Program, method, information processing device and system

Abstract

To easily confirm crops of a farm field by using a mobile body while suppressing the cost of a device.SOLUTION: Provided is a program to be executed by a computer including a processor and a memory. The program allows the processor to execute the steps of: acquiring an image obtained by imaging a farm field with an RGB camera mounted on a flying body; acquiring a color chart image having the correspondence relation to an analysis content, captured by the RGB camera under the same environment as the farm field; calculating a vegetation index on the basis of colors included in the image of the farm field and colors included in the color chart image; and estimating vegetation in the farm field from the vegetation index calculated based on the colors of the color chart and the vegetation index calculated based on the colors of the farm field.SELECTED DRAWING: Figure 8

Description

Technical Field

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

Background Art

[0002] There is a technique of calculating the NDVI (Normalized Difference Vegetation Index) based on data of a field photographed from above by a camera and using the calculated NDVI as a growth index of crops in the field (see Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] To calculate the NDVI, it is necessary to use a multispectral camera. However, a multispectral camera is expensive and difficult to handle.

[0005] An object of the present disclosure is to simply check crops in a field using a moving body while suppressing the cost of the device.

Means for Solving the Problems

[0006] A program for causing a computer including a processor and a memory to execute. The program causes the processor to perform steps of: acquiring an image of a farm field captured by an RGB camera mounted on an aircraft; acquiring an image of a color chart having a correspondence with analysis content, captured by the RGB camera in the same environment as the farm field; calculating a vegetation index based on the colors included in the image of the farm field and the colors included in the image of the color chart; and estimating the vegetation in the farm field from the vegetation index calculated based on the colors of the color chart and the vegetation index calculated based on the colors of the farm field.

Effect of the Invention

[0007] According to the present disclosure, it is possible to easily check the crops in a farm field by using a mobile body while suppressing the cost of the device.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Embodiments for Carrying Out the Invention

[0009] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the following description, the same parts are denoted by the same reference numerals. Their names and functions are also the same. Therefore, detailed descriptions thereof will not be repeated.

[0010] <Overview> In the system according to this embodiment, a RGB camera mounted on an aircraft photographs a farmland from above. A color chart having a correspondence relationship with the analysis content is placed in the farmland. The system photographs the color chart together with the farmland. The system discriminates the color of the photographed image and estimates a region where a color corresponding to a predetermined color in the color chart is discriminated as a target region.

[0011] <1 Configuration Diagram of the Whole System> FIG. 1 is a block diagram showing an example of the overall configuration of system 1. The system 1 shown in FIG. 1 includes, for example, a terminal device 10, a server 20, a mobile body 30, and an operation device 40. The terminal device 10, the server 20, the mobile body 30, and the operation device 40 are communicatively connected via, for example, a network 80.

[0012] In FIG. 1, an example in which the system 1 includes one terminal device 10 is shown, but the number of terminal devices 10 included in the system 1 is not limited to one. The number of terminal devices 10 included in the system 1 may be two or more.

[0013] In the present embodiment, an aggregate of a plurality of devices may be regarded as one server. The way of distributing the plurality of functions required to implement the server 20 according to the present embodiment for one or more pieces of hardware can be appropriately determined in view of the processing capabilities of each piece of hardware and / or the specifications required for the server 20. Further, the server 20 may be composed of a plurality of servers according to the functions it has.

[0014] In FIG. 1, an example is shown in which the system 1 includes a set of mobile bodies 30 and an operating device 40. However, the number of mobile bodies 30 and operating devices 40 included in the system 1 is not limited to a set. The number of mobile bodies 30 and operating devices 40 included in the system 1 may be two sets or more. Also, the mobile body 30 may move autonomously or may move in response to an operation by the operating device 40. When the mobile body 30 moves autonomously, the operating device 40 may not be included in the system 1.

[0015] The terminal device 10 shown in FIG. 1 is, for example, an information processing device possessed by a farmer (farm manager) who manages a farm. The farm includes, for example, fields and arable land. The terminal device 10 receives operation instructions and information input from a user and transmits predetermined information to the server 20. The predetermined information includes, for example, information regarding the farm with which the user is involved or information regarding the cultivation of crops. Also, the terminal device 10 receives information transmitted from the server 20 and information transmitted from the mobile body 30 and presents it to the user. The information transmitted from the server 20 includes, for example, information regarding the growth of crops. The information transmitted from the mobile body 30 includes, for example, information regarding the position (latitude, longitude, altitude) of the mobile body 30, information regarding the storage amount of the spraying material, information regarding the remaining battery level, camera images, and the like.

[0016] The terminal device 10 is realized by, for example, a mobile terminal such as a smartphone or a tablet. The terminal device 10 may be a stationary PC (Personal Computer) or a laptop PC. The terminal device 10 may also be a wearable terminal such as an HMD (Head Mount Display) or a wristwatch-type terminal.

[0017] The terminal device 10 includes a communication IF (Interface) 12, an input device 13, an output device 14, a memory 15, a storage 16, and a processor 19. The input device 13 is a device for receiving input operations from the user (for example, a pointing device such as a touch panel, a touch pad, a mouse, etc., a keyboard, etc.). The output device 14 is a device for presenting information to the user (a display, a speaker, etc.).

[0018] The server 20 is, for example, an information processing device that estimates a region of interest in a farm field based on information input from the user, information transmitted from the mobile body 30, or information regarding the environment acquired from the outside.

[0019] The server 20 is realized, for example, by a computer connected to the 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 with an input device for receiving input operations from the user and an output device for presenting information to the user.

[0020] The mobile body 30 is a device that moves on the ground or in the air. The mobile body 30 includes, for example, a tractor or a vehicle that moves on the ground by tires or crawlers. Also, the mobile body 30 includes, for example, a multi-copter type drone that moves in the air having a propeller or a fixed-wing drone that moves in the air by a fixed wing. The mobile body 30 operates according to operations from the operation device 40. Also, the mobile body 30 may operate autonomously based on the movement method set in the server 20.

[0021] The mobile body 30, for example, moves over the farm field and photographs the crops planted in the farm field from above. The mobile body 30, for example, flies at a height of about 50 m to 100 m and photographs the farm field. A color chart is placed within the range photographed by the mobile body 30.

[0022] The color chart has colors that have a correspondence relationship with, for example, the content to be analyzed. Specifically, for example, the color chart has a plurality of regions painted in green of varying shades according to the leaf color density. The leaf color density represented by the color chart is, for example, the leaf color density corresponding to the crop to be analyzed. Specifically, the leaf color density represented by the color chart is the leaf color density corresponding to the leaf color of rice.

[0023] On the color chart, for example, there are regions painted in multiple types of green while changing the density, from regions painted in a yellowish - green color close to a low leaf color density to regions painted in a dark green color with a high leaf color density. The color chart, for example, has regions painted in 7 types of green arranged in descending order of the darkness of the green.

[0024] The color chart, for example, has a rectangular shape with a longitudinal direction. The color chart, for example, has a length of about 0.5 m to 1 m in the short - hand direction and a length of several meters (2 - 4 m) in the longitudinal direction. The green regions are painted, for example, so as to be arranged in the longitudinal direction.

[0025] The operation device 40 is an information - processing device that controls the operation of the mobile body 30 based on operations from the user. Also, the operation device 40 receives information transmitted from the server 20 or the mobile body 30 and presents it to the user.

[0026] The operation device 40 is realized, for example, by a mobile terminal such as a smartphone or a tablet. The operation device 40 may be a dedicated device for operating the mobile body 30. The operation device 40 has an input part for receiving operations from the user and an output part (display, speaker, etc.) for presenting information to the user.

[0027] Each information processing device is configured by a computer including an arithmetic unit and a storage unit. The basic hardware configuration of the computer and the basic functional configuration of the computer realized by the hardware configuration will be described later. For each of the terminal device 10, the server 20, and the operation device 40, descriptions overlapping with the basic hardware configuration of the computer and the basic functional configuration of the computer described later are omitted.

[0028] <1.1 Configuration of Terminal Device> FIG. 2 is a block diagram showing a configuration example of the terminal device 10 shown in FIG. 1. As shown in FIG. 2, the terminal device 10 includes a communication unit 120, an input device 13, an output device 14, an audio processing unit 17, a microphone 171, a speaker 172, a camera 160, a position information sensor 150, a storage unit 180, and a control unit 190. Each block included in the terminal device 10 is electrically connected by, for example, a bus or the like.

[0029] The communication unit 120 performs processes such as modulation / demodulation processing for the terminal device 10 to communicate with other devices. The communication unit 120 performs transmission processing on the signal generated by the control unit 190 and transmits it to the outside (for example, the server 20, the mobile body 30, or the operation device 40). The communication unit 120 performs reception processing on the signal received from the outside and outputs it to the control unit 190.

[0030] The input device 13 is a device for a user operating the terminal device 10 to input instructions or information. The input device 13 is realized by, for example, a touch-sensitive device 131 into which an instruction is input by touching an operation surface. When the terminal device 10 is a PC or the like, the input device 13 may be realized by a reader, a keyboard, a mouse, or the like. The input device 13 converts an instruction input from the user into an electrical signal and outputs the electrical signal to the control unit 190. Note that the input device 13 may include, for example, a reception port for receiving an electrical signal input from an external input device.

[0031] The output device 14 is a device for presenting information to the user who operates the terminal device 10. The output device 14 is realized by, for example, a display 141 or the like. The display 141 displays data according to the control of the control unit 190. The display 141 is realized by, for example, an LCD (Liquid Crystal Display), an organic EL (Electro-Luminescence) display, or the like.

[0032] The audio processing unit 17 performs, for example, digital-to-analog conversion processing of an audio signal. The audio processing unit 17 converts the signal given from the microphone 171 into a digital signal and gives the converted signal to the control unit 190. Also, the audio processing unit 17 gives the audio signal to the speaker 172. The audio processing unit 17 is realized by, for example, a processor for audio processing. The microphone 171 receives an audio input and gives an audio signal corresponding to the audio input to the audio processing unit 17. The speaker 172 converts the audio signal given from the audio processing unit 17 into audio and outputs the audio to the outside of the terminal device 10.

[0033] The camera 160 is a device that receives light by a light receiving element and outputs it as a shooting signal.

[0034] The position information sensor 150 is a sensor that detects the position of the terminal device 10 and is, for example, a GPS (Global Positioning System) module. The GPS module is a receiving device used in a satellite positioning system. In the satellite positioning system, signals from at least three or four satellites are received, and based on the received signals, the current position of the terminal device 10 equipped with the GPS module is detected. The position information sensor 150 may detect the current position of the terminal device 10 from the position of the wireless base station to which the terminal device 10 is connected.

[0035] The storage unit 180 is realized by, for example, a memory 15 and a storage 16, etc., and stores data and programs used by the terminal device 10. The storage unit 180 stores, for example, farmer information 181.

[0036] The farmer information 181 includes, for example, information about farmers who use the terminal device 10. The information about farmers includes, for example, the names, addresses, contact information (phone numbers, email addresses, etc.), and field information of the personnel who make up the farmer.

[0037] The control unit 190 is realized by the processor 19 reading the program stored in the storage unit 180 and executing the instructions included in the program. The control unit 190 controls the operation of the terminal device 10. By operating according to the program, the control unit 190 functions as an operation reception unit 191, a transmission / reception unit 192, and a presentation control unit 193.

[0038] The operation reception unit 191 performs processing for receiving instructions or information input from the input device 13. Specifically, for example, the operation reception unit 191 receives instructions or information input from the touch-sensitive device 131 or the like.

[0039] Also, the operation reception unit 191 may receive the image captured by the camera 160 as an input instruction. Specifically, for example, the operation reception unit 191 receives the image signal captured by the camera 160 and accepts it as a predetermined input.

[0040] Also, the operation reception unit 191 may receive the sound collected by the microphone 171 as an input instruction. Specifically, for example, the operation reception unit 191 receives the voice signal input from the microphone 171 and converted into a digital signal by the voice processing unit 17 and accepts it as a predetermined input.

[0041] The transmission / reception unit 192 performs processing for the terminal device 10 to transmit and receive data to and from external devices such as the server 20, the mobile body 30, and the operation device 40 according to the communication protocol. Specifically, for example, the transmission / reception unit 192 transmits information about the farmer (field) or information about crop cultivation input by the user to the server 20. Also, the transmission / reception unit 192 receives information about crop growth and the like from the server 20.

[0042] The presentation control unit 193 controls the output device 14 in order to present predetermined information to the user. Specifically, for example, the presentation control unit 193 presents information for causing the user to input information regarding farmers, information regarding crop cultivation, etc. to the user. Further, the presentation control unit 193 presents information regarding the growth of crops, etc. created by the server 20 to the user.

[0043] <1.2 Functional Configuration of Server> FIG. 3 is a diagram showing an example of the functional configuration of the server 20. As shown in FIG. 3, the server 20 functions as a communication unit 201, a storage unit 202, and a control unit 203.

[0044] The communication unit 201 performs processing for the server 20 to communicate with an external device.

[0045] The storage unit 202 has, for example, a farmer information table 2021, a crop information table 2022, a leaf color information table 2023, and the like.

[0046] The farmer information table 2021 is a table that stores information regarding farmers. Details will be described later.

[0047] The crop information table 2022 is a table that stores information regarding crops cultivated by farmers. Details will be described later.

[0048] The leaf color information table 2023 is a table that stores information regarding leaf colors. Details will be described later.

[0049] The control unit 203 is realized by the processor 29 reading a program stored in the storage unit 202 and executing instructions included in the program. The control unit 203 functions as a reception control module 2031, a transmission control module 2032, an analysis module 2033, an estimation module 2034, a proposal module 2035, and a presentation control module 2036 by operating according to the program.

[0050] The reception control module 2031 controls the process in which the server 20 receives a signal from an external device according to a communication protocol. For example, the reception control module 2031 receives an image signal transmitted from the mobile body 30.

[0051] The transmission control module 2032 controls the process in which the server 20 transmits a signal to an external device according to a communication protocol. For example, the transmission control module 2032 transmits information regarding the growth of crops to the terminal device 10.

[0052] The analysis module 2033 analyzes an image captured by the mobile body 30 and calculates a vegetation index such as crops included in the image. Specifically, the analysis module 2033 calculates a vegetation index for each pixel, for example, based on the color of the pixels (picture elements) included in the image. In the present embodiment, the analysis module 2033 uses GRVI (Green-Red Vegetation Index) as the vegetation index. GRVI is an index representing the intensity of the color corresponding to the leaf color density, and is calculated as follows using the intensity Green of the green component and the intensity Red of the red component in the pixel. Note that GRVI is an example, and other vegetation indices may be used as long as they are indices representing the intensity of the color corresponding to the leaf color density. In addition to GRVI, for example, RGBVI or the like may be used as the vegetation index. GRVI=(Green-Red) / (Green+Red)

[0053] The analysis module 2033 discriminates between the GRVI calculated for the color chart included in the image and the GRVI calculated for the area where the crop is planted. Specifically, for example, the analysis module 2033 detects the color chart. The analysis module 2033 calculates the GRVI within the detected color chart. More specifically, the color chart has a frame portion such as a predetermined color or pattern. The analysis module 2033 detects the frame portion based on, for example, a predetermined color or pattern. The analysis module 2033 detects the colors within the color chart based on the pixel values of the area surrounded by the frame. The analysis module 2033 calculates the GRVI for each detected color. The analysis module 2033 determines the GRVI calculated here as the GRVI for each color included in the color chart. The analysis module 2033 determines the GRVI calculated for the area outside the area surrounded by the frame as the GRVI calculated for the area where the crop is cultivated.

[0054] The estimation module 2034 estimates the growth state of the crop. Specifically, for example, the estimation module 2034 estimates the growth state of the crop based on the GRVI for each color included in the color chart and the GRVI calculated for the area where the crop is planted. More specifically, for example, the estimation module 2034 sets the leaf color density on the color chart that is considered to have insufficient growth for the crop planted in the field. The leaf color density set here is treated as a threshold (criterion) for determining the growth state. The estimation module 2034 acquires the GRVI of the area (pixels) on the color chart corresponding to the set leaf color density. The estimation module 2034 estimates the area of pixels with a GRVI lower than the acquired GRVI as the area of interest. The area of interest represents, for example, an area where the growth state of the crop is not as good as expected.

[0055] The estimation module 2034 calculates the difference between the GRVI for each color included in the color chart and the GRVI calculated for the area where the crop is planted, and may categorize the leaf color of the area where the crop is planted into any color in the color chart. Further, the estimation module 2034 may calculate the SPAD value by inputting the number of the categorized leaf color into a predetermined mathematical formula.

[0056] The proposal module 2035 proposes a process for the estimated area. Specifically, for example, the proposal module 2035 proposes topdressing (fertilization) for the area of interest. Fertilization is carried out, for example, by spraying fertilizer with the mobile body 30. Also, for example, the proposal module 2035 may propose spraying of agricultural chemicals for the purpose of preventing pests and diseases, treating diseases, controlling pests, etc. for the area of interest.

[0057] The presentation control module 2036 presents information related to the growth of the crop, etc. to the user. Specifically, for example, the presentation control module 2036 presents the area estimated to be the area of interest to the user. Also, the presentation control module 2036 presents the categorized leaf color or the SPAD value calculated based on the leaf color to the user. The presentation control module 2036 may switch between the leaf color and the SPAD value and present them to the user according to an instruction from the user. Also, the presentation control module 2036 presents the process proposed for the area of interest to the user.

[0058] <1.3 Configuration of the Mobile Body> FIG. 4 is a block diagram showing a configuration example of the mobile body 30 shown in FIG. 1. As shown in FIG. 4, the mobile body 30 includes a communication unit 301, an input device 302, an output device 303, a drive device 304, a spraying device 305, a camera 306, a sensor 307, a storage unit 308, and a control unit 309. Each block included in the mobile body 30 is electrically connected, for example, by a bus or the like.

[0059] The communication unit 301 performs processing such as modulation and demodulation processing for the mobile object 30 to communicate with other devices. The communication unit 301 performs transmission processing on a signal generated by the control unit 309 and transmits the signal to the outside (for example, the terminal device 10, the server 20, or the operation device 40). The communication unit 301 performs reception processing on a signal received from the outside and outputs the signal to the control unit 390.

[0060] The input device 302 is a device for inputting instructions and the like by a user of the mobile object 30. The input device 302 is realized by, for example, a switch or the like.

[0061] The output device 303 is a device for presenting information to a user who operates the moving object 30. The output device 303 is realized by a display means such as an LED, a warning light, or a display. The output device 303 may also be realized by a sound generating means such as a buzzer or a speaker.

[0062] The driving device 304 is a device for moving the moving body 30. When the moving body 30 is a device that moves on the ground, the driving device 304 has, for example, a motor, tires, etc. When the moving body 30 is a device that moves in the air, the driving device 304 has, for example, a motor, propellers, etc.

[0063] The spraying device 305 is a device for spraying a substance to be sprayed. The spraying device 305 has, for example, a tank for storing the substance to be sprayed, a nozzle for spraying the substance to be sprayed, a pump for sucking up the substance stored in the tank and spraying it from the nozzle, etc. The spraying device 305 may have a sensor for measuring the amount of the substance to be sprayed in the tank, and may monitor the remaining amount of the substance to be sprayed in the tank.

[0064] The camera 306 is a device for receiving light with a light receiving element and outputting the light as an image capturing signal. The camera 306 is realized by, for example, a camera that receives visible light (RGB camera). The camera 306 may be, for example, a high-resolution camera such as a 4K camera.

[0065] The sensor 307 is a sensor for acquiring information used when the moving body 30 moves. The sensor 307 includes, for example, a six-axis gyro sensor that measures accelerations in three mutually orthogonal directions, a geomagnetic sensor that measures the direction of the moving body 30 by measuring geomagnetism, a barometric pressure sensor that measures barometric pressure, an altitude sensor that measures the altitude of the moving body 30 by using laser light or ultrasonic waves, etc., and a position information sensor that detects the position of the moving body 30. The position information sensor is, for example, a GPS (Global Positioning System) module. The GPS module is a receiving device used in a satellite positioning system. Note that the sensors provided in the moving body 30 are not limited to these. Any of these sensors may not be provided, or different sensors may be provided. For example, an angular velocity sensor for measuring the inclination of the aircraft body, a wind force sensor for measuring wind force, etc. may be provided.

[0066] The storage unit 308 is realized by, for example, a memory, a storage, etc., and stores data and programs used by the moving body 30. The storage unit 308 stores, for example, the movement method 3081 set in the server 20.

[0067] The control unit 309 is realized by a processor reading a program stored in the storage unit 308 and executing instructions included in the program. The control unit 309 controls the operation of the moving body 30. By operating according to a program, the control unit 309 functions as an operation reception unit 3091, a transmission / reception unit 3092, a movement control unit 3093, a shooting control unit 3094, and a spraying control unit 3095.

[0068] The operation reception unit 3091 performs processing for receiving an instruction or information input from the input device 302.

[0069] The transmission / reception unit 3092 performs processes for the mobile body 30 to transmit and receive data to and from external devices such as the terminal device 10, the server 20, and the operation device 40 according to a communication protocol. Specifically, for example, the transmission / reception unit 3092 transmits information regarding an image captured by the camera 306 as an image signal to the terminal device 10 or the server 20. Further, the transmission / reception unit 3092 receives information regarding a movement method transmitted from the terminal device 10 or the server 20 and stores it in the storage unit 308. Further, the transmission / reception unit 3092 receives an operation signal transmitted from the operation device 40.

[0070] The movement control unit 3093 controls the movement of the mobile body 30. Specifically, for example, the movement control unit 3093 controls the drive device 304 based on the information acquired from the sensor 307.

[0071] The shooting control unit 3094 controls shooting by the camera 306. Specifically, for example, when an instruction to start shooting is given, the shooting control unit 3094 causes the camera 306 to start shooting. When an instruction to end shooting is given, the shooting control unit 3094 ends the shooting.

[0072] The spraying control unit 3095 controls the spraying of a sprayed material by the spraying device 305. Specifically, for example, when an instruction to spray the sprayed material is given, the spraying control unit 3095 causes the spraying device 305 to spray the sprayed material. When an instruction to end spraying is given, the spraying control unit 3095 ends the spraying.

[0073] <2 Data Structure> Figs. 5 to 7 are diagrams showing the data structure of a table stored in the server 20. Note that Figs. 5 to 7 are examples and do not exclude data not described. Also, even data described in the same table may be stored in separate storage areas in the storage unit 202.

[0074] Fig. 5 is a diagram showing the data structure of the farmer information table 2021. The farmer information table 2021 shown in Fig. 5 is a table having columns such as name, address, contact information, and field information with the farmer ID as a key.

[0075] The farmer ID is an item that stores an identifier for uniquely identifying a farmer. The name is an item that stores the names of the persons who make up the farmer. The name to be stored is not limited to one person. The address is an item that stores the address of the farmer. The contact information is an item that stores the contact information of the farmer. The field information is an item that stores information about the field. Information about the field includes, for example, the address of the field, the position coordinates of the field, the altitude of the field, the area of the field, the quality of the soil in the field (e.g., nitrogen concentration, drainage, etc.). In other words, information about the field may include information about the terrain of the field.

[0076] Records in the farmer information table 2021 are created, for example, when a farmer registers as a user for the services provided by the server 20. A farmer ID is issued when creating a record. The name, address, contact information, field information, etc. are input, for example, from the farmer who wishes to register during user registration. The input of field information includes, for example, the input of the address or the specification with reference to a map.

[0077] Figure 6 is a diagram showing the data structure of the crop information table 2022. The crop information table 2022 shown in Figure 6 is a table for managing the crops planted by farmers, and is a table having columns such as crop ID, crop name, planting date, planting area, etc. with the farmer ID as the key.

[0078] The crop ID is an item that stores an identifier for uniquely identifying a crop. The crop name is an item that stores the name of the crop. The planting date is an item that stores the date when the crop was planted. The planting area is an item that stores the field where the crop was planted or the area (section) in the field.

[0079] Records in the crop information table 2022 are created, for example, when a farmer inputs that they have planted a crop. Records in the crop information table 2022 may also be created when a farmer selects a crop and inputs the planned planting date. When creating a record, the crop ID and crop name of the crop specified by the farmer are stored in the record, and the date of planting is stored as the planting date. Note that planting may also be referred to as sowing. The input of the planting area includes, for example, the input of an address or the specification with reference to a map, etc.

[0080] Figure 7 is a diagram showing the data structure of the leaf color information table 2023. The leaf color information table 2023 shown in Figure 7 is a table for managing the leaf color representing the growth state of a crop, and is a table having columns such as local ID, time period, variety, number, etc. The leaf color information table 2023 is provided, for example, for each crop corresponding to a color chart. The leaf color information table 2023 shown in Figure 7 is a table set for a color chart corresponding to paddy rice, for example.

[0081] The local ID is an item that stores an identifier for identifying the region where the farmland exists. In the item "local ID", for example, identifiers for identifying regions that can be divided by climate, etc., such as Okinawa region, southern Kyushu region, northern Kyushu region, Chugoku region, Shikoku region, Kinki region, Hokuriku region, Tokai region, Kanto-Koshin region, Tohoku region, Hokkaido region, etc., are stored. Note that the way of dividing regions is not limited to the way listed here. It may be divided more broadly or more narrowly. For example, it may be divided by prefecture.

[0082] The time period is an item that stores the time period when the growth diagnosis is carried out. The variety is an item that stores the variety of a predetermined crop. For example, when the crop is paddy rice, in the item "variety", for example, Koshihikari (registered trademark), Akitakomachi (registered trademark), Yumepirika (registered trademark), etc. are stored. The number is an item that stores the number of the leaf color density in the color chart. The item "number" represents a threshold value related to the growth state. For example, when the color of the crop's leaves is lighter than the leaf color density of the number stored in the item "number", it is determined that the growth state of the crop is not good.

[0083] Depending on the region where the field is located, the crop (variety) being cultivated, the number of days elapsed since the sowing date, etc., the leaf color density determined to be in a poor growth state varies. For example, even at the same time, the leaf color density determined to be in a poor growth state in the northern part of Kyushu is different from the leaf color density determined to be in a poor growth state in the Hokkaido region. Also, even in the same region, depending on the variety being grown, the leaf color density determined to be in a poor growth state is different. Therefore, for example, the leaf color density serving as a growth standard is preset for each region, time, variety, etc. That is, the numbers stored in the item "number" are set to different numbers for each region, time, variety, etc., for example.

[0084] <3 Operations> The operation of the server 20 when estimating the growth state of the crop based on the image captured by the moving body 30 will be described.

[0085] FIG. 8 is a schematic diagram showing an example when the moving body 30 according to the present embodiment photographs a field. In the following description, a case where the moving body 30 is a drone and the crop being planted is paddy rice will be described as an example.

[0086] The operator of the moving body 30 operates the operating device 40 to fly the moving body 30. The operator flies the moving body 30 while, for example, taking a video. The operator may, for example, give an instruction to the moving body 30 to start shooting when a predetermined position is reached. Also, the moving body 30 may fly automatically over the field and photograph the field.

[0087] The moving body 30 photographs the field from a height of about 50 m to 100 m, for example. On, for example, the ridges of the field, a color chart 50 is placed. The moving body 30 also photographs the color chart 50 placed on the ridges together with the field. In the present embodiment, the color chart 50 is also photographed together with the field. The moving body 30 flies so that the color chart 50 is included in the angle of view, for example, and photographs the field. If the color chart 50 cannot be included in the angle of view anyway, the color chart 50 may be moved.

[0088] The color chart 50 has a plurality of regions 51 to 57 with different shades of green. The colors of the regions 51 to 57 correspond to the leaf color density of paddy rice. The color chart 50 has, for example, a frame portion 58 in which a predetermined pattern, design, color, or a combination thereof is expressed. In FIG. 8, the frame portion 58 is set to surround the color chart, but it does not necessarily have to surround it. For example, the frame portion 58 may be placed at the four corners of the color chart 50. Also, the pattern of the frame portion 58 may be, for example, a QR code (registered trademark).

[0089] FIG. 9 is an example of a flowchart showing the operation when the server 20 estimates the growth state of a crop.

[0090] In step S11, the server 20 receives an image signal transmitted from the mobile body 30.

[0091] In step S12, the server 20 analyzes the image based on the received image signal. Specifically, for example, the control unit 203 of the server 20 detects the frame portion 58 included in the image by the analysis module 2033. The analysis module 2033 detects the color in the color chart based on the pixel values in the region surrounded by the frame portion 58. The analysis module 2033 calculates the GRVI for each detected color. The GRVI calculated for the pixels in the region surrounded by the frame portion 58 is the GRVI of each color included in the color chart 50. The analysis module 2033 calculates the GRVI for the pixels in the region not surrounded by the frame portion 58.

[0092] The analysis module 2033 may determine the selection of data based on the calculated GRVI. For example, the aerial image includes not only vegetation but also buildings, soil, and roads. For example, for buildings and roads, the probability that the GRVI value does not reach a predetermined value is high. The analysis module 2033 regards the information of pixels whose GRVI value does not reach the predetermined value as no data. In this embodiment, the predetermined value is, for example, 0.1. That is, the analysis module 2033 regards the information of pixels with a GRVI value less than 0.1 as no data. By regarding the information of pixels whose GRVI value does not reach the predetermined value as no data, the accuracy of the processing in the estimation module 2034 is improved. Also, the processing load in the estimation module 2034 is reduced. Also, it becomes possible to exclude areas not related to vegetation, such as buildings and roads, from the target of topdressing.

[0093] In step S13, the server 20 estimates the growth state of the crops (paddy rice) cultivated in the field. Specifically, for example, the server 20 estimates the growth state of the crops based on the GRVI calculated for the color chart and the GRVI calculated for the area where the crops are cultivated by the estimation module 2034. More specifically, for example, the estimation module 2034 reads out the leaf color density considered to be insufficient growth from the leaf color information table 2023 based on the region, time, and variety of paddy rice that is the target of the growth diagnosis. The estimation module 2034 sets the leaf color density at this time to "4", for example. The leaf color density "4" on the color chart 50 represents the leaf color density in the region 54, for example.

[0094] The estimation module 2034 extracts the area of pixels with a GRVI lower than the GRVI calculated for the area 54. The estimation module 2034 estimates that the extracted area is the area of interest. According to FIG. 8, the estimation module 2034 sets the area R1 of pixels with a GRVI lower than the GRVI calculated for the area 54 as the area of interest.

[0095] The estimation module 2034 calculates the difference between the GRVI for each color included in the color chart and the GRVI calculated for the area where the crop is planted, and categorizes the leaf color of the area where the crop is planted into any one of the colors in the color chart. Further, the estimation module 2034 calculates the SPAD value by inputting the number of the categorized leaf color into a predetermined mathematical formula.

[0096] In step S14, the server 20 determines the content of the process to be performed on the estimated target area. Specifically, for example, the control unit 203 determines, by the proposal module 2035, that top dressing should be performed on the target area.

[0097] In step S15, the server 20 presents the analysis result and the proposed content to the user. Specifically, the presentation control module 2036 transmits, by the transmission control module 2032, information regarding the target area to the terminal device 10. Further, the presentation control module 2036 transmits, by the transmission control module 2032, the categorized leaf color or the SPAD value calculated based on the leaf color to the terminal device 10. Further, the presentation control module 2036 transmits information regarding the proposed content to the terminal device 10.

[0098] When the terminal device 10 receives information regarding the target area, it causes the display 141 to display the target area. Further, when the terminal device 10 receives information regarding the proposed content, it causes the display 141 to display the proposed content.

[0099] FIG. 10 is a schematic diagram showing an example of the display on the display 141. FIG. 10 shows an example of a field where paddy rice is cultivated. The presentation control unit 193 displays, in the field, the area determined as the target area in a distinguishable manner for the user. For example, the presentation control unit 193 surrounds the target area with an indicator 1411. Further, the presentation control unit 193 displays information regarding the proposed content in association with the target area. For example, the presentation control unit 193 displays a text box 1412 in which the proposed content is described for the target area surrounded by the indicator 1411.

[0100] The user checks the display 141, for example, and determines whether top dressing is required for the area of interest. If it is determined that top dressing is required, the user operates the mobile body 30, for example, and performs top dressing on the area of interest.

[0101] The top dressing may be automatically performed by an operation from the server 20. For example, the presentation control unit 193 displays a screen for the user to input that they accept the proposed content. When the proposed content is accepted, the presentation control unit 193 displays a screen for adjusting the schedule for performing the top dressing. The user inputs information regarding the user and information regarding the schedule on the screen. When the information is received, the transmission / reception unit 192 transmits the received information to the server 20.

[0102] The server 20 stores the received information in a schedule management table (not shown). The server 20 calculates a flight path based on information regarding the field associated with the user. The flight path includes, for example, a path from the movement start position of the mobile body 30 to the area of interest, a path that enables efficient spraying of the spraying material in the area of interest, etc. Note that the flight path may be referred to as a movement path. When the date managed in the schedule management table arrives, the server 20 transmits information regarding the flight path to the terminal device 10 or the mobile body 30. The mobile body 30 flies based on the information regarding the flight path and sprays fertilizer.

[0103] In FIG. 9, for example, the case where the GRVI for each pixel calculated by the analysis module 2033 in step S12 is used in the estimation after step S13 was described. However, the analysis module 2033 may calculate the GRVI for each grid based on the GRVI for each pixel. Specifically, for example, the field is divided into grid boxes of a predetermined size. The predetermined size is, for example, a size of 4 to 5 m on each side. The analysis module 2033 averages the GRVI for each pixel in grid units to calculate the GRVI for each grid.

[0104] As described above, in the above embodiment, the reception control module 2031 acquires an image of a field photographed by an RGB camera mounted on the aircraft (mobile object) 30. The reception control module 2031 acquires an image of a color chart having a correspondence relationship with the analysis content, which is photographed by the RGB camera in the same environment as the field. The analysis module 2033 calculates a vegetation index based on the colors included in the image of the field and the colors included in the image of the color chart. The estimation module 2034 estimates the vegetation in the field from the vegetation index calculated based on the colors of the color chart and the vegetation index calculated based on the colors of the field. As a result, it becomes possible to accurately grasp the situation of the crops planted in the field by photographing from above using an RGB camera. In addition, it becomes possible to accurately evaluate the uneven growth in the field.

[0105] In the conventional growth diagnosis using NDVI, it is necessary to use a multispectral camera. In addition, multispectral cameras are expensive and difficult to handle. According to this embodiment, since growth diagnosis can be performed using an RGB camera, it is possible to suppress the cost of the device. In addition, the need to pay attention to the operation of the device is obtained.

[0106] In addition, in the conventional growth diagnosis using NDVI, sufficient accuracy cannot be obtained unless the relationship between NDVI and the growth amount of the crop is accumulated for several years for each field where the crop is grown. Therefore, a predetermined period is required until sufficient accuracy is obtained even if an attempt is made to introduce it. According to this embodiment, since the relationship between the leaf color density and the growth state is already set, sufficient accuracy can be expected immediately after the introduction.

[0107] In this embodiment, since the color chart is included in the same image as the field, the environment at the time of photographing is reflected in the color chart. For example, it becomes possible to match the states such as the solar radiation amount and the solar radiation direction between the field and the color chart. Therefore, it becomes possible to compare the leaf color density in the color chart and the leaf color density of the crops cultivated in the field under the same conditions.

[0108] Therefore, according to the system according to this embodiment, while suppressing the cost of the device, the crop in the field can be easily checked using the mobile body 30.

[0109] Also, in the above embodiment, the color chart includes a plurality of colors corresponding to the leaf color density. Thereby, the server 20 can grasp the growth state step by step.

[0110] Also, in the above embodiment, the plurality of colors corresponding to the leaf color density correspond to the leaf color of paddy rice. Thereby, the server 20 can diagnose the growth state of paddy rice with high accuracy.

[0111] Also, in the above embodiment, the estimation module 2034 estimates the vegetation in the field based on the GRVI (Green-Red Vegetation Index). Thereby, the server 20 can compare the leaf color density of the color chart with the leaf color density of the crop in the field with high accuracy.

[0112] Also, in the above embodiment, the estimation module 2034 estimates the area of the field where the vegetation index calculated is lower than the vegetation index calculated based on a predetermined color in the color chart as the attention area. Thereby, the server 20 can diagnose the growth state of the crop in the field using the color chart.

[0113] Also, in the above embodiment, the estimation module 2034 uses, as a reference, any one of the colors included in the color chart, and uses the vegetation index based on the color for the estimation of the attention area. The reference color varies depending on the variety, region, and diagnosis time. Thereby, since the server 20 can perform a diagnosis suitable for the variety, region, diagnosis time, etc., the accuracy of the growth diagnosis is improved.

[0114] In addition, in the above-described embodiment, the proposal module 2035 proposes topdressing for the area of interest. As a result, based on the results of the growth diagnosis, it becomes possible to fertilize efficiently. In addition, since it becomes possible to fertilize pinpoint, it becomes possible to improve uneven growth. In addition, since the moving body 30 can be automatically moved to the area where fertilization is required, it becomes possible to locally and fully automatically spray fertilizer.

[0115] In addition, in the above-described embodiment, the RGB camera mounted on the moving body 30 simultaneously photographs the farm field and the color chart. As a result, the farm field and the color chart are photographed in the same environment. For this reason, it becomes possible to accurately grasp the situation of the crops planted in the farm field by photographing from above using the RGB camera.

[0116] In addition, in the above-described embodiment, the image is an image obtained by photographing the farm field from an altitude of about 50 m to 100 m using the RGB camera mounted on the moving body 30. The color chart has a size of about several meters in at least one direction. As a result, the moving body 30 can photograph the farm field within the shooting range. In addition, since the color chart placed in the farm field only needs to have a size of about several meters in at least one direction, the labor for photographing together with the farm field is small.

[0117] In addition, in the above-described embodiment, after the color chart is photographed by the RGB camera mounted on the moving body 30, the farm field is photographed. As a result, the color chart is photographed immediately before the aerial photography, and then the farm field is photographed. Therefore, the farm field and the color chart are photographed in the same environment. For this reason, it becomes possible to accurately grasp the situation of the crops planted in the farm field by photographing from above using the RGB camera.

[0118] <Modification Example> In the above embodiment, the case where the analysis module 2033 of the server 20 analyzes the image captured by the moving body 30 has been described. However, the analysis of the image is not limited to being performed by the server 20. The control unit 309 of the moving body 30 may analyze the image. In this case, the transmission / reception unit 3092 transmits the analysis result to the terminal device 10 or the server 20.

[0119] Also, in the above embodiment, the case where the server 20 estimates the growth state of the crops cultivated in the field and determines the proposed content corresponding to the estimated growth state has been described. However, the process of estimating the growth state of the crops cultivated in the field and determining the proposed content corresponding to the estimated growth state may be performed outside the server 20. For example, the terminal device 10 may estimate the growth state of the crops cultivated in the field and determine the proposed content corresponding to the estimated growth state. In this case, the control unit 190 of the terminal device 10 will have functions corresponding to, for example, the analysis module 2033, the estimation module 2034, and the proposal module 2035.

[0120] Also, in the above embodiment, the case where the color chart is included in the image has been described as an example. However, it is not necessarily required to include the color chart in the image. For example, at the timing when the growth diagnosis is started, an image including the field and the color chart may be captured, and the color chart obtained at this time may be used in subsequent growth diagnoses. Or, for example, at the timing when the growth diagnosis is started, only the color chart may be captured first, and the color chart obtained at this time may be used in subsequent growth diagnoses. That is, for example, at the timing when the growth diagnosis is started, only the color chart is captured, and immediately thereafter, for example, within a few minutes, the field is taken an aerial photograph. In this way, by capturing only the color chart in the stage before the aerial photograph, it is possible to suppress the size of the color chart.

[0121] Also, for example, an image of a photographed color chart may be used for a predetermined period, and when the predetermined period has passed, a new field and color chart, or the color chart may be photographed again. The predetermined period is preferably a time when the surrounding environment does not change significantly. For example, a time of about several tens of minutes is assumed. Also, for example, a sunlight sensor may be arranged on the moving body 30 or at a predetermined position, and based on the detection results of the solar radiation amount and the solar radiation direction, a new field and color chart may be photographed. When it is time to take a photograph including the color chart, the presentation control unit 193 causes the display 141 to display a proposal to take a photograph of the color chart, such as "Please take a photograph of the color chart".

[0122] In the above embodiment, the case where the analysis module 2033 automatically detects the color chart and automatically detects each color on the color chart has been described. However, the detection of the color chart and each color on the color chart is not limited to being automatic. The analysis module 2033 may manually receive the designation of the color on the color chart from the user.

[0123] For example, when the field and the color chart are photographed together by aerial photography, the user refers to the image obtained by aerial photography and designates the color chart included in the image. The user designates each color (for example, 7 - level leaf color) on the designated color chart.

[0124] Also, in the above embodiment,

[0125] <4 Basic Hardware Configuration of Computer> FIG. 11 is a block diagram showing the basic hardware configuration of a computer 90. The computer 90 includes at least a processor 91, a main storage device 92, an auxiliary storage device 93, and a communication IF 99 (Interface). These are electrically connected to each other by a bus.

[0126] The processor 91 is hardware for executing an instruction set described in a program. The processor 91 is composed of an arithmetic unit, registers, peripheral circuits, and the like.

[0127] The main memory device 92 is for temporarily storing a program and data processed by the program and the like. For example, it is a volatile memory such as DRAM (Dynamic Random Access Memory).

[0128] The auxiliary storage device 93 is a storage device for storing data and programs. For example, it is a flash memory, HDD (Hard Disc Drive), magneto-optical disk, CD-ROM, DVD-ROM, semiconductor memory, and the like.

[0129] The communication IF 99 is an interface for inputting and outputting signals for communicating with other computers via a network using a wired or wireless communication standard. The network is composed of various mobile communication systems constructed by the Internet, LAN, wireless base stations, and the like. For example, the network includes 3G, 4G, 5G mobile communication systems, LTE (Long Term Evolution), a wireless network (e.g., Wi-Fi (registered trademark)) that can be connected to the Internet by a predetermined access point, and the like. When connecting wirelessly, communication protocols such as Z-Wave (registered trademark), ZigBee (registered trademark), Bluetooth (registered trademark), and the like are included. When connecting wired, the network also includes those directly connected by a USB (Universal Serial Bus) cable or the like.

[0130] Note that all or part of each hardware configuration can be distributed and provided to a plurality of computers 90, and the computers 90 can be virtually realized by connecting them to each other via a network. In this way, the computer 90 is a concept that includes not only a single housing or a computer 90 housed in a case but also a virtualized computer system.

[0131] <Basic Functional Configuration of Computer 90> The functional configuration of the computer realized by the basic hardware configuration of the computer 90 shown in FIG. 11 will be described. The computer includes at least functional units of a control unit, a storage unit, and a communication unit.

[0132] Note that the functional units included in the computer 90 can also be realized by distributing all or part of each functional unit to a plurality of computers 90 interconnected by a network. The computer 90 is a concept that includes not only a single computer 90 but also a virtualized computer system.

[0133] The control unit is realized by the processor 91 reading out various programs stored in the auxiliary storage device 93 and expanding them in the main storage device 92, and executing processing according to the programs. The control unit can realize a functional unit that performs various information processes according to the type of program. Thereby, the computer is realized as an information processing device that performs information processing.

[0134] The storage unit is realized by the main storage device 92 and the auxiliary storage device 93. The storage unit stores data, various programs, and various databases. Further, the processor 91 can secure a storage area corresponding to the storage unit in the main storage device 92 or the auxiliary storage device 93 according to the program. Also, the control unit can cause the processor 91 to execute addition, update, and deletion processing of the data stored in the storage unit according to various programs.

[0135] The database refers to a relational database and is for managing a data set called a table in a tabular format structurally defined by rows and columns in association with each other. In a database, a table is called a table, a column of a table is called a column, and a row of a table is called a record. In a relational database, the relationship between tables can be set and associated. Generally, each table is set with a column that serves as a key for uniquely identifying records, but setting a key for a column is not mandatory. The control unit can cause the processor 91 to add, delete, or update records in a specific table stored in the storage unit according to various programs.

[0136] The communication unit is realized by the communication IF 99. The communication unit realizes the function of communicating with other computers 90 via a 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 91 to execute information processing on the received information according to various programs. Also, the communication unit can transmit the information output from the control unit to other computers 90.

[0137] As described above, some embodiments of the present disclosure have been explained. However, these embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are to be included in the scope and gist of the invention, as well as in the invention described in the claims and the equivalent scope thereof.

[0138] <Supplementary Note> The matters described in each of the above embodiments are appended below. (Supplementary Note 1) A program for causing a computer including a processor and a memory to execute, the program causing the processor to perform steps of: acquiring an image of a field photographed by an RGB camera mounted on an aircraft; acquiring an image of a color chart having a correspondence relationship with analysis content, photographed by the RGB camera in the same environment as the field; calculating a vegetation index based on the colors included in the image of the field and the colors included in the image of the color chart; and estimating the vegetation in the field from the vegetation index calculated based on the colors of the color chart and the vegetation index calculated based on the colors of the field. (Supplementary Note 2) The color chart is a program described in (Appendix 1) that includes a plurality of colors corresponding to leaf color density. (Appendix 3) The plurality of colors corresponding to leaf color density is a program described in (Appendix 2) that corresponds to the leaf color of rice. (Appendix 4) In the step of estimating, it is a program described in any one of (Appendix 1) to (Appendix 3) that estimates the vegetation in the field based on GRVI (Green-Red Vegetation Index). (Appendix 5) In the step of estimating, it is a program described in any one of (Appendix 1) to (Appendix 4) that estimates the area of the field where a vegetation index lower than the vegetation index calculated based on a predetermined color in the color chart is calculated as the attention area. (Appendix 6) In the step of estimating, using any color included in the color chart as a reference, the vegetation index based on the color is used for estimating the attention area, and the reference color varies depending on the variety, region, and diagnosis time. It is a program described in (Appendix 5). (Appendix 7) It is a program described in (Appendix 5) that causes the processor to execute the step of proposing fertilization for the attention area. (Appendix 8) It is a program described in any one of (Appendix 1) to (Appendix 7) that the field and the color chart are photographed simultaneously. (Appendix 9) The images of the field and the color chart are images obtained by photographing the field from an altitude of about 50m to 100m with an RGB camera mounted on an aircraft, and the color chart is at least several meters in size in at least one direction. It is a program described in (Appendix 8). (Appendix 10) It is a program described in any one of (Appendix 1) to (Appendix 7) that the field is photographed after the color chart is photographed. (Appendix 11) A method to be executed on a computer including a processor and a memory, the method comprising: a step of the processor obtaining an image of a field captured by an RGB camera mounted on an aircraft; a step of obtaining an image of a color chart having a correspondence relationship with an analysis content, the color chart being captured by the RGB camera in the same environment as the field; a step of calculating a vegetation index based on the colors included in the image of the field and the colors included in the image of the color chart; and a step of estimating the vegetation in the field from the vegetation index calculated based on the colors of the color chart and the vegetation index calculated based on the colors of the field. (Appendix 12) An information processing apparatus including a control unit and a storage unit, the control unit performing: a step of obtaining an image of a field captured by an RGB camera mounted on an aircraft; a step of obtaining an image of a color chart having a correspondence relationship with an analysis content, the color chart being captured by the RGB camera in the same environment as the field; a step of calculating a vegetation index based on the colors included in the image of the field and the colors included in the image of the color chart; and a step of estimating the vegetation in the field from the vegetation index calculated based on the colors of the color chart and the vegetation index calculated based on the colors of the field An information processing apparatus that performs the above. (Appendix 13) A system comprising: means for obtaining an image of a field captured by an RGB camera mounted on an aircraft; means for obtaining an image of a color chart having a correspondence relationship with an analysis content, the color chart being captured by the RGB camera in the same environment as the field; means for calculating a vegetation index based on the colors included in the image of the field and the colors included in the image of the color chart; and means for estimating the vegetation in the field from the vegetation index calculated based on the colors of the color chart and the vegetation index calculated based on the colors of the field.

Explanation of Signs

[0139] 1…System 10…Terminal device 12…Communication IF 120…Communication unit 13…Input device 131…Touch-sensitive device 14... Output device 141... Display 15... Memory 150... Position information sensor 16... Storage 160... Camera 17... Audio processing unit 171... Microphone 172... Speaker 180... Memory unit 19... Processor 190... Control unit 20... Server

Claims

1. A program for causing a computer having a processor and a memory to execute the program, the program causing the processor to: acquiring an image of a farm field taken by an RGB camera mounted on an aircraft; acquiring an image of a color chart having a correspondence relationship with an analysis content, the image being captured by the RGB camera under the same environment as the farm field; calculating a vegetation index based on the colors contained in the image of the field and the colors contained in the image of the color chart; estimating vegetation in the field from a vegetation index calculated based on the color of the color chart and a vegetation index calculated based on the color of the field; A program that executes the following.

2. The program according to claim 1 , wherein the color chart includes a plurality of colors corresponding to leaf color intensities.

3. 3. The program according to claim 2, wherein the plurality of colors corresponding to the leaf color densities correspond to leaf colors of paddy rice.

4. 2. The program according to claim 1, wherein in the estimating step, the vegetation in the field is estimated based on a Green-Red Vegetation Index (GRVI).

5. 2. The program according to claim 1, wherein in the estimating step, an area of ​​the field in which a vegetation index calculated is lower than a vegetation index calculated based on a predetermined color in the color chart is estimated to be a region of interest.

6. 6. The program according to claim 5, wherein in the estimating step, one of the colors included in the color chart is used as a reference, and a vegetation index based on that color is used to estimate the area of ​​interest, and the reference color varies depending on the variety, region, and time of diagnosis.

7. The program according to claim 5 , which causes the processor to execute a step of suggesting fertilization for the area of ​​interest.

8. 2. The program according to claim 1, wherein the field and the color chart are photographed simultaneously.

9. the image of the field and the color chart is an image of the field photographed from the sky at a height of about 50 m to 100 m by the RGB camera mounted on the aircraft, 9. The program according to claim 8, wherein the color chart has a size of about several meters in at least one direction.

10. 2. The program according to claim 1, wherein the farm field is photographed after the color chart is photographed.

11. 1. A computer-implemented method comprising a processor and a memory, the processor comprising: acquiring an image of a farm field taken by an RGB camera mounted on an aircraft; acquiring an image of a color chart having a correspondence relationship with an analysis content, the image being captured by the RGB camera under the same environment as the farm field; calculating a vegetation index based on the colors contained in the image of the field and the colors contained in the image of the color chart; estimating vegetation in the field from a vegetation index calculated based on the color of the color chart and a vegetation index calculated based on the color of the field; How to do it.

12. An information processing device including a control unit and a storage unit, acquiring an image of a farm field taken by an RGB camera mounted on an aircraft; acquiring an image of a color chart having a correspondence relationship with an analysis content, the image being captured by the RGB camera under the same environment as the farm field; calculating a vegetation index based on the colors contained in the image of the field and the colors contained in the image of the color chart; estimating vegetation in the field from a vegetation index calculated based on the color of the color chart and a vegetation index calculated based on the color of the field; An information processing device that executes the above.

13. A means for acquiring an image of a farm field by an RGB camera mounted on an aircraft; A means for acquiring an image of a color chart having a correspondence relationship with an analysis content, the image being captured by the RGB camera under the same environment as the farm field; a means for calculating a vegetation index based on the colors contained in the image of the farm field and the colors contained in the image of the color chart; a means for estimating vegetation in the field from a vegetation index calculated based on the color of the color chart and a vegetation index calculated based on the color of the field; A system comprising:

Images