the first satellite image for a predetermined period in the past, and the first vegetation index for a predetermined period in the first forest area. The information about the first satellite image may be, for example, a numerical value indicating scattering characteristics obtained based on the first satellite image (SAR image). Alternatively, the information about the first satellite image may be reference information for the first satellite image (e.g., file path, URL, etc.). In this case, the first satellite image itself may be stored in a separate storage area in the storage unit 202, such as a file system or cloud storage. In the example in Figure 4, the item "First Important Information" stores reference information as information about the first satellite image.

[0090] The item "Third Important Information" is, for example, an item that stores information on all regularly acquired third satellite images and all regularly calculated third vegetation indicators for first forest areas. Specific examples of information on third satellite images are similar to those for first satellite images.

[0091] The item "Second Basic Information" is an item that stores, for example, the basic information of the second forest area and the second filtering information. A specific example of the basic information of the second forest area is the same as a specific example of the basic information of the first forest area. The item "Second Location Information" is an item that stores, for example, the basic information of the second location. A specific example of the basic information of the second location is the same as a specific example of the basic information of the first location.

[0092] The item "Second Important Information" is, for example, an item that stores information on the second satellite image for a predetermined period in the past, and the second vegetation index for a predetermined period in the second forest area. Specific examples of information on the second satellite image are similar to the specific examples of information on the first satellite image.

[0093] The item "Fourth Important Information" is, for example, an item that stores information on all regularly acquired fourth satellite images and all regularly calculated fourth vegetation indicators for second forest areas. Specific examples of information on fourth satellite images are similar to those for first satellite images.

[0094] The item "Evaluation Result" is used to store the reliability evaluation results performed by Server 20. There are no particular limitations on the form of evaluation results stored in the item "Evaluation Result". For example, the item "Evaluation Item" may store individual evaluation results periodically performed by Server 20, or it may store the results of a comprehensive evaluation of those individual evaluation results. Alternatively, for example, the item "Evaluation Item" may store the evaluation results as ranks such as "A, B, C, ...", "1, 2, 3, ...", or "High, Medium, Low", or it may store them as numerical values ​​such as "100 points, 70 points, 35 points, ...". In the example in Figure 4, the item "Evaluation Item" stores the comprehensive evaluation results as a five-level rank of "A, B, C, D, E".

[0095] In this embodiment, the basic information for the first forest area and the second forest area is stored in the corresponding items of the forest database 2021 when the server 20 receives this information transmitted from the terminal device 10. The basic information for the first forest area includes, for example, the basic information for the first location, and the basic information for the second forest area includes, for example, the basic information for the second location. The server 20 may also store information obtained by searching public databases such as forest registers held by local governments and databases based on NFI (National Forest Inventory) based on the basic information received from the terminal device 10 in the corresponding items of the forest database 2021.

[0096] Furthermore, information regarding the first to fourth satellite images will be stored in the corresponding items of the forest database 2021 when the server 20 receives the first to fourth satellite images transmitted from the artificial satellite 30 via the ground station. In addition, the first filtering information and the second filtering information will be stored in the corresponding items when the server 20 receives this information transmitted from the terminal device 10. Furthermore, the first to fourth vegetation indices and evaluation results will be sequentially accumulated in the corresponding items of the forest database 2021 by the evaluation processing module 2034.

[0097] [4 actions] Referring to Figure 5, an example of the operation of server 20 when evaluating the reliability of forest credit amounts will be explained. Figure 5 is a flowchart showing an example of the operation of server 20 when evaluating the reliability of forest credit amounts.

[0098] In step S11 shown in Figure 5, the server 20 acquires the first satellite image and the second satellite image for a predetermined period of time in the past.

[0099] Specifically, for example, the operation reception unit 191 receives a request from the user to send first filtering information and second filtering information. The transmission / reception unit 192 transmits, for example, the first filtering information and second filtering information to the server 20. The first filtering information and second filtering information may be stored in the storage unit 180 in advance, or they may be input by the operation reception unit 191 receiving input operations from the user. The reception control module 2031 receives, for example, the first filtering information and second filtering information transmitted from the terminal device 10 and stores them in the forest database 2021.

[0100] The transmission control module 2032, for example, sends a transmission request to the ground station for the first and second satellite images for a predetermined period of time in the past. The reception control module 2031, for example, receives the first and second satellite images for the predetermined period of time in the past from the ground station that received the transmission request and stores this reference information in the forest database 2021.

[0101] The operation reception unit 191 may, for example, receive a user's request to transmit basic information for the first forest area and the second forest area, as well as project information. The transmission / reception unit 192 may, for example, transmit the basic information and project information to the server 20. The basic information and project information may, for example, be stored in the storage unit 180 in advance, or they may be input by the operation reception unit 191 receiving input operations from the user. The reception control module 2031 may, for example, receive the basic information and project information transmitted from the terminal device 10 and store it in the forest database 2021.

[0102] In step S12, the server 20 selects an arbitrary point within the first forest area as the first point. Specifically, for example, the evaluation processing module 2034 analyzes the acquired first satellite image and selects an arbitrary point that it deems preferable for selecting the second point as the first point. The evaluation processing module 2034 extracts the basic information of the first point from the basic information of the first forest area by searching the forest database 2021, for example, and stores it in the item "First Point Information".

[0103] In step S13, the server 20 calculates a first vegetation index for a predetermined period in the first forest area based on first satellite images for a predetermined period in the past. The server 20 also calculates a second vegetation index for a predetermined period in the second forest area based on second satellite images for a predetermined period in the past.

[0104] Specifically, for example, the evaluation processing module 2034 reads first filtering information from the forest database 2021 and uses this first filtering information to obtain first image portions for a predetermined period in the past. The evaluation processing module 2034 uses the first image portions for the predetermined period in the past to calculate the first vegetation index for the predetermined period in the first forest area. The evaluation processing module 2034 stores the first vegetation index for the predetermined period in the first forest area in the forest database 2021.

[0105] The evaluation processing module 2034, for example, reads second filtering information from the forest database 2021 and uses this second filtering information to obtain second image portions for a predetermined period in the past. The evaluation processing module 2034, for example, uses the second image portions for the predetermined period in the past to calculate the second vegetation index for the predetermined period in the second forest area. The evaluation processing module 2034, for example, stores the second vegetation index for the predetermined period in the second forest area in the forest database.

[0106] In step S14, a specific point within the second forest area where the second transition is similar to the first transition is selected as the second point.

[0107] Specifically, for example, the evaluation processing module 2034 extracts the first vegetation index at the first location from each of the first vegetation indexes for a predetermined period in the past in the first forest area. The evaluation processing module 2034 then grasps the first trend by, for example, arranging each of the first vegetation indexes for a predetermined period in the past at the first location in chronological order. The evaluation processing module 2034 then grasps the second trend at the arbitrary location by, for example, selecting an arbitrary location from the second forest area and performing the same processing as for the first location.

[0108] The evaluation processing module 2034 determines whether the second transition at an arbitrary location it has identified is similar to the first transition it has identified by comparing it with the first transition it has identified. If the evaluation processing module 2034 determines that they are similar, it selects the arbitrary location as the second location and also selects another arbitrary location from the second forest area and performs the same processing as described above. On the other hand, if it determines that they are not similar, the evaluation processing module 2034 selects another arbitrary location from the second forest area and performs the same processing as described above. The evaluation processing module 2034 selects one or more second locations by repeatedly performing the above series of processes. If the evaluation processing module 2034 searches the forest database 2021, it extracts the basic information of the second location from the basic information of the second forest area and stores it in the item "Second Location Information".

[0109] In step S15, the server 20 calculates the third vegetation index for the first location each time it periodically acquires the third satellite image, starting from the beginning of forest credit creation. The server 20 also calculates the fourth vegetation index for the second location each time it periodically acquires the fourth satellite image, starting from the beginning of forest credit creation.

[0110] Specifically, for example, the evaluation processing module 2034 calculates the third vegetation index for the first forest area based on the third satellite image, and then extracts the third vegetation index for the first location from among the third vegetation indexes for the first forest area. The evaluation processing module 2034 then stores all the third vegetation indexes for the first forest area that have been calculated periodically in the forest database 2021.

[0111] The evaluation processing module 2034 calculates the fourth vegetation index for the second forest area based on the fourth satellite image, and then extracts the fourth vegetation index for the second location from among the fourth vegetation indexes for the second forest area. The evaluation processing module 2034 sets the trend of the fourth vegetation index as a baseline, for example, when all the fourth vegetation indexes for the second location calculated periodically are arranged in a time series. The evaluation processing module 2034 stores all the fourth vegetation indexes for the second forest area calculated periodically in the forest database 2021.

[0112] The evaluation processing module 2034 generates graphs showing, for example, the first to fourth trends. The third trend represents the change in the third vegetation index when all the third vegetation index values ​​for the first location, calculated periodically, are arranged in time series. The fourth trend represents the change in the fourth vegetation index values ​​for the second location, calculated periodically, are arranged in time series. In other words, the fourth trend serves as the baseline.

[0113] The presentation control module 2033, for example, controls the presentation control unit 193 to display the graph on the display 141. That is, the presentation control module 2033 transmits information for displaying the graph to the terminal device 10, for example. The transmitting / receiving unit 192 receives information for displaying the graph from the server 20, for example. When the presentation control unit 193 receives a presentation request from the user, for example, it displays the graph on the display 141.

[0114] The presentation control module 2033 may, for example, present the graph to the administrator. In this case, the presentation control module 2033 may, for example, display the graph on the display (not shown) of an output device provided on the server 20 upon receiving a presentation request from the administrator.

[0115] The following describes an example of the display 141 screen when the user is presented with the first to fourth transitions, referring to Figure 6. Figure 6 is a schematic diagram showing an example of the display 141 screen when the user is presented with the first to fourth transitions.

[0116] In the example screen shown in Figure 6, Graph 1411 is displayed on Display 141. In Graph 1411, the vertical axis shows the vegetation indicators for the first and second locations, and the horizontal axis shows the number of years elapsed since the start of the forest project. In other words, "0" on the horizontal axis represents the start of the forest project.

[0117] In Graph 1411, the negative values ​​on the horizontal axis represent the plotted data for the first vegetation index 1412 at the first location and the second vegetation index 1413 at the second location for a predetermined period of time. As shown in Figure 6, the first and second trends are similar to each other.

[0118] In Graph 1411, the positive values ​​on the horizontal axis represent the plotted values ​​of the third vegetation index 1414 for all first locations, which were calculated periodically. Similarly, the positive values ​​on the horizontal axis of Graph 1411 also represent the plotted values ​​of the fourth vegetation index 1415 for all second locations, which were calculated periodically. In the example screen shown in Figure 6, the fourth trend is the baseline 1416.

[0119] Please note that the screen example in Figure 6 is merely an example, and various variations in the content and display method of Graph 1411 are conceivable. Furthermore, the process of presenting Graph 1411 to the user is not a mandatory process.

[0120] In the example shown in Figure 5, the server 20 executes the processes in step S14 and step S15 consecutively, but this is not the only case. For example, the server 20 may execute the processes up to step S14 separately from the processes from step S15 onward.

[0121] In step S16, the server 20 evaluates the reliability of the generated forest credit amount based on the third vegetation index at the first location and the fourth vegetation index at the second location, which are calculated periodically.

[0122] Specifically, for example, the evaluation processing module 2034 calculates a comparison value by multiplying the amount of forest biomass present in the first forest area by the value obtained by dividing the third vegetation index at the first location by the fourth vegetation index at the second location.

[0123] There are various variations in what data is used to define "the amount of forest biomass present in the first forest area." For example, multiple first-measured values ​​listed in a report on a forest project may be used to define "the amount of forest biomass present in the first forest area." The first-measured values ​​are the measured amounts of forest biomass present in the first forest area at each calculation point for multiple third-vegetation indicators that are calculated periodically. Information indicating the first-measured values ​​is stored, for example, in the forest database 2021. In this case, the evaluation processing module 2034 directly multiplies the first-measured values ​​indicated by the information read from the forest database 2021 by the ratio of the fourth-vegetation indicator at the second location to the third-vegetation indicator at the first location. The evaluation processing module 2034 performs this process for the first-measured values ​​corresponding to all of the multiple third-vegetation indicators that are calculated periodically.

[0124] Alternatively, for example, multiple theoretical quantities calculated based on each of the multiple second-order measurements described in the aforementioned report may be defined as "the amount of forest biomass present in the first forest area." The second-order measurement is an example of a measurement according to one aspect of this disclosure, and is the measured amount of forest biomass present in the first forest area at each calculation point of the first vegetation index for a predetermined period in the past. Information indicating the second-order measurement is stored, for example, in the forest database 2021. In this case, the evaluation processing module 2034 reads, for example, the information indicating the second-order measurement from the forest database 2021. The evaluation processing module 2034 calculates the theoretical quantity by multiplying the second-order measurement indicated by the read information by the ratio of the first vegetation index calculated at the calculation point that serves as the basis for the second-order measurement and the third vegetation index. Specifically, the theoretical quantity in this case is the theoretical quantity at the calculation point of the third vegetation index. Here, the second-order measurement used to calculate the theoretical quantity may be from any calculation point. In other words, the second-order measurement used to calculate the theoretical quantity may be any second-order measurement. The evaluation processing module 2034, for example, multiplies the calculated theoretical quantity by the value obtained by dividing the third vegetation index at the first location by the fourth vegetation index at the second location. The evaluation processing module 2034 then performs this process for the second measured values ​​that correspond to all of the multiple first vegetation indices calculated over a predetermined period in the past.

[0125] Alternatively, for example, the estimated amount of forest biomass obtained by inputting the third satellite image into the aforementioned machine learning model may be defined as "the amount of forest biomass present in the first forest area." In this case, the evaluation processing module 2034 inputs each of the periodically acquired third satellite images into the aforementioned machine learning model, and outputs multiple estimates of forest biomass from the machine learning model.

[0126] The evaluation processing module 2034, for example, compares the calculated comparison value with a pre-set first baseline value. The evaluation processing module 2034 evaluates the reliability as higher the greater the difference between the comparison value and the first baseline value. Conversely, the reliability as lower the greater the difference between the comparison value and the first baseline value. The evaluation processing module 2034, for example, stores the evaluation results in the forest database 2021.

[0127] In step S17, the server 20 presents the evaluation results to at least one of the user and the administrator. Specifically, for example, the presentation control module 2033 presents the evaluation results from the evaluation processing module 2034 to at least one of the user or the administrator.

[0128] When presenting evaluation results to the user, the transmission control module 2032 transmits, for example, information for displaying the evaluation results to the terminal device 10. The transmission / reception unit 192 receives, for example, information for displaying the evaluation results from the server 20. When the presentation control unit 193 receives, for example, a presentation request from the user, it displays the evaluation results on the display 141.

[0129] When presenting evaluation results to the administrator, the presentation control module 2033, for example, upon receiving a presentation request from the administrator, displays the evaluation results on the display of the output device provided on the server 20.

[0130] Furthermore, if the output devices of output device 14 and server 20 are printers, the presentation control module 2033 may, for example, print out paper media with the evaluation results printed on it from the output devices of output device 14 and server 20. Also, the process by which the presentation control module 2033 presents the evaluation results to at least one of the user and the administrator is not a mandatory process.

[0131] [5 Summary] As described above, in this embodiment, the transmission control module 2032 transmits a transmission request to the ground station for a predetermined period of past first and second satellite images, triggered by the reception of first and second filtering information. The reception control module 2031 receives, for example, the first and second satellite images for a predetermined period of past past from the ground station that received the transmission request. The evaluation processing module 2034 analyzes the acquired first satellite images and selects an arbitrary location that it deems preferable for selecting a second location as the first location. The evaluation processing module 2034 calculates a first vegetation index for a predetermined period of past past in the first forest area using the first satellite images optimized by the first filtering information. The evaluation processing module 2034 calculates a second vegetation index for a predetermined period of past past in the second forest area using the second satellite images optimized using the second filtering information. The evaluation processing module 2034 selects one or more second locations by comparing the first and second trends and determining whether the second trend is similar to the first trend.

[0132] Furthermore, in this embodiment, the evaluation processing module 2034 calculates a third vegetation index for the first forest area based on the third satellite image, and then extracts the third vegetation index for the first location from the third vegetation index of the first forest area. The evaluation processing module 2034 calculates a fourth vegetation index for the second forest area based on the fourth satellite image, and then extracts the fourth vegetation index for the second location from the fourth vegetation index of the second forest area. The evaluation processing module 2034 calculates a comparison value by multiplying the amount of forest biomass present in the first forest area by the value obtained by dividing the third vegetation index of the first location by the fourth vegetation index of the second location. The evaluation processing module 2034 evaluates the reliability of the forest credit amount by comparing the comparison value with a pre-set first reference value.

[0133] This allows server 20 to select a location as the second location where a second vegetation index can be obtained in which the second transition is similar to the first transition. Therefore, if the transition of the fourth vegetation index at the second location (fourth transition) is set as the baseline, this baseline will be approximately the same as the transition of the third vegetation index at the first location in the case where no forest project is implemented. Thus, server 20 can set a conservative and realistic baseline and accurately evaluate the reliability of the amount of forest credit.

[0134] Furthermore, because it is possible to set a conservative and realistic baseline, the accuracy of the predicted revenue from forest credits, in other words, the accuracy of additionality, is also improved. From this perspective as well, Server 20 can accurately assess the reliability of the amount of forest credits.

[0135] [6 Variations] System 1 can provide various additional services in its evaluation service that can ensure the reliability of forest credit quantities. Below are some examples of additional services that System 1 can offer.

[0136] <6-1 First Variation> Server 20 may, for example, determine whether or not there is a forest-destroyed area in the first forest area and notify the user of the determination result. In the first modified example, the forest-destroyed area is an area in the first forest area where the forest was destroyed by logging or other means before the creation of forest credits, but where forest existed at the start of forest credit creation.

[0137] First, server 20 may acquire pre-creation image data and post-creation image data. Pre-creation image data is image data of the first forest area at a first point in time (any point in time) before the creation of forest credits. Post-creation image data is image data of the first forest area at a second point in time (any point in time) after the start of forest credit creation. There are no particular limitations on the types of image data that can be used as pre-creation image data and post-creation image data. Pre-creation image data and post-creation image data may be, for example, satellite images or aerial images taken by a drone, etc. Also, there are no particular limitations on the number of pre-creation image data and post-creation image data acquired by server 20.

[0138] Specifically, for example, an input device provided on server 20 may accept an image data acquisition operation by the administrator. The evaluation processing module 2034 may, for example, accept the acquisition operation and read and acquire pre-creation image data and post-creation image data from an image database (not shown).

[0139] The image database may be stored in, for example, the storage unit 202, or it may be managed by a management server separate from the server 20. The image database may store, for example, reference information for pre-creation image data and reference information for post-creation image data. The reference information may be, for example, a file path or a URL. In this case, the pre-creation image data itself and the post-creation image data itself may be stored in a separate storage area in the storage unit 202, for example, a file system or cloud storage.

[0140] Next, the server 20 may determine whether or not there was a forest loss area in the first forest region by analyzing the pre-creation image data and the post-creation image data. Specifically, for example, the evaluation processing module 2034 may determine whether or not there was a forest loss area by analyzing the pre-creation image data and the post-creation image data read from the image database.

[0141] There are no particular limitations on the analysis methods used by the evaluation processing module 2034 for both pre-creation and post-creation image data. In the first modified example, the evaluation processing module 2034 analyzes these image data using the following methods.

[0142] In other words, the evaluation processing module 2034 may, for example, preprocess the pre-creation image data and post-creation image data read from the image database. As preprocessing, the evaluation processing module 2034 may perform at least one correction process, such as atmospheric correction, geometric correction, or cloud mask correction. Note that preprocessing is not a mandatory process.

[0143] The evaluation processing module 2034 may, for example, perform time-series analysis by comparing multiple pre-creation image data and multiple post-creation image data to detect the difference between the pre-creation image data and the post-creation image data. In this difference detection, the evaluation processing module 2034 may, for example, use NDVI that can be calculated based on these image data. The evaluation processing module 2034 may, for example, determine whether or not a forest loss area existed based on the difference detection result.

[0144] Furthermore, the evaluation processing module 2034 may, for example, input the pre-creation image data and post-creation image data into a trained machine learning model such as a random forest, a support vector machine (SVM), or a convolutional neural network, and have the machine learning model predict the presence or absence of forest loss areas. Alternatively, the evaluation processing module 2034 may, for example, input the pre-creation image data and post-creation image data into a geographic information system (GIS) and have the GIS determine the presence or absence of forest loss areas.

[0145] Next, if the server 20 determines that there is a forest loss area in the first forest area, it may notify the user of the determination result. Specifically, for example, if the evaluation processing module 2034 determines that there is a forest loss area in the first forest area, it may control the display control unit 193 to display the determination result on the display 141. Alternatively, for example, the evaluation processing module 2034 may control the audio processing unit 170 to output an audio notification of the determination result from the speaker 172.

[0146] The evaluation processing module 2034 may, for example, notify the administrator of the judgment result. In this case, the evaluation processing module 2034 may, for example, display the judgment result on the display of the output device provided on the server 20. Alternatively, the evaluation processing module 2034 may output the judgment result as audio from the microphone (not shown) of the output device.

[0147] Thus, according to the first modification, users can be notified that areas of forest loss existed before forest credits were generated. This allows users to understand that the amount of forest credits that would have been generated (if forests had existed in the lost areas) was not generated, meaning that the amount of forest credits is less than it should have been. Therefore, according to the first modification, information about the forest project can be disclosed to users comprehensively and transparently, and the reliability of the amount of forest credits can be evaluated with greater accuracy.

[0148] <6-2 Second Variation> Server 20 may, for example, notify the user of the result if the percentage or area of ​​forest loss at the end of a predetermined period after the start of the forest project exceeds a standard value. The "predetermined period after the start of the forest project" specifically refers to a predetermined period from the start of forest credit creation. The predetermined period is a period that can be set arbitrarily. In the second modified example, the forest loss area is an area in the first forest area where forest existed before the creation of forest credit, but where forest ceased to exist due to logging or other reasons at some point after the start of forest credit creation.

[0149] First, the server 20 may periodically acquire monitoring image data during a predetermined period after the start of the forest project. The monitoring image data is image data of the first forest area captured during a predetermined period after the start of the forest project. There are no particular limitations on the types of image data that can be used as monitoring image data. For example, the monitoring image data may be satellite images or aerial images taken by a drone, etc. Furthermore, there are no particular limitations on the number of monitoring image data acquired by the server 20, nor are there any particular limitations on the timing at which the server 20 periodically acquires the monitoring image data.

[0150] Specifically, for example, an input device provided on server 20 may accept an operation by the administrator to start acquiring image data. The receiving control module 2031 may periodically acquire monitoring image data by accepting an acquisition start operation. Alternatively, for example, the receiving control module 2031 may periodically acquire monitoring image data by detecting when a predetermined timing (which can be arbitrarily set in advance) has arrived after the start of the forest project.

[0151] If the monitoring image data is satellite imagery, the receiving control module 2031 may acquire the monitoring image data from, for example, the artificial satellite 30 via a ground station. If the monitoring image data is aerial imagery, the receiving control module 2031 may acquire the monitoring image data from, for example, a drone or helicopter.

[0152] The receiving control module 2031 may store information regarding monitoring image data acquired from, for example, an artificial satellite 30 or a drone in an image database (not shown). The image database may be stored in, for example, the storage unit 202, or it may be managed by a management server separate from the server 20.

[0153] Next, the server 20 may analyze the periodically acquired monitoring image data to calculate the percentage or area of ​​forest loss in the first forest area (hereinafter referred to as the loss percentage or loss area) at the end of a predetermined period. Specifically, for example, the evaluation processing module 2034 may analyze the monitoring image data acquired from the artificial satellite 30 or a drone to calculate the loss percentage or loss area. The analysis method for the monitoring image data may be the same as the analysis methods for the pre-creation image data and post-creation image data in the first modified example.

[0154] Next, the server 20 may compare the calculated loss rate or loss area with a reference value and notify the user of the comparison result if the loss rate or loss area exceeds the reference value. Specifically, for example, the evaluation processing module 2034 may compare the calculated loss rate or loss area with a reference value, and if the loss rate or loss area exceeds the reference value, it may control the presentation control unit 193 to display the comparison result indicating that the reference value has been exceeded on the display 141. Alternatively, for example, the evaluation processing module 2034 may control the audio processing unit 170 to output an audio message from the speaker 172 notifying the user of the comparison result indicating that the reference value has been exceeded.

[0155] The baseline value is, for example, a value that can be arbitrarily set in advance, and may be determined depending on where the acceptable limit for the reduction in forest credit due to deforestation is set.

[0156] The evaluation processing module 2034 may, for example, notify the administrator of the comparison results. In this case, the evaluation processing module 2034 may, for example, display the comparison results on the display of the output device provided on the server 20. Alternatively, the evaluation processing module 2034 may output the comparison results as audio from the microphone (not shown) of the output device.

[0157] For example, if the percentage or area of ​​loss exceeds a threshold, the evaluation processing module 2034 may calculate an estimated amount of forest credit loss based on the percentage or area of ​​loss and notify the user or administrator of the difference between the estimated value and the threshold value. This allows the user or administrator to demand compensation for the revenue that would have been earned based on the difference from the party responsible for the deforestation.

[0158] Thus, according to the second modification, users can be notified if the loss rate or loss area exceeds a standard value. This allows users to understand that the amount of forest credits that would have been generated even if legitimate circumstances such as logging based on appropriate reasons had occurred was not generated, meaning that the amount of forest credits generated is less than that considering legitimate circumstances. Therefore, according to the second modification, information on forest projects can be disclosed to users comprehensively and transparently, and the reliability of the amount of forest credits can be evaluated with greater accuracy.

[0159] [7. Basic Computer Hardware Configuration] Figure 7 is a block diagram showing the basic hardware configuration of computer 90. Computer 90 includes at least a processor 901, main memory 902, auxiliary memory 903, and a communication interface IF991. These are electrically connected to each other by a communication bus 921.

[0160] The processor 901 is hardware for executing the instruction set written in a program. The processor 901 consists of an arithmetic unit, registers, peripheral circuits, etc.

[0161] Main memory 902 is used to temporarily store programs and data processed by programs, etc. For example, it is a volatile memory such as DRAM (Dynamic Random Access Memory).

[0162] Auxiliary storage device 903 refers to a storage device for saving data and programs. Examples include flash memory, HDD (Hard Disk Drive), magneto-optical disk, CD-ROM, DVD-ROM, and semiconductor memory.

[0163] The IF991 communication interface is an interface for inputting and outputting signals for communication with other computers via a network using wired or wireless communication standards.

[0164] A network consists of various mobile communication systems, such as the internet, LANs, and wireless base stations. For example, a network includes 3G, 4G, and 5G mobile communication systems, LTE (Long Term Evolution), and wireless networks that can connect to the internet via designated access points (e.g., Wi-Fi®). When connecting wirelessly, communication protocols include, for example, Z-Wave®, ZigBee®, and Bluetooth®. When connecting via a wired connection, the network also includes connections made directly via USB (Universal Serial Bus) cables, etc.

[0165] Furthermore, by distributing all or part of each hardware configuration across multiple computers 90 and connecting them to each other via a network, a computer 90 can be virtually realized. Thus, the concept of computer 90 includes not only a computer 90 housed in a single enclosure or case, but also a virtualized computer system.

[0166] [8. Basic Functional Configuration of Computer 90] The functional configuration of the computer realized by the basic hardware configuration of computer 90 (Figure 7) will be explained. The computer comprises at least one functional unit: a control unit, a memory unit, and a communication unit.

[0167] Furthermore, the functional units of computer 90 can also be realized by distributing all or part of each functional unit across multiple computers 90 interconnected via a network. The concept of computer 90 includes not only a single computer 90 but also a virtualized computer system.

[0168] The control unit is realized when the processor 901 reads various programs stored in the auxiliary storage device 903, loads them into the main memory device 902, and executes processing according to those programs. The control unit can realize various functional units that perform information processing depending on the type of program. In this way, the computer is realized as an information processing device that performs information processing.

[0169] The memory unit is implemented by the main memory 902 and the auxiliary memory 903. The memory unit stores data, various programs, and various databases. The processor 901 can also reserve memory areas corresponding to the memory unit in the main memory 902 or the auxiliary memory 903 according to the program. The control unit can also cause the processor 901 to perform operations such as adding, updating, and deleting data stored in the memory unit according to the various programs.

[0170] A database, specifically a relational database, is used to manage and link together tabular data sets called masters, which are structurally defined by rows and columns. In a database, tables are called tables, masters are called masters, the columns of tables are called columns, and the rows of tables are called records. In a relational database, relationships can be established and linked between tables and masters.

[0171] Typically, each table and master has a primary key column to uniquely identify records, but setting a primary key column is not mandatory. The control unit can instruct the processor 901 to add, delete, or update records in specific tables and masters stored in the memory unit, according to various programs.

[0172] Furthermore, by storing data, various programs, and various databases in the memory unit, the information processing device and information processing system related to this disclosure can be considered to have been manufactured.

[0173] Furthermore, the databases and masters in this disclosure may include any data structures (lists, dictionaries, associative arrays, objects, etc.) in which information is structurally defined. Data structures also include data that can be considered as data structures by combining data with functions, classes, methods, etc., written in any programming language.

[0174] The communication unit is implemented by the communication IF991. The communication unit provides the functionality to communicate with other computers 90 via the network. The communication unit can receive information transmitted from other computers 90 and input it to the control unit. The control unit can cause the processor 901 to perform information processing on the received information according to various programs. The communication unit can also transmit information output from the control unit to other computers 90.

[0175] Furthermore, each of the above-mentioned configurations, functions, processing units, processing means, etc., may be implemented in hardware, in whole or in part, for example, by designing them as integrated circuits. The present invention can also be implemented 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 the processor of that computer reads the program code stored in the storage medium. In this case, the program code read from the storage medium itself realizes the functions of the embodiments described above, and the program code itself and the storage medium on which it is stored constitute the present invention. Examples of storage media used to supply 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, and the like.

[0176] Furthermore, the program code that implements the functions described in this embodiment can be implemented in a wide range of programming or scripting languages, such as assembler, C / C++, Perl, Shell, PHP, Java®, JavaScript, and TypeScript.

[0177] Furthermore, the program code of the software that realizes the functions of the embodiment may be distributed via a network and stored on a storage means such as a computer's hard disk or memory, or on a storage medium such as a CD-RW or CD-R, and the computer's processor may read and execute the program code stored on the storage means or storage medium.

[0178] The functions realized by the components described herein may be implemented in a circuit 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 realize the functions described herein. A processor is considered to be a circuit or processing circuitry, including transistors and other circuits. A processor may be a programmed processor that executes a program stored in memory.

[0179] In this specification, circuitry, unit, and means are hardware programmed to perform or execute the functions described herein. Such hardware may be any hardware disclosed herein, or any hardware known to be programmed to perform or execute the functions described herein.

[0180] If the hardware is a processor that is considered to be a type of circuitry, then the circuitry, means, or unit is a combination of hardware and software used to constitute the hardware and / or processor.

[0181] Although several embodiments of this 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 their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents.

[0182] [9. Addendum] The details described in each of the above embodiments are noted below.

[0183] <Note 1> A program for execution on a computer having a processor and memory, the program comprising the steps of: obtaining first image data of a first forest area subject to forest credit generation and second image data of a second forest area located around the first forest area for a predetermined past period; selecting an arbitrary point within the first forest area as the first point; calculating a first vegetation index for the first forest area for a predetermined past period based on the first image data for the predetermined past period, and calculating a second vegetation index for the second forest area for a predetermined past period based on the second image data for the predetermined past period. A program that performs the following steps: selecting a specific location within the second forest area as the second location, where the trend of the second vegetation index over a predetermined period in the past is similar to the trend of the first vegetation index over a predetermined period in the past at the first location; calculating the third vegetation index at the first location each time third image data related to the first forest area is acquired periodically from the start of forest credit creation, and calculating the fourth vegetation index at the second location each time fourth image data related to the second forest area is acquired periodically; and evaluating the reliability of the amount of forest credit created based on the periodically calculated third and fourth vegetation indices.

[0184] <Note 2> In the evaluation step, the program obtains an arbitrary measured value of forest biomass present in the first forest area at each calculation point of the first vegetation index for a predetermined period in the past, calculates a theoretical value by multiplying the obtained arbitrary measured value by the ratio of the first vegetation index and the third vegetation index calculated at the calculation point that serves as the basis for the arbitrary measured value, and evaluates the reliability based on the calculated theoretical value (as described in Appendix 1).

[0185] <Note 3> In the evaluation step, the program described in (Appendix 1) periodically inputs the third image data into a trained machine learning model, outputs an estimate of the forest biomass present in the first forest area from the machine learning model, and evaluates the reliability based on the output estimate.

[0186] <Note 4> A program as described in any of (Appendix 1) to (Appendix 3), which causes the processor to further execute the following steps for the first forest area: acquiring image data at a first point in time before the creation of forest credits and image data at a second point in time after the start of forest credit creation; determining whether or not there was a forest loss area in the first forest area before the creation of forest credits by analyzing the image data at the first point in time and the image data at the second point in time; and notifying the user of the determination result if it is determined that a forest loss area existed.

[0187] <Note 5> A program as described in any of (Appendix 1) to (Appendix 4), which causes the processor to further execute the following steps during a predetermined period after the start of forest credit creation: periodically acquire image data of the first forest area captured during the predetermined period; analyze the periodically acquired image data of the first forest area to calculate the percentage or area of ​​forest loss in the first forest area at the end of the predetermined period; and compare the calculated percentage or area with a reference value and notify the user of the comparison result if the percentage or area exceeds the reference value.

[0188] <Note 6> An information processing device comprising a control unit and a storage unit, wherein the control unit executes all steps in any of the programs described in (Appendix 1) to (Appendix 5).

[0189] <Note 7> A method to be executed on a computer having a processor and memory, wherein the processor executes all steps in any of the programs described in (Appendix 1) to (Appendix 5).

[0190] <Note 8> A system comprising means for executing all steps in any of the programs described in (Appendix 1) to (Appendix 5). [Explanation of symbols]

[0191] 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 Interface 25…Memory 2 hours… storage 29… Processor 30…Artificial satellite

Claims

1. A program to be executed on a computer having a processor and memory, The program is provided to the processor: The steps include acquiring first image data of a first forest area that is the target of forest credit creation, and second image data of a second forest area located around the first forest area, for a predetermined period in the past, The steps include selecting any point within the first forest area as the first point, The steps include: calculating a first vegetation index for the first forest area for the predetermined past period based on the first image data for the predetermined past period; and calculating a second vegetation index for the second forest area for the predetermined past period based on the second image data for the predetermined past period; The steps include selecting a specific location within the second forest area as the second location, such that the trend of the second vegetation index during the predetermined past period is similar to the trend of the first vegetation index during the predetermined past period at the first location, From the start of the creation of the aforementioned forest credits, the third vegetation index of the first location is calculated each time third image data relating to the first forest area is periodically acquired, and the fourth vegetation index of the second location is calculated each time fourth image data relating to the second forest area is periodically acquired. A step of evaluating the reliability of the amount of forest credit created based on the third and fourth vegetation indices calculated periodically. A program that executes the command.

2. In the evaluation step described above, From among the measured forest biomass present in the first forest area at each calculation point of the first vegetation index for the aforementioned predetermined past period, an arbitrary measured value is obtained. A theoretical quantity is calculated by multiplying any acquired measured quantity by the ratio of the first vegetation index calculated at the calculation point that serves as the basis for said measured quantity, and the third vegetation index. The program according to claim 1, which evaluates the reliability based on the calculated theoretical quantity.

3. In the evaluation step described above, The third image data acquired periodically is input into a trained machine learning model, and the machine learning model outputs an estimate of the forest biomass present in the first forest area. The program according to claim 1, which evaluates the reliability based on the outputted estimate.

4. The steps include obtaining, with respect to the first forest area, image data at a first point in time before the creation of the forest credits and image data at a second point in time after the start of the creation of the forest credits, The steps include: determining whether or not a forest loss area existed in the first forest area before the creation of the forest credit by analyzing the image data at the first time point and the image data at the second time point; If it is determined that the aforementioned missing area exists, the steps include notifying the user of the determination result. The program according to claim 1, which causes the processor to further execute the following.

5. The steps include: periodically acquiring image data of the first forest area captured during a predetermined period after the start of the creation of the aforementioned forest credits; The steps include: analyzing image data of the first forest area acquired periodically to calculate the percentage or area of ​​forest loss in the first forest area at the end of the predetermined period; The process involves comparing the calculated ratio or area with a standard value, and notifying the user of the comparison result if the ratio or area exceeds the standard value. The program according to claim 1, which causes the processor to further execute the following.

6. An information processing device comprising a control unit and a storage unit, wherein the control unit executes all steps in the program described in any one of claims 1 to 5.

7. A method to be performed on a computer comprising a processor and memory, wherein the processor performs all steps of a program according to any one of claims 1 to 5.

8. A system comprising means for executing all steps in the program described in any one of claims 1 to 5.

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