JP7514536B2 - Damage estimation device and damage estimation system - Google Patents

Description

The present invention relates to a feeding damage estimation device and a feeding damage estimation system.

Damage to crops caused by mollusks such as apple snails has become a problem. Since low temperatures in winter are a major cause of death for apple snails, it has been proposed to predict the number of apple snails from the average winter temperature (e.g., Non-Patent Document 1). A system has also been proposed that processes image information taken from the air of farm fields to provide information on the growth status or disease status of agricultural crops in response to requests from farmers (e.g., Patent Document 1). It is also known to create a digital elevation model from images taken from the air (e.g., Non-Patent Document 2).

JP 2003-143959 A

Akira Kondo et al., "Prediction of apple snail abundance based on average winter temperatures," Research Report of the Agricultural Experiment Station, Okayama Prefectural Agricultural Research Center, Vol. 27, 2009, pp. 1-3 "How to take aerial photographs using drones and analyze the images - for planning operations and understanding resource amounts," Forest Research Institute, Toyama Prefectural Agriculture, Forestry and Fisheries Research Center, January 6, 2020

To reduce damage to crops caused by shellfish, it is desirable to accurately estimate the occurrence of such damage.

The present invention was developed in consideration of the above problems, and aims to accurately estimate the occurrence of damage caused by shellfish.

The present invention is a predation damage estimation device that includes a depression information acquisition unit that acquires information regarding depressions in the paddy field from an image of the paddy field captured from the sky , including the amount of depression in the depression ; a weather information acquisition unit that acquires weather information; a water depth estimation unit that estimates the water depth in the depression based on rainfall information included in the weather information or the water depth actually measured at a specified position in the paddy field and the amount of depression in the depression; and a predation damage estimation unit that estimates damage caused by shellfish based on the water depth in the depression and temperature information included in the weather information.

The present invention is a predation damage estimation system that includes an aircraft and a damage estimation device, the damage estimation device having a depression information acquisition unit that acquires information regarding depressions in the paddy field from an image of the paddy field captured by the aircraft, the depression information acquisition unit that acquires meteorological information, a water depth estimation unit that estimates the water depth in the depression based on rainfall information included in the weather information or the water depth actually measured at a specified position in the paddy field and the depression volume of the depression , and a damage estimation unit that estimates damage caused by shellfish based on the water depth in the depression and temperature information included in the weather information.

The present invention makes it possible to accurately estimate the occurrence of damage caused by shellfish.

FIG. 1 is a system configuration diagram of a damage estimation system according to a first embodiment. FIG. 2 is a diagram illustrating an example of an aircraft. FIG. 3 is a functional configuration diagram of the feeding damage estimation device according to the first embodiment. FIG. 4 is a diagram illustrating an example of information about depressions acquired by the depression information acquisition unit. FIG. 5 is a diagram showing an example of damage estimation by the damage estimation unit. FIG. 6 is a flowchart showing an example of a method for estimating damage according to the first embodiment. FIG. 7 is a hardware configuration diagram of the damage estimation device. FIG. 8 is a functional configuration diagram of the damage estimation device according to the second embodiment. FIG. 9 is a diagram showing an example of shellfish history information. FIG. 10 is a diagram illustrating an example of stock shortage history information. FIG. 11 is a flowchart showing an example of a method for estimating damage according to the second embodiment.

First Embodiment
FIG. 1 is a system configuration diagram of a feeding damage estimation system 100 according to a first embodiment. As shown in FIG. 1, the feeding damage estimation system 100 includes a feeding damage estimation device 10 and an aircraft 50. The feeding damage estimation device 10 is a computer such as a personal computer (PC), a server, a smartphone, or a tablet terminal. The aircraft 50 is, for example, a drone equipped with rotors (propellers). Note that the aircraft 50 may be a fixed-wing aircraft without rotors.

Figure 2 is a diagram showing an example of an aircraft 50. As shown in Figure 2, the aircraft 50 comprises a main body 52, a rotor (propeller) 54 attached to the main body 52, and an imaging unit 56 attached to the main body 52 and capable of imaging the ground. The imaging unit 56 is a camera that images the ground at a predetermined angle of view, such as a CCD camera. The aircraft 50 may be one in which flight is controlled by a pilot operating the pilot, or one in which the aircraft flies automatically according to a flight route stored in advance.

As shown in FIG. 1, the damage estimation device 10 and the flying object 50 are connected via a network 60, and image data captured by the imaging unit 56 is transmitted from the flying object 50 to the damage estimation device 10. The network 60 is not particularly limited, and the Internet or a wireless LAN (Local Area Network) may be used as the network 60. Furthermore, the image data captured by the imaging unit 56 may be wirelessly transmitted from the flying object 50 to the damage estimation device 10 without using the network 60. The standard of wireless transmission is also not particularly limited, and the flying object 50 may transmit the captured image data to the damage estimation device 10 using Wi-Fi (registered trademark) or the like.

The damage estimation device 10 also obtains weather information from a server 62. The server 62 is, for example, a computer managed by the Japan Meteorological Agency, and is a server that provides past, present, and future weather information.

Figure 3 is a functional configuration diagram of the damage estimation device 10 in the first embodiment. As shown in Figure 3, the damage estimation device 10 has a communication unit 12, an input unit 14, a display unit 16, a memory unit 18, and a control unit 20.

The communication unit 12 is an interface that connects the damage estimation device 10 to a network 60 (see FIG. 1) and communicates wirelessly with the flying object 50 when image data is wirelessly transmitted from the flying object 50.

The input unit 14 is a device such as a keyboard or touch panel that allows the operator to input various information into the damage estimation device 10.

The display unit 16 is a display device such as a liquid crystal display that displays various information such as images captured by the flying object 50 and information predicting damage caused by shellfish.

The memory unit 18 stores various information, such as information about depressions, information about estimated damage caused by shellfish, and information about areas where damage caused by shellfish has occurred in the past.

The control unit 20 is a processing unit that controls each part of the feeding damage estimation device 10. As an example, the control unit 20 has an image acquisition unit 22, a depression information acquisition unit 24, a meteorological information acquisition unit 26, a water depth estimation unit 28, an overwintering number estimation unit 30, and a feeding damage estimation unit 32.

The captured image acquisition unit 22 is a processing unit that acquires captured images of a paddy field captured by the imaging unit 56 of the aircraft 50. There is no particular limitation on the crops cultivated in the paddy field, but the following description will be given of the case where the crop is paddy rice.

The depression information acquisition unit 24 is a processing unit that acquires information about depressions in the paddy field from the captured images of the paddy field acquired by the captured image acquisition unit 22. For example, the depression information acquisition unit 24 creates a digital elevation model using multiple captured images of the paddy field captured by the imaging unit 56 of the aircraft 50, and acquires information about the depressions from this digital elevation model. The information about the depressions is, for example, the position information of the depressions and the depression volume of the depressions.

4(a) and 4(b) are diagrams showing an example of information about depressions acquired by the depression information acquisition unit 24. As shown in FIG. 4(a), the depression information acquisition unit 24 subdivides the paddy field 70 into predetermined sizes (e.g., several cm to several tens of cm), acquires position information of depressions A, B, C, D, E, etc. that are recessed by a predetermined value (e.g., 1 cm) or more from the average height of the paddy field 70, creates a map, and stores it in the memory unit 18. The depression information acquisition unit 24 may display the created map on the display unit 16. In FIG. 4(a), depressions with a depth of 1 cm or more and less than 2 cm from the average height are illustrated with coarse hatching, depressions with a depth of 2 cm or more and less than 3 cm are illustrated with medium-coarse hatching, and depressions with a depth of 3 cm or more are illustrated with fine hatching. Also, as shown in FIG. 4(b), the depression information acquisition unit 24 may create depression information, which is a database of the location information (latitude and longitude, etc.) and depression amount (maximum depression amount, depression amount range, etc.) of depressions A, B, C, D, E, etc., and store this in the memory unit 18.

The weather information acquisition unit 26 is a processing unit that acquires weather information provided by the server 62. As weather information, for example, precipitation information and temperature information are acquired.

The water depth estimation unit 28 is a processing unit that estimates the water depth in depressions A, B, C, D, E, etc. acquired by the depression information acquisition unit 24. In this first embodiment, the water depth estimation unit 28 estimates the predicted water depth in depressions A, B, C, D, E, etc. from the depression volume of depressions A, B, C, D, E, etc. and rainfall information from the present to several days into the future acquired by the weather information acquisition unit 26.

The overwintering number estimation unit 30 is a processing unit that estimates the number of shellfish that overwintered in each paddy field 70 from the overwintering survival rate of shellfish such as apple snails calculated from the average temperature in the winter of the previous year (for example, December to February) and the number of shellfish such as apple snails that occurred in the paddy field 70 in the previous year. Since the drop in temperature in winter is a major cause of death for shellfish such as apple snails and it is known that there is a correlation between the average temperature in winter and the overwintering survival rate, this correlation is used to estimate the number of shellfish that overwintered. The average temperature in the winter of the previous year may be obtained from the server 62, or the daily temperatures in winter or the average temperature calculated from these temperatures may be stored in the memory unit 18 and obtained from this memory unit 18. The number of shellfish that occurred in the paddy field 70 in the previous year is stored in advance in the memory unit 18 and obtained from this memory unit 18. The number of shellfish that have emerged may be obtained by a computer performing image analysis on images of the rice paddy field 70 captured by the aircraft 50, or it may be an empirical number or a number inferred from the distribution of egg masses or the area of past damage, or the number that an operator estimates by actually looking at the rice paddy field 70 may be input.

The feeding damage estimation unit 32 is a processing unit that estimates feeding damage by shellfish based on the water depth in depressions A, B, C, D, E, etc. estimated by the water depth estimation unit 28 and the temperature information acquired by the weather information acquisition unit 26. In this first embodiment, the feeding damage estimation unit 32 estimates feeding damage by shellfish based on the predicted water depth in depressions A, B, C, D, E, etc. and the temperature information from the present to several days later. Shellfish such as apple snails start to eat rice when the depth of the water in the rice field 70 is, for example, 4 cm or more. Also, shellfish such as apple snails start to eat rice when the temperature of the water in the rice field 70 rises and the temperature is, for example, 15° C. or more, and they start to eat actively when the temperature is, for example, 25° C. or more. On the other hand, when the water temperature is, for example, 35° C. or more, shellfish such as apple snails become sluggish and do not eat much rice.

For this reason, the damage estimation unit 32 estimates damage caused by shellfish based on the water depth in depressions A, B, C, D, E, etc. estimated by the water depth estimation unit 28 and the temperature information acquired by the weather information acquisition unit 26. This allows for good estimation of damage caused by shellfish in depressions where the water is deep and damage is likely to occur. Figures 5(a) and 5(b) are diagrams showing an example of damage estimation by the damage estimation unit 32. As shown in Figure 5(a), when there is a depression where the temperature of the paddy field 70 is equal to or higher than a predetermined temperature based on the temperature information acquired by the weather information acquisition unit 26 and the water depth estimated by the water depth estimation unit 28 is equal to or higher than a predetermined value, the damage estimation unit 32 acquires position information of the depression as a damage prediction area α, β, etc. where damage is predicted to occur, creates a map, and stores it in the memory unit 18. The damage estimation unit 32 displays the created map on the display unit 16. Furthermore, as shown in FIG. 5(b), the damage estimation unit 32 may create damage estimation information, which is a database showing the location information (latitude, longitude, etc.) of the estimated damage prediction areas α, β, etc., and store this in the memory unit 18.

As described above, when the air temperature rises and the water temperature in the paddy field 70 rises to a certain level, the shellfish will actively eat the rice. Therefore, the feeding damage estimation unit 32 may refer to the air temperature information acquired by the weather information acquisition unit 26 to estimate the extent of damage caused by the shellfish (feeding damage risk) and display the estimation result on the map of FIG. 5(a). For example, when the air temperature in the paddy field 70 is equal to or higher than the first predetermined temperature and lower than the second predetermined temperature, the shellfish will feed on the rice and the feeding damage risk is estimated to be medium, when the air temperature is equal to or higher than the second predetermined temperature and lower than the third predetermined temperature, the shellfish will actively feed on the rice and the feeding damage risk is estimated to be high, and when the air temperature is equal to or higher than the third predetermined temperature, the shellfish will slow down and the feeding damage risk is estimated to be low, and the estimation result may be displayed on the map of FIG. 5(a). Note that the feeding damage risk is not limited to three stages, but may be two stages or four stages or more.

Furthermore, the greater the number of shellfish that overwinter, the greater the damage caused by shellfish predation. Therefore, the predation damage estimation unit 32 may estimate the degree of predation risk by referring to the number of shellfish overwintering estimated by the overwintering number estimation unit 30. For example, the predation damage estimation unit 32 may estimate that the degree of predation risk is low when the number of shellfish overwintering is less than a first predetermined number, that the degree of predation risk is medium when the number of shellfish overwintering is equal to or greater than the first predetermined number and less than a second predetermined number, and that the degree of predation risk is high when the number of shellfish overwintering is equal to or greater than the second predetermined number. Note that the degree of predation risk is not limited to three levels, and may be two or four or more levels.

The feeding damage estimation unit 32 may also estimate the feeding damage risk by referring to information about paddy fields where feeding damage has occurred in the past, stored in the memory unit 18. For example, the feeding damage estimation unit 32 may estimate that the feeding damage risk is low when the estimated feeding damage prediction areas α, β... are in a paddy field different from the paddy field that has been previously damaged, and may estimate that the feeding damage risk is high when they are in the same paddy field. Note that the feeding damage risk is not limited to two stages, and may be three or more stages.

The damage estimation unit 32 may estimate the risk of damage from two or more of the temperature of the paddy field 70, the number of overwintering shellfish, and the history of past damage occurrence. In this case, the highest risk of damage among the respective risk levels may be adopted, or the average of the risk levels of damage among the respective risk levels may be adopted, or a risk of damage calculated using some formula (for example, a function such as risk of damage = f (temperature, number of overwintering shellfish, past occurrence history)) may be adopted.

Next, the method for estimating predation damage according to the first embodiment will be described. FIG. 6 is a flowchart showing an example of the method for estimating predation damage according to the first embodiment. The flowchart in FIG. 6 is executed after an app (predation damage estimation program) for estimating predation damage caused by shellfish, which is stored in the memory unit 18, is launched. The app is launched by an operator operating the input unit 14. As shown in FIG. 6, first, the image acquisition unit 22 acquires a plurality of images of the paddy field 70 captured by the imaging unit 56 of the aircraft 50 (step S10).

Next, the depression information acquisition unit 24 creates a digital elevation model of the paddy field 70 using the multiple captured images acquired in step S10 (step S12). A commonly known method can be used to create the digital elevation model.

Next, the depression information acquisition unit 24 acquires information about depressions occurring in the paddy field 70 from the digital elevation model of the paddy field 70 (step S14). For example, the depression information acquisition unit 24 acquires position information of depressions that are depressed by a predetermined value (e.g., 1 cm) or more from the average height of the paddy field 70 obtained from the digital elevation model, and the amount of depression of the depression from the average height of the paddy field 70. The depression information acquisition unit 24 creates the map of FIG. 4(a) and the depression information database of FIG. 4(b) from the acquired information about depressions. The created map may be displayed on the display unit 16.

Next, the weather information acquisition unit 26 acquires weather information including precipitation information and temperature information from the server 62 (step S16). In this first embodiment, the weather information acquisition unit 26 acquires precipitation information and temperature information from the server 62 for the next few days.

Next, the water depth estimation unit 28 estimates the predicted water depth in the depression based on the depression depth obtained in step S14 and the rainfall information from the present to several days into the future obtained in step S16 (step S18).

Next, the overwintering number estimation unit 30 estimates the number of overwintering shellfish by multiplying the overwintering survival rate of the apple snails and other shellfish calculated from the average winter temperature of the previous year by the number of shellfish and other shellfish that occurred in the paddy field 70 in the previous year (step S20). As described above, the number of shellfish that occurred in the paddy field 70 in the previous year may be a number obtained from a captured image of the paddy field 70, a number inferred from the distribution of egg masses or the area of past damage, an empirical number, or a number estimated by an operator actually looking at the paddy field 70. Note that the estimation of the number of overwintering shellfish does not have to be performed after step S18, but may be performed at any stage before step S26.

Next, the predation damage estimation unit 32 determines whether there is a depression where the water depth estimated in step S18 is equal to or greater than a predetermined value (e.g., 4 cm) (step S22). If there is no depression with a water depth equal to or greater than the predetermined value (step S22: No), the predation damage estimation unit 32 ends the process since the possibility of predation damage by shellfish is low. In this way, the predetermined water depth is a depth that makes it possible to distinguish between water depths where predation damage by shellfish is likely to occur and water depths where it is unlikely to occur.

If there is a depression with a water depth equal to or greater than a predetermined value (step S22: Yes), because damage caused by shellfish is affected by temperature, the damage estimation unit 32 determines from the temperature information acquired in step S16 whether the temperature in the paddy field 70 is equal to or greater than a predetermined temperature (e.g., 15°C) (step S24). If the temperature in the paddy field 70 is below the predetermined temperature, shellfish are slow to move and do not eat much rice, so the possibility of damage caused by shellfish is low, and the damage estimation unit 32 ends processing. In this way, the predetermined temperature is a temperature that makes it possible to distinguish between temperatures at which damage caused by shellfish is likely to occur and temperatures at which it is unlikely to occur.

If the air temperature is equal to or higher than the predetermined temperature (step S24: Yes), the damage estimation unit 32 estimates that depressions with a water depth equal to or greater than a predetermined value are areas where damage is expected to occur (step S26). The damage estimation unit 32 creates the map in FIG. 5(a) and the damage estimation information database in FIG. 5(b). The created map is displayed on the display unit 16.

The damage estimation unit 32 may estimate the extent of damage (damage risk) by referring to the temperature information of the paddy field 70 acquired in step S16, information on the overwintering number of shellfish estimated in step S20, and/or information on paddy fields where damage has occurred in the past stored in the memory unit 18. When the damage estimation unit 32 estimates the damage risk, it displays the estimation result on the map in FIG. 5(a). When only the damage risk is estimated, steps S22 and S24 do not need to be performed.

The worker can reduce the damage caused by the feeding damage by spraying pesticides locally in the predicted area of feeding damage estimated in step S26 and displayed on the display unit 16, removing shellfish from the predicted area of feeding damage, or lowering the water level of the rice field including the predicted area of feeding damage. The pesticides can be sprayed directly by the worker or by using a drone. By spraying pesticides locally in the predicted area of feeding damage, the amount of pesticide used can be reduced and costs can be reduced compared to spraying pesticides over the entire rice field. In addition, when removing shellfish from the predicted area of feeding damage, the worker's labor is reduced compared to when the worker patrols the entire rice field to remove shellfish or sets traps and attractants over the entire field. In addition, the feeding damage estimation device 10 may directly control the drone that sprays the pesticides or directly control the water level adjustment unit that adjusts the water level of the rice field.

In addition, the damage estimation unit 32 estimates the risk of damage by referencing the temperature of the paddy field 70, the number of overwintering shellfish, and/or paddy fields where damage has occurred in the past that are stored in the memory unit 18. This allows workers to spray pesticides and remove shellfish according to the risk of damage, further reducing the amount of pesticide used and the effort required to remove shellfish.

Figure 7 is a hardware configuration diagram of the damage estimation device 10. As shown in Figure 7, the damage estimation device 10 has a storage device 40, a memory 41, a processor 42, a communication interface 43, an input device 44, a display device 45, and a media reading device 46. Each of these parts is connected to each other by a bus 47.

The storage device 40 is a non-volatile storage device such as a hard disk drive (HDD) or a solid state drive (SSD), and stores the pest damage estimation program 1.

The damage estimation program 1 may be recorded on a computer-readable recording medium 48, and the processor 42 may read the damage estimation program 1 via the medium reading device 46. Examples of the recording medium 48 include physically portable recording media such as CD-ROMs (Compact Disk - Read Only Memory), DVDs (Digital Versatile Discs), and USB (Universal Serial Bus) memories. Semiconductor memories such as flash memories and hard disk drives may also be used as the recording medium 48. These recording media 48 are not temporary media such as carrier waves that do not have a physical form.

Furthermore, the damage estimation program 1 may be stored in a device connected to a public line, the Internet, a LAN, etc. In that case, the processor 42 may read and execute the damage estimation program 1.

Memory 41 is hardware that temporarily stores data, such as a dynamic random access memory (DRAM). The memory unit 18 in FIG. 3 is realized by the storage device 40 and memory 41.

The processor 42 is hardware such as a CPU (Central Processing Unit) or a GPU (Graphical Processing Unit) that controls each part of the damage estimation device 10. The processor 42 also executes the damage estimation program 1 in cooperation with the memory 41.

In this way, the memory 41 and the processor 42 work together to execute the damage estimation program 1, thereby realizing the control unit 20 of the damage estimation device 10.

The communication interface 43 is hardware such as a network interface card (NIC) for connecting the damage estimation device 10 to the network 60 (see FIG. 1). The communication interface 43 realizes the communication unit 12 in FIG. 3.

The input device 44 is an input device such as a touch panel or keyboard that allows an operator to input various information to the damage estimation device 10. The input device 44 realizes the input unit 14 in FIG. 3.

The display device 45 is hardware for implementing the display unit 16, and is a display device such as an LCD display for displaying a map showing predicted damage locations, etc.

The media reading device 46 is hardware such as a CD drive, DVD drive, or USB interface for reading the recording medium 48.

According to the first embodiment, the depression information acquisition unit 24 acquires information about depressions A, B, C, D, E, etc. of the paddy field 70 from an image of the paddy field 70 captured from the sky. The weather information acquisition unit 26 acquires weather information. The water depth estimation unit 28 estimates the water depth in depressions A, B, C, D, E, etc. based on the rainfall information included in the weather information. The feeding damage estimation unit 32 estimates feeding damage by shellfish based on the water depth in depressions A, B, C, D, E, etc. and the temperature information included in the weather information. Since feeding damage by shellfish is likely to occur when the water depth is equal to or greater than a predetermined value (e.g., 4 cm) and the temperature is equal to or greater than a predetermined temperature, it is possible to accurately estimate the location of feeding damage in the paddy field 70 by estimating feeding damage by shellfish based on the water depth in depressions A, B, C, D, E, etc. and the temperature information included in the weather information.

In the first embodiment, the water depth estimation unit 28 may estimate the water depth of depressions A, B, C, D, E... from the depression volume of depressions A, B, C, D, E... and the water depth actually measured at a predetermined position in the paddy field 70. However, as in this first embodiment, when the water depth estimation unit 28 estimates the water depth of depressions A, B, C, D, E... based on the rainfall information included in the weather information, a water depth sensor for actually measuring the water depth of the paddy field 70 becomes unnecessary.

In addition, in this first embodiment, the weather information acquisition unit 26 acquires rainfall information and temperature information from the present to a predetermined time later. By using the rainfall information from the present to a predetermined time later, it is possible to estimate the water depth predicted to occur in depressions A, B, C, D, E, etc. in the future. By using the temperature information from the present to a predetermined time later, it is possible to estimate the damage caused by shellfish predicted to occur in depressions A, B, C, D, E, etc. in these depressions. In this way, since future damage can be estimated in advance, it is possible to prevent damage in advance by spraying pesticides, adjusting water levels, removing shellfish, etc. based on the estimation results.

In addition, in this first embodiment, the overwintering number estimation unit 30 estimates the number of shellfish that have overwintered. The predation damage estimation unit 32 estimates the predation damage to shellfish based on the number of shellfish that have overwintered. Since the extent of predation damage is thought to vary depending on the number of shellfish that have overwintered, predation damage to shellfish can be estimated with high accuracy by estimating the predation damage to shellfish with reference to the number of shellfish that have overwintered.

In addition, in this first embodiment, the damage estimation unit 32 estimates damage to shellfish based on the history of past damage (e.g., information on rice paddy fields where damage has occurred in the past) stored in the memory unit 18. Since it is believed that shellfish are likely to be present again this year in areas where damage has occurred in the past (e.g., rice paddy fields) and that damage from damage is likely to be greater, damage to shellfish can be estimated with high accuracy by estimating damage from shellfish by referring to information on areas where damage has occurred in the past (e.g., rice paddy fields).

In the first embodiment, the weather information acquisition unit 26 may acquire rainfall information and temperature information from the present up to a predetermined period of time ago (e.g., several days ago). In this case, the current water depth of depressions A, B, C, D, E, etc. can be estimated.

In the above first embodiment, an example was given of obtaining meteorological information, such as rainfall information and temperature information, from the server 62. However, rainfall information and temperature information may also be obtained from a rainfall sensor and a temperature sensor installed in the paddy field 70.

In the above first embodiment, the image acquisition unit 22 has been described as acquiring images of a paddy field captured by an air vehicle 50, which is a drone, as an example. However, the image acquisition unit 22 may also acquire images of a paddy field captured by an object other than a drone from the sky.

Second Embodiment
The system configuration diagram of the damage estimation system according to the second embodiment is the same as the system configuration diagram of the damage estimation system according to the first embodiment shown in FIG. 1, so illustration and explanation will be omitted.

Figure 8 is a functional configuration diagram of the predation damage estimation device 10a in the second embodiment. As shown in Figure 8, in the second embodiment, the control unit 20a has a shellfish etc. identification unit 34, a missing stump etc. identification unit 36, and a warning issuing unit 38 in addition to the captured image acquisition unit 22, depression information acquisition unit 24, meteorological information acquisition unit 26, water depth estimation unit 28, overwintering number estimation unit 30, and predation damage estimation unit 32.

The shellfish etc. identification unit 34 detects at least one of individual shellfish and egg masses (hereinafter referred to as shellfish etc.) from the captured image of the paddy field 70 acquired by the captured image acquisition unit 22, and identifies the paddy field in which the shellfish etc. are occurring. The shellfish etc. identification unit 34 then updates the shellfish history information that records information identifying the paddy field in which the shellfish etc. are occurring (such as the paddy field identification number and location information), and stores it in the memory unit 18.

Figure 9 is a diagram showing an example of shellfish history information. As shown in Figure 9, the shellfish history information is a database that associates the date when shellfish, etc. were detected from the captured image of the rice paddy field with information that identifies the rice paddy field where the shellfish, etc. occurred (such as the identification number and location information of the rice paddy field). The shellfish history information is, for example, history information that spans multiple years.

The missing stump etc. identifying unit 36 detects at least one of missing stumps and broken leaves (hereinafter referred to as missing stumps etc.) from the captured image of the paddy field acquired by the captured image acquisition unit 22, and identifies the area where missing stumps etc. have occurred. The missing stump etc. identifying unit 36 then updates missing stump history information that records information (location information etc.) that identifies the area where missing stumps etc. have occurred, and stores it in the memory unit 18. A missing stump means that there is no rice plant where it should be, and broken leaves means that part of the rice has been eaten by shellfish and is floating in the water in a green state.

Figure 10 is a diagram showing an example of missing stock history information. As shown in Figure 10, missing stock history information is a database that associates the date when missing stocks, etc. were detected from captured images of a paddy field with information that identifies the area where the missing stocks, etc. occurred (such as latitude and longitude location information). Missing stock history information is, for example, historical information for a single year.

The warning issuing unit 38 judges whether the infestation field identified by the shellfish etc. identifying unit 34 is different from the infestation field recorded in the shellfish history information in the memory unit 18. If the warning issuing unit 38 judges that the infestation field identified by the shellfish etc. identifying unit 34 is a new field not recorded in the shellfish history information, it issues a warning to inform the operator that shellfish have been found in the new field. The warning may be displayed on the display unit 16, or, if the damage estimation device 10a is equipped with a speaker function, a warning sound may be issued from the speaker.

The warning issuing unit 38 also judges whether the area where missing stocks, etc. have occurred, identified by the missing stock etc. identifying unit 36, is different from the area where it has occurred, which is recorded in the missing stock history information in the memory unit 18. If the warning issuing unit 38 judges that the area where missing stocks, etc. have occurred, identified by the missing stock etc. identifying unit 36, is an area not recorded in the missing stock history information, it issues a warning to inform the operator that new damage caused by shellfish has occurred. The warning may be displayed on the display unit 16, or, if the damage estimation device 10a is equipped with a speaker function, a warning sound may be issued from the speaker.

Next, a method for estimating damage caused by insect pests according to the second embodiment will be described. In the second embodiment, in addition to estimating damage caused by insect pests according to the flowchart shown in FIG. 6 of the first embodiment, damage caused by insect pests is estimated according to the flowchart shown in FIG. 11. FIG. 11 is a flowchart showing an example of a method for estimating damage caused by insect pests according to the second embodiment.

As shown in FIG. 11, first, the image acquisition unit 22 acquires an image of the paddy field 70 captured by the imaging unit 56 of the aircraft 50 (step S30).

Next, the shellfish etc. identification unit 34 identifies the paddy fields where shellfish etc. are occurring by performing image processing on the captured image acquired in step S30 (step S32).

Next, the warning issuing unit 38 judges whether the paddy field identified in step S32 is different from the paddy field described in the shellfish history information in the memory unit 18 (step S34). If it is different from the previous paddy field (step S34: Yes), the warning issuing unit 38 issues a warning that shellfish have appeared in the new paddy field (step S36). The warning may be displayed on the display unit 16, or, if the damage estimation device 10a has a speaker function, a warning sound may be issued from the speaker. On the other hand, if it is the same as the previous paddy field (step S34: No), the warning issuing unit 38 does not issue a warning. The shellfish etc. identification unit 34 then stores the information on the paddy field identified in step S32 in the shellfish history information in the memory unit 18 (step S38).

Next, the missing stock etc. identification unit 36 identifies the area where missing stock etc. occurs by performing image processing on the captured image acquired in step S30 (step S40).

Then, the warning issuing unit 38 judges whether the occurrence area identified in step S40 is different from the occurrence area stored in the missing stock history information in the memory unit 18 (step S42). If it is different from the previous occurrence area (step S42: Yes), the warning issuing unit 38 issues a warning that new damage by shellfish has occurred (step S44). The warning may be displayed on the display unit 16, or, if the damage estimation device 10a has a speaker function, a warning sound may be issued from the speaker. On the other hand, if it is the same as the previous occurrence area (step S42: No), no warning is issued. The missing stock etc. identifying unit 36 then stores the position information of the occurrence area identified in step 40 in the missing stock history information in the memory unit 18 (step S46).

The order of steps S32 to S38 and steps S40 to S46 may be reversed.

According to the second embodiment, the shellfish etc. identification unit 34 (first identification unit) identifies a paddy field where at least one of shellfish and shellfish eggs is occurring from an image of the paddy field 70 captured from the sky. The warning issuing unit 38 (first warning issuing unit) issues a warning when the paddy field identified by the shellfish etc. identification unit 34 is different from the previous paddy field stored in the memory unit 18 (first memory unit). This makes it possible to inform the worker that shellfish have invaded a new paddy field and that there is a risk of new damage occurring in a paddy field that has not been damaged before. This allows the worker to lower the water level of the target paddy field or spray pesticides on the target paddy field.

According to the second embodiment, the missing stubble etc. identifying unit 36 (second identifying unit) identifies an area where at least one of missing stubbles and broken leaves has occurred from an image of the paddy field 70 captured from the sky. The warning issuing unit 38 (second warning issuing unit) issues a warning when the occurrence area identified by the missing stubble etc. identifying unit 36 differs from the past occurrence area stored in the memory unit 18 (second memory unit). This makes it possible to inform the worker that damage caused by shellfish has occurred in a new area. Thus, the worker can lower the water level in the target area or spray pesticides in the target area.

In the above second embodiment, the shellfish history information and the missing stock history information are stored in the same memory unit 18, but they may be stored in different memory units. Also, in the above example, the same warning issuing unit 38 issues a warning when shellfish appear in a new rice paddy field and when damage caused by shellfish occurs for the first time, but different warning issuing units may issue warnings.

In the first and second embodiments, the aircraft 50 is preferably a drone. By using a drone as the aircraft 50, it is possible to capture images of the paddy field 70 in high detail.

Although the embodiment of the present invention has been described in detail above, the present invention is not limited to such a specific embodiment, and various modifications and variations are possible within the scope of the gist of the present invention as described in the claims.

LIST OF SYMBOLS 1 Damage estimation program 10, 10a Damage estimation device 12 Communication unit 14 Input unit 16 Display unit 18 Memory unit 20, 20a Control unit 22 Image acquisition unit 24 Depression information acquisition unit 26 Weather information acquisition unit 28 Water depth estimation unit 30 Overwintering number estimation unit 32 Damage estimation unit 34 Shellfish etc. identification unit 36 Missing stumps etc. identification unit 38 Warning issuing unit 40 Storage device 41 Memory 42 Processor 43 Communication interface 44 Input device 45 Display device 46 Media reading device 47 Bus 48 Recording medium 50 Aircraft 52 Main body unit 54 Rotor 56 Imaging unit 60 Network 62 Server 70 Paddy field 100 Damage estimation system A to E Depressions α, β Damage prediction area

Claims (9)

a depression information acquiring unit that acquires information about depressions in the paddy field , the information including the depression volume of the depression, from an image of the paddy field captured from above;
A weather information acquisition unit for acquiring weather information;
a water depth estimation unit that estimates the water depth in the depression based on rainfall information included in the meteorological information or a water depth actually measured at a predetermined position in the paddy field and a depression amount of the depression ;
A predation damage estimation device comprising: a predation damage estimation unit that estimates damage caused by shellfish based on the water depth in the depression and the temperature information included in the weather information. The information about the depression includes location information about the depression,
The predation damage estimation device according to claim 1 , wherein the predation damage estimation unit estimates whether predation damage caused by the shellfish will occur in the depression, and outputs location information of the depression where the predation damage is estimated to occur . The rainfall information is rainfall information from the present to a predetermined period after,
The damage estimation device according to claim 1 or 2, wherein the temperature information is temperature information from the present to the end of the predetermined period. a wintering number estimation unit that estimates the number of shellfish that have overwintered based on an average winter temperature of the previous year;
The predation damage estimation device according to claim 1 , wherein the predation damage estimation unit estimates predation damage to the shellfish based on the number of the shellfish that have overwintered. The predation damage estimation device according to any one of claims 1 to 4, wherein the predation damage estimation unit estimates predation damage to the shellfish based on a history of past occurrences of predation damage caused by the shellfish. A first identification unit that identifies a paddy field in which at least one of the shellfish and the shellfish eggs is occurring from the captured image;
a first storage unit that stores the identified paddy field;
A damage estimation device as described in any one of claims 1 to 5, further comprising a first warning issuing unit that issues a warning when the identified paddy field is different from a past paddy field stored in the first memory unit. a second identification unit that identifies an occurrence area in which at least one of a missing stubble of a crop planted in the paddy field and a broken leaf eaten by the shellfish is occurring from the captured image;
a second storage unit that stores the identified occurrence area;
A pest damage estimation device as described in any one of claims 1 to 6, further comprising a second warning issuing unit that issues a warning when the identified occurrence area differs from a past occurrence area stored in the second memory unit. The damage estimation device according to any one of claims 1 to 7, wherein the captured image is an image captured by a drone. The aircraft,
A damage estimation device,
The damage estimation device includes:
a depression information acquisition unit that acquires information about depressions in the paddy field from an image of the paddy field captured by the aircraft , the information including a depression volume of the depression ;
A weather information acquisition unit for acquiring weather information;
a water depth estimation unit that estimates the water depth in the depression based on rainfall information included in the meteorological information or a water depth actually measured at a predetermined position in the paddy field and a depression amount of the depression ;
A predation damage estimation system having a predation damage estimation unit that estimates damage caused by shellfish based on the water depth in the depression and the temperature information included in the weather information.

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