Mosquito propagation suppression program, computer-readable recording medium having mosquito propagation suppression program recorded thereon, mosquito propagation suppression system, and mosquito propagation suppression method

Abstract

Provided are: a mosquito propagation suppression program for analyzing a puddle likely to be inhabited by mosquito larvae on the basis of an image obtained from a flying object; a computer-readable recording medium on which the mosquito propagation suppression program is recorded; a mosquito propagation suppression system, and a mosquito propagation suppression method. A mosquito propagation suppression program according to the present invention is a mosquito propagation suppression program for analyzing a puddle likely to be inhabited by mosquito larvae on the basis of an image obtained from a flying object, and causes a computer to execute: an acquisition step for acquiring the position and size of a puddle in the image obtained from the flying object; a temperature measurement step for acquiring the temperature of the puddle measured by the flying object; and an estimation step for estimating the depth of the puddle on the basis of the position and size of the puddle acquired by the acquisition step and the temperature of the puddle acquired by the temperature measurement step.

Description

Mosquito breeding control program, computer-readable recording medium having the mosquito breeding control program recorded thereon, mosquito breeding control system, and mosquito breeding control method

[0001] The present invention relates to a mosquito breeding control program, a computer-readable recording medium on which the mosquito breeding control program is recorded, a mosquito breeding control system, and a mosquito breeding control method.

[0002] Preventing the spread of mosquito-borne infectious diseases such as malaria and dengue fever is a very important issue. To reduce mosquito-borne infectious diseases, a method called Larval Source Management (hereinafter referred to as "LSM") has been proposed. LSM is a method of reducing the population of mosquito larvae by spraying insecticides in water bodies that serve as breeding grounds for mosquito larvae. LSM is sometimes implemented as a national project in African countries as a measure against infectious diseases.

[0003] Patent No. 7193824

[0004] However, LSM has not been widely adopted for the following reasons. The first problem is that workers must search for puddles by walking or other means from the ground, which requires a lot of time and effort. After rain falls on a vast area of ​​land, many puddles form simultaneously. Furthermore, eggs are present on the dry surface of the ground, and within two to three days after puddles form, the eggs turn into larvae, which then progress through a pupa stage called a giant mosquito larvae and then into adults within a few days to a week. After puddles form due to rain, it is necessary to quickly spray insecticides, etc. However, because workers must search for puddles on foot, there is a shortage of workers, and the work cannot be completed in time.

[0005] The second problem is that, in the past, when carrying out LSM, workers had to spray pesticides in all puddles. Spraying puddles over a wide area required a large number of workers. Furthermore, spraying pesticides in all puddles required a large amount of pesticide, which not only increased the cost of purchasing the pesticide, but also raised concerns about the environmental impact of using large amounts of pesticide. Furthermore, spraying large amounts of pesticide leaves its residue for a long period of time, affecting not only mosquito larvae but also surrounding organisms. Considering the living environment in malaria-prone areas, this could pose a health risk to humans.

[0006] To address this issue, the inventors of the present invention have considered mounting a Light Detection and Ranging (LiDAR) measurement device on a drone in order to search for and discover puddles over a wide area. For example, as disclosed in Patent Document 1, there is a technology for mounting a LiDAR measurement device on a drone.

[0007] However, with the lidar measurement technology disclosed in Patent Document 1, puddles reflect radio waves, making it difficult to effectively detect puddles because the signal difference between the ground surface and puddles is small.

[0008] Even if puddles could be detected, hundreds to thousands of puddles would be found when a wide area was viewed from the air. If pesticides were sprayed on all puddles as in the past, more workers would be required and more puddles would be found than if workers had searched from the ground, resulting in the problem of increased pesticide use.

[0009] The present invention has been made to solve such problems, and aims to provide a mosquito breeding suppression program that analyzes puddles where mosquito larvae are likely to live based on images obtained from a flying object, a computer-readable recording medium on which the mosquito breeding suppression program is recorded, a mosquito breeding suppression system, and a mosquito breeding suppression method.

[0010] To achieve the above object, according to one embodiment of the present invention, there is provided a mosquito breeding control program for analyzing puddles likely to be home to mosquito larvae based on images acquired from an aerial vehicle, the program causing a computer to execute the following steps: acquiring the position and size of the puddle in the image acquired from the aerial vehicle; measuring the temperature of the puddle measured from the aerial vehicle; and estimating the depth of the puddle based on the position and size of the puddle acquired in the acquiring step and the puddle temperature acquired in the temperature measuring step. According to one embodiment of the present invention configured in this manner, the program causes the computer to execute the estimation step of estimating the depth of the puddle based on the position and size of the puddle acquired in the acquiring step and the puddle temperature acquired in the temperature measuring step. This makes it possible to estimate the depth of the puddle, which is a biologically important factor in analyzing puddles likely to be home to mosquito larvae, and to efficiently identify puddles likely to be home to mosquito larvae based on images acquired from the aerial vehicle. Therefore, puddles where mosquito larvae are likely to live can be efficiently found, allowing a limited number of workers to spray insecticide on the found puddles, thereby reducing the number of workers, labor, and amount of insecticide used.

[0011] According to one embodiment of the present invention, the estimation step of the mosquito breeding control program preferably estimates the depth of the puddle by comparing the temperature of the puddle with the temperature of a reference puddle, for example, a pre-created puddle whose size and depth have been specified.

[0012] According to one embodiment of the present invention, the estimation step of the mosquito breeding control program preferably measures the temperature of the puddle at least two or more times at different times, and estimates the depth of the puddle based on the measured temperature change.

[0013] According to one embodiment of the present invention, the mosquito breeding control program preferably further comprises an evaluation step of evaluating the risk of mosquito larvae inhabiting the puddles based on the depth of the puddles.

[0014] According to one embodiment of the present invention, the mosquito breeding control program preferably further includes an output step of displaying puddles that have been evaluated as being high risk by the evaluation step on a display device, distinguishing them from other puddles in the image obtained from the flying object.

[0015] According to one embodiment of the present invention, the output step of the mosquito breeding control program preferably displays the positional relationship between the position of the mobile information terminal having the display device and a puddle evaluated as being high risk in an image obtained from the flying object.

[0016] According to one embodiment of the present invention, preferably, a computer-readable recording medium having any of the above-mentioned mosquito breeding control programs recorded thereon is provided. According to one embodiment of the present invention configured in this manner, the computer-readable recording medium having the above-mentioned mosquito breeding control program recorded thereon can cause a computer to execute predetermined steps, thereby efficiently detecting puddles that are likely to be inhabited by mosquito larvae.

[0017] According to one embodiment of the present invention, a mosquito breeding control system that analyzes puddles likely to be home to mosquito larvae based on images obtained from an aerial vehicle includes: an aerial vehicle that flies above the ground; a temperature measuring device attached to the aerial vehicle; a camera attached to the aerial vehicle; and an estimation device that estimates the depth of the puddle based on the position and size of the puddle acquired by the camera and the temperature of the puddle measured by the temperature measuring device. According to one embodiment of the present invention configured as described above, the camera attached to the aerial vehicle acquires images of a relatively wide range, and the estimation device estimates the depth of the puddle based on the position and size of the puddle acquired by the camera and the temperature of the puddle measured by the temperature measuring device. This allows the estimation of the puddle depth, which is a biologically important factor in analyzing puddles likely to be home to mosquito larvae, and enables efficient discovery of puddles likely to be home to mosquito larvae based on images obtained from the aerial vehicle. Therefore, puddles where mosquito larvae are likely to live can be efficiently found, allowing a limited number of workers to spray insecticide on the found puddles, thereby reducing the number of workers, labor, and amount of insecticide used.

[0018] According to one embodiment of the present invention, the air vehicle is preferably a fixed-wing drone.

[0019] According to one embodiment of the present invention, a mosquito breeding control method for analyzing puddles that are likely to be home to mosquito larvae based on images acquired from an aerial vehicle preferably includes the following steps: acquiring the position and size of the puddle in the image acquired from the aerial vehicle; measuring the temperature of the puddle measured from the aerial vehicle and whose position and size have been acquired; and estimating the depth of the puddle based on the position and size of the puddle acquired in the acquiring step and the temperature of the puddle acquired in the temperature measuring step. According to one embodiment of the present invention configured in this manner, the mosquito breeding control method includes the following steps: acquiring the position and size of the puddle in the image acquired from the aerial vehicle; measuring the temperature of the puddle measured from the aerial vehicle and whose position and size have been acquired; and estimating the depth of the puddle based on the position and size of the puddle acquired in the acquiring step and the temperature of the puddle acquired in the temperature measuring step. This makes it possible to estimate the depth of a puddle, which is a biologically important factor when analyzing puddles where mosquito larvae are likely to live, and to efficiently find puddles where mosquito larvae are likely to live based on images obtained from the aerial vehicle.As a result, because puddles where mosquito larvae are likely to live can be found efficiently, a limited number of workers can spray insecticide on the found puddles, reducing the number of workers, labor, and amount of insecticide used.

[0020] The mosquito breeding suppression program, computer-readable recording medium on which the mosquito breeding suppression program is recorded, mosquito breeding suppression system, and mosquito breeding suppression method of the present invention make it possible to analyze puddles that are likely to be inhabited by mosquito larvae based on images obtained from flying objects.

[0021] 8 is a schematic diagram of a mosquito breeding control system equipped with a mosquito breeding control program according to one embodiment of the present invention. FIG. 9 is a diagram showing the state of the interior of a puddle analyzed using the mosquito breeding control program according to one embodiment of the present invention. FIG. 10 is a block diagram showing the configuration of a mosquito breeding control system according to one embodiment of the present invention. FIG. 11 is a block diagram showing the configuration of an estimation device in the mosquito breeding control system according to one embodiment of the present invention. FIG. 12 is a diagram showing the relationship between the estimation device of the mosquito breeding control system of FIG. 4 and a mobile information terminal. FIG. 13 is a block diagram showing the configuration of an estimation device in the mosquito breeding control system according to one embodiment of the present invention. FIG. 14 is a diagram showing a flowchart of processing related to the mosquito breeding control system according to one embodiment of the present invention. FIG. 15 is a diagram showing an aerial image taken by a camera of the flying object of the mosquito breeding control system according to one embodiment of the present invention. FIG. 16 is a diagram showing an image measured by a temperature measurement device of the flying object of the mosquito breeding control system according to one embodiment of the present invention. FIG. 17 is a diagram showing a state in which a puddle 4 is detected and distinguished from other ground, vegetation, etc. in the aerial image of FIG. 8. FIG. 18 is a diagram showing a puddle evaluated as having a relatively high risk among puddles in an aerial image in the mosquito breeding control system according to one embodiment of the present invention. FIG. 19 is a diagram explaining the mechanism for estimating the depth of a puddle based on a reference puddle in one embodiment of the present invention. FIG. 19 is a diagram showing factors and conditions that increase the risk of larvae inhabiting in one embodiment of the present invention.

[0022] A mosquito breeding control system 1 equipped with a computer that executes a mosquito breeding control program 2 (see FIG. 3) according to one embodiment of the present invention will now be described with reference to the accompanying drawings. The embodiments of the present disclosure have been described by way of example, and it will be apparent to those skilled in the art that many modifications, changes, and substitutions may be made within the spirit and scope of the present invention. Therefore, the present invention is not limited to the disclosed embodiments, and various modifications, changes, etc. may be made in form and detail without departing from the scope of the claims. Furthermore, the components disclosed in the specification may be freely combined.

[0023] As shown in Figure 1, a mosquito breeding control system 1 according to one embodiment of the present invention analyzes puddles 4 where mosquito larvae 3 (see Figure 2) are likely to emerge (exist) and inhabit, based on images captured from an aerial vehicle 6. The mosquito breeding control system 1 can select and display puddles 4 in the aerial image that are likely to be inhabited by mosquito larvae 3. Since the mosquito breeding control system 1 can suppress mosquito breeding, it is also a mosquito-borne infectious disease control system. Similarly, the mosquito breeding control program is a mosquito-borne infectious disease control program, and the mosquito breeding control method described below is a mosquito-borne infectious disease control program.

[0024] FIG. 2 shows an example of a puddle 4 in which mosquito larvae 3 exist. The water surface 4a of the puddle 4 is indicated by a dashed line. The mosquito larvae 3 are hatched from eggs 3a in the puddle 4. The larvae 3 are so-called mosquito larvae. For example, when rain falls while the eggs are present, the larvae 3 develop into larvae approximately two to three days after the formation of the puddle 4. It is known that Anopheles eggs can withstand nine months of dryness and hatch into adult mosquito larvae after the formation of puddles due to rain, even during a long dry season. The larvae 3 develop into adult mosquitoes in the puddle 4 within approximately several days to one week. The mosquitoes are, for example, Anopheles species. Mosquitoes feed on human blood, and Anopheles species mosquitoes transmit, for example, the infectious disease malaria. Other types of mosquitoes transmit infectious diseases such as dengue fever, Japanese encephalitis, West Nile fever, and Zika virus infection, depending on the type of mosquito.

[0025] Puddles 4 are puddles that form on the ground G after rain, for example. They are formed by water collecting on uneven or sloped areas of the ground G. The size of puddles 4 is not limited. Puddles 4 may be puddles after rain, puddles that have accumulated in depressions, puddles that have seeped out, ponds, swamps, reservoirs, rice paddies, water in depressions, water in irrigation ditches, lakes, etc. Puddles 4 also include puddles measuring, for example, 30 cm x 30 cm and 200 cm x 200 cm. Puddles 4 include not only those that form short-term after rain, but also those that exist for long periods due to weather or climate. Depending on the target mosquito species, puddles 4 may not include places with constant flowing water, lakes where other aquatic organisms that serve as predators for mosquito larvae do not grow easily, or relatively large ponds (e.g., ponds of 100 m x 100 m). Anopheles mosquitoes prefer to breed in relatively small puddles 4, so the puddle 4 may be a relatively small puddle that is smaller than 500 cm x 500 cm in size. Such a relatively small puddle 4 is difficult to identify from a satellite or manned aircraft, but the drone of this embodiment has a spatial resolution of 0.02 m or less, making it easy to detect.

[0026] As shown in Figure 3, the mosquito breeding control system 1 includes a flying object 6 that flies above the ground, a temperature measuring device 8 provided on the flying object 6, a camera 10 provided on the flying object 6, a multispectral camera 11 provided on the flying object 6, a GPS 9 provided on the flying object 6, a control device 7 that controls the flying object 6, the temperature measuring device 8, the camera 10, etc., and an estimation device 12 (mosquito breeding control device) that estimates the depth of the puddle 4.

[0027] The flying object 6 is a device that flies above the ground G, and in this embodiment, is a fixed-wing drone. The flying object 6 may be, for example, a satellite, a manned aircraft, a helicopter, an unmanned aircraft, a fixed-wing drone, a multicopter drone, an airship, or the like. Fixed-wing drones have the advantage of being able to fly for longer periods of time and over longer distances (e.g., approximately 200 km) in a single flight compared to multicopter drones, etc. Therefore, fixed-wing drones can acquire aerial images (ground images) of a relatively wide area in a single flight, for example, aerial images (ground images) of a 20 km x 20 km area or a 10 km x 10 km area. Furthermore, fixed-wing drones can perform measurements more easily than manned aircraft, helicopters, etc. Fixed-wing drones have the advantage of being able to easily detect relatively small puddles 4 (e.g., 30 cm square puddles) on the ground from a lower height than satellites or manned aircraft.

[0028] The temperature measuring device 8 is attached to the flying object 6 and measures the temperature of an object on the ground from above. The temperature measuring device 8 is, for example, a thermal camera, and measures the temperature by detecting infrared rays emitted from the object. The temperature measuring device 8 functions as a temperature measuring device. The temperature measuring device 8 can measure the temperature (water temperature) of the puddle 4 in the image.

[0029] The camera 10 is attached to the flying object 6 and captures images of objects on the ground from the sky. The camera 10 has the function of capturing visible light images. The camera 10 can capture still images or videos. The temperature measurement by the temperature measuring device 8 and the image capture by the camera 10 and a multispectral camera 11 (described later) are synchronized. Therefore, it is possible to compare the temperature on the image captured by the temperature measuring device 8 with the object on the image captured by the camera 10 and the multispectral camera 11.

[0030] The multispectral camera 11 is attached to the flying object 6 and captures images of objects on the ground from the sky. The multispectral camera 11 has a function of capturing images that can be analyzed for wavelength components (spectrum) of light.

[0031] The GPS 9 is a global positioning system, and is a satellite positioning system. The GPS 9 is electrically connected to the control device 7 and transmits position information such as the latitude and longitude of the flying object 6 to the control device 7.

[0032] The control device 7 is provided separately from the flying object 6 and remotely controls the flight course, speed, etc. of the flying object 6. The control device 7 can also control the temperature measurement device 8, the camera 10, the multispectral camera 11, etc. The flying object 6 flies unmanned along a predetermined flight course under the control of the control device 7. The control device 7 recognizes the position (e.g., latitude and longitude) of the flying object 6 using a GPS 9 provided in the flying object 6. The control device 7 is provided separately from the estimation device 12, but the control device 7 may be configured integrally with the estimation device 12 and have the functions of the estimation device 12. The control device 7 is provided with a storage device and a processor capable of executing control.

[0033] The estimation device 12 estimates the depth of the puddle 4 based on the position and size of the puddle 4 acquired by the camera 10 or the multispectral camera 11 and the temperature of the puddle 4 acquired by the temperature measuring device 8. The estimation device 12 is equipped with a mosquito breeding control program 2 that analyzes puddles 4 that are likely to be inhabited by mosquito larvae 3 based on images acquired from the camera of the flying object 6, etc. The estimation device 12 is equipped with a mosquito breeding control program 2 that selects puddles 4 that are likely to be inhabited by mosquito larvae 3 from puddles in the images acquired from the flying object 6. The mosquito breeding control program 2 has a function of estimating the depth of the puddle 4 based on the position and size of the puddle 4 acquired by the camera 10 and the temperature of the puddle 4 acquired by the temperature measuring device 8. The estimation device 12 is composed of one or more servers that function as computers. The estimation device 12 does not have to be configured as a single server, but may be configured as another server located in a remote location via the Internet 32.

[0034] The estimation device 12 includes a storage device 16 and a processor 18. The estimation device 12 also functions as a control unit for a series of control processes. The storage device 16 is, for example, a volatile memory capable of high-speed reading and writing of information, and is used as a storage area and a working area when the processor 18 processes information. The storage device 16 may be a nonvolatile storage or nonvolatile memory, for example, a flash memory such as an eMMC, UFS, or SSD. The storage device 16 stores programs and various data for executing the mosquito breeding suppression program of this embodiment. The storage device 16 constitutes a computer-readable tangible recording medium and stores the mosquito breeding suppression program 2. The processor 18 controls the operation of the estimation device 12. The processor 18 is, for example, a CPU. Note that the processor 18 may also be an electronic circuit such as an MPU. The processor 18 performs various processes by reading and executing programs and data stored in the estimation device 12. If the program of this embodiment is stored in another computer-readable recording medium, the processor 18 may execute instructions from the program in that recording medium. The computer-readable recording medium may be another recording medium capable of storing data, such as a USB memory, an SD card, or a DVD. The estimation device 12 may be a tablet computer, a smartphone, another personal digital assistant, a smart watch, a wearable device, or another electronic device. The estimation device 12 may include a communication device 20 for transmitting and receiving data to and from other devices, a display device 22 such as a display for displaying output results to a user, and an input device 23 for receiving input commands to the estimation device 12. The communication device 20 may be a device or module for wireless communication or a device or module for wired communication. The input device 23 may be, for example, a keyboard or a mouse for receiving keyboard input. These components are connected via a bus 13. Note that an interface is provided between the bus 13 and each component as needed.

[0035] As shown in FIG. 6 , the estimation device 12 includes an acquisition step function unit 24 that executes an acquisition step S2, a temperature measurement step function unit 26 that executes a temperature measurement step S3, an estimation step function unit 28 that executes an estimation step S4, an evaluation step function unit 30 that executes an evaluation step S5, and an output step function unit 33 that executes an output step S6, based on the mosquito breeding control program 2. The acquisition step function unit 24 has the function of causing the estimation device 12, which is a computer, to execute an acquisition step S2 (see FIG. 7 ) that acquires information about the position and size of puddles 4 in an image (see FIG. 8 ) obtained from the flying object 6. Therefore, the acquisition step function unit 24 has the function of detecting puddles 4 in the captured image. The acquisition step function unit 24 is configured as part of the mosquito breeding control program 2.

[0036] The temperature measurement step function unit 26 has a function of causing the estimation device 12 as a computer to execute a temperature measurement step S3 of acquiring information about the temperature of the puddle 4 measured from the flying object 6 at approximately the same time as the image (see FIG. 8 ) is acquired. Such a temperature measurement step function unit 26 is configured as part of the mosquito breeding control program 2.

[0037] The estimation step function unit 28 has a function of causing the estimation device 12 as a computer to execute an estimation step S4 of estimating the depth of the puddle 4 based on the position and size of the puddle 4 acquired in the acquisition step S2 and the temperature of the puddle 4 acquired in the temperature measurement step S3. The evaluation step function unit 30 has a function of causing the estimation device 12 as a computer to execute an evaluation step S5 of evaluating the risk of mosquito larvae 3 living in the puddle 4 based on the depth of the puddle 4. The evaluation step function unit 30 is configured as a part of the mosquito breeding control program 2.

[0038] The output step function unit 33 has a function of causing the estimation device 12 as a computer to execute an output step S6 in which the puddles 4 evaluated as having a high risk in the evaluation step S5 are displayed on a display device, distinguished from other puddles 4 in the image obtained from the flying object 6. Such an output step function unit 33 is configured as a part of the mosquito breeding control program 2.

[0039] The estimation step function unit 28 is configured as part of the mosquito breeding control program 2. The estimation step function unit 28 has a function of executing the estimation step S4 (see FIG. 7).

[0040] As shown in FIG. 5 , the estimation device 12 can communicate with a mobile information terminal 34 via the Internet 32, and information is transmitted. The mobile information terminal 34 is provided so that the worker spraying the insecticide can easily check the information. For example, each worker has a mobile information terminal 34 such as a smartphone. The mobile information terminal 34 can be configured as a smartphone, mobile phone, smartwatch, tablet PC, notebook PC, desktop PC, etc. The mobile information terminal 34 has a display device 34a that forms a display screen. The display device 34a can be, for example, a monitor display, a display screen of a mobile information terminal, a display screen of a smartphone, etc. The estimation device 12 can output the output result of the output step S6 (see FIG. 7 ) on the display screen of the mobile information terminal 34. Therefore, in the output step S6, puddles 4 evaluated as high risk (or puddles evaluated as having a certain level of risk or higher) are displayed on the display screen of the mobile information terminal 34 of the worker spraying the insecticide, distinguishing them from other puddles. Such a mobile information terminal 34 may or may not be included in the mosquito breeding control system 1. A plurality of portable information terminals 34 can be provided for one estimation device 12. This allows multiple workers to simultaneously perform tasks such as spraying pesticides while checking information on their own portable information terminals 34. This makes the pesticide spraying process more efficient.

[0041] Next, a series of operations related to the mosquito breeding control system of this embodiment will be described with reference to FIG. 7 . The mosquito breeding control program 2 can be used for the series of operations related to the mosquito breeding control system of this embodiment. As shown in FIG. 7 , in a preparation step S1 of the mosquito breeding control method, the estimation device 12 acquires ground surface image data B (see FIG. 8 ) of an aerial image taken by the camera 10 attached to the flying object 6, temperature data C (see FIG. 9 ) of the temperature of the ground surface, etc., acquired from the flying object 6, etc. After acquiring the ground surface image data, etc., the estimation device 12 determines that preparations for executing subsequent processing are complete, and proceeds to S2. Note that FIGS. 8 and 9 each merely show examples of images, and therefore illustrate images of different objects.

[0042] As shown in FIG. 1 , the ground surface image data (see FIG. 8 ) and temperature data (see FIG. 9 ) of the ground surface, etc., of the aerial photographed image are obtained by flying the flying object 6 of the mosquito breeding control system 1 over the area from which data is to be obtained. While the flying object 6 flies over the survey area, the camera 10 captures aerial images of objects on the ground G, and the temperature measurement device 8 measures the temperature of objects on the ground. The area A of the aerial image captured by the camera 10 is illustrated by a dashed line in FIG. 1 . The images captured by the camera 10 are overlaid and modeled, and then orthomosaic-ized using so-called orthosoft. The orthomosaic ground surface image data is illustrated in FIG. 8 . In this manner, the estimation device 12 acquires the ground surface image data. The estimation device 12 may be equipped with orthosoft. The estimation device 12 also acquires temperature data (see FIG. 9 ) of the ground surface, etc., in the same area as the ground surface image data.

[0043] In step S2, as shown in FIGS. 1 and 7 , the acquisition step function unit 24 of the estimation device 12 executes an acquisition step S2 in which the location and size (surface area) of the puddle 4 are acquired from the ground surface image data B (see FIG. 8 ) acquired from the flying object 6. More specifically, as shown in FIG. 10 , the estimation device 12 analyzes the acquired ground surface image data B using the acquisition step function unit 24 and recognizes the puddle 4, distinguishing it from other ground, vegetation, etc. The estimation device 12 measures and acquires not only the existence of the puddle 4, but also its location (latitude and longitude) and size (length, width, and area) of the puddle 4. For example, the estimation device 12 recognizes the latitude and longitude at which the aerial image was taken, and can determine the latitude and longitude of the location of the puddle 4 in the image. In FIG. 10 , the detected puddle 4 is illustrated surrounded by a dashed line D. Furthermore, as shown in Fig. 11, the estimation device 12 assigns a unique identification index E (e.g., an index value such as "index 1") to each detected puddle 4. Therefore, the detected puddles 4 can be individually recognized and registered, facilitating subsequent management. In Fig. 11, the position (latitude and longitude) of each puddle 4 is displayed below the index of the identification index E. In this way, for example, approximately tens to thousands of puddles are detected in the aerial image by the acquisition step S2.

[0044] For example, the area of ​​the puddle 4 can be detected in the image acquired by the multispectral camera 11. For example, if R is the reflectance of visible red light and SWIR is the reflectance of shortwave infrared wavelengths, it is possible to determine whether or not the puddle 4 is present in the image using the following formula: For example, if NDWI is equal to or different from the value of 1, it may be determined that the puddle 4 is present. It should be noted that the puddle 4 may be determined using an image index such as NDVI instead of NDWI.

[0045] Furthermore, as a modified example, the area of ​​the puddle 4 may be detected by, for example, capturing an infrared image at the same time as capturing the aerial image, and then binarizing and analyzing the infrared image. For example, the area of ​​the puddle 4 may be detected by binarizing each of the infrared image and the thermo image and calculating the product. Note that image recognition using AI software may be used to detect such puddles 4, and the puddle 4 may be recognized separately from other ground, vegetation, etc. Returning to the description of this embodiment, after acquiring the position and size of the puddle 4, the estimation device 12 proceeds to S3.

[0046] In S3, the temperature measurement step function unit 26 of the estimation device 12 executes a temperature measurement step S3 in which the temperature of the puddle 4 is measured by the temperature measurement device 8 of the flying object 6 and acquired by the temperature measurement device 8 at approximately the same time as the image of the puddle 4 is captured by the camera 10. FIG. 9 shows an image of the temperature distribution measured by the temperature measurement step function unit 26. The estimation device 12 matches the puddle 4 detected by the acquisition step function unit 24 with the temperature of the area corresponding to the puddle 4 acquired by the temperature measurement device 8, and acquires the temperature of the puddle 4. The temperature measurement step function unit 26 has the function of comparing the image captured by the camera 10 with the image acquired by the temperature measurement device 8 to determine the water surface temperature of the puddle 4. The temperature measurement step function unit 26 may simply compare the two images, or may compare the two images using image recognition such as AI. After acquiring the temperature of the puddle 4, the estimation device 12 proceeds to S4.

[0047] In step S4, the estimation device 12 executes an estimation step S4 in which it estimates the depth d2 of the puddle 4 based on the position and size (e.g., surface area) of the puddle 4 acquired in the acquisition step S2 and the temperature of the puddle 4 acquired in the temperature measurement step S3. As shown in FIG. 12, the estimation step S4 (see FIG. 7) of the mosquito breeding control program 2 estimates the depth d2 of the puddle 4 (the depth from the water surface 4a to the bottom surface 4b) by comparing the temperature of the puddle 4 with the temperature of a reference puddle 30 whose size and depth are specified. This estimation step S4 is based on the mechanism that, when the size (surface area) of a puddle is the same under the same sunlight conditions, the shallower the puddle, the faster the water temperature rises. The estimation step S4 estimates the depth d2 of the detected puddle 4 based on the size of the puddle 4 and the rise in water temperature.

[0048] Here, the reference puddle 30 is a puddle whose size (length, width, and surface area) and depth are specified and which serves as a reference for comparison with other puddles. The reference puddle 30 is created in advance and artificially formed so that the size and depth of the puddle are clear. Note that a naturally formed puddle may be used as the reference puddle 30 as long as its size and depth can be specified. It is preferable that the reference puddle 30 be formed in the same soil as puddle 4 to make the environment similar to that of puddle 4.

[0049] The mechanism for estimating puddle depth will be described in more detail with reference to FIG. 12 . For example, if the puddle 4 to be estimated is located several kilometers to approximately 20 kilometers from the reference puddle 30, the puddle 4 to be estimated and the reference puddle 30 will be under roughly similar weather conditions (sunshine conditions). For example, the hours of sunshine from sunrise to the time of measurement and the air temperature for the puddle 4 to be estimated and the reference puddle 30 will be roughly similar. The energy required to raise the temperature of a puddle is determined by the amount of energy provided by sunlight per unit area, and the surface area of ​​the puddle is a factor in the temperature rise. For puddles with the same surface area, the temperature rise is determined by the volume of water, so the deeper the puddle, the more gradual the temperature rise. Therefore, at a given time, there is a temperature difference between the measured temperature of puddle 4 and the temperature of the reference puddle 30 due to the difference between the surface area and depth of puddle 4 and the surface area and depth of the reference puddle 30. A specific example will be used to explain this. The image taken at a certain time during the day includes the reference puddle 30 and the puddle 4. The temperature of the reference puddle 30 is 25°C, and the size (surface area) of the reference puddle 30 is 1 m. ２ (length 1m x width 1m), depth d1cm (specified), and the temperature of puddle 4 is 22 degrees, the size of puddle 4 is 1m ２The puddle 4 has a size of 1 m long x 1 m wide and a depth of d2 cm. In this case, the water temperature of the puddle 4 is lower than that of the reference puddle 30, so the depth d2 cm of the puddle 4 is estimated to be deeper than the depth d1 cm of the reference puddle 30. Based on this mechanism, the estimation device 12 possesses the data necessary to estimate the relationship between the temperature, size (surface area), and depth of the puddle 4. Therefore, the estimation device 12 can specifically calculate the depth d2 cm of the puddle 4 as an estimated value. Based on this mechanism, the estimation device 12 can estimate the depth d2 cm of the puddle 4. The estimation device 12 may also specifically calculate the depth d2 cm of the puddle 4 as an estimated value using AI software that has learned data such as the temperature, size (surface area), and depth of the puddle 4 as training data. Measuring the depth and temperature of each puddle by hand, as in the past, would require insufficient manpower and time, and measurements would not be possible in time because mosquitoes mature from larvae 3 to adults in a few days. According to the puddle depth estimation of this embodiment, the depths of a large number of puddles 4 can be estimated, thereby solving such conventional problems.

[0050] As a modified example, the estimation step S4 may measure the temperature of the same puddle 4 at least two or more times at different times, and estimate the depth of the puddle 4 based on the measured temperature change. By acquiring the temperature of the puddle 4 measured in a first measurement at a certain time and the temperature of the same puddle 4 measured in a second measurement after a certain time has passed, the estimation device 12 can estimate the depth d2 cm of the puddle 4 with higher accuracy. More specifically, based on the image and temperature data taken in the first measurement at a certain time during the day, the temperature of the puddle 4 is 20 degrees, the size of the puddle 4 is 1 m, and so on, ２ The size of the puddle is 1m (length 1m x width 1m), and the temperature and other data taken in the second measurement after a certain time has passed show that the temperature of the same puddle 4 is 25 degrees and the size of the puddle 4 is 1m. ２For example, if the reference puddle 30 has dimensions of 1 m long x 1 m wide, the depth d2 cm of the puddle 4 can be estimated by taking into account factors such as the duration of sunlight between the first and second measurements. In this case, the amount of heat the reference puddle 30 received from sunlight can be calculated by taking into account the change in temperature between the reference puddle 30 photographed in the first measurement and the reference puddle 30 photographed in the second measurement, and the amount of heat received by the puddle 4 and its depth can be estimated based on this amount of heat. Taking into account the temperature change in the reference puddle 30, the accuracy of estimating the depth d2 cm of the puddle 4 can be further improved. Even without a reference puddle 30, the estimation device 12 can estimate the depth d2 cm of the puddle 4 with a certain degree of accuracy based on the theory described above.

[0051] Returning to FIG. 7 , the flowchart will be explained. In S5, the estimation device 12 executes an evaluation step S5 in which the estimation device 12 evaluates the risk of mosquito larvae 3 inhabiting the puddle 4 based on the depth d2 of the puddle 4. In the evaluation step, the estimation device 12 evaluates the risk of each puddle 4 based on the temperature of the puddle 4, the depth d2 cm of the puddle 4, information about the vegetation surrounding the puddle 4, and the like. In the evaluation step, as shown in FIG. 13 , the estimation device 12 evaluates the risk of mosquito larvae 3 inhabiting the puddle 4 based mainly on three factors. For example, if any, any combination, or all of the following conditions (1) to (3) are satisfied: (1) the puddle is shallower than 50 cm (preferably 40 cm) (e.g., between 1 cm and 50 cm), (2) the water temperature is between 26° C. and 34° C., and (3) vegetation is present within a predetermined distance from the puddle, the puddle 4 is evaluated as having a high risk of larvae 3 inhabiting the puddle 4. For example, if the depth of the puddle under condition (1) is shallower than 50 cm, the risk of larvae 3 inhabiting is likely to be assessed as high based on the biological theory that the shallower the puddle, the easier it is for the water temperature to rise and the easier it is for larvae 3 to inhabit. Also, if the water temperature under condition (2) is met, the risk of larvae 3 inhabiting is likely to be assessed as high based on the biological theory that the temperature is a temperature that is easy for larvae 3 to inhabit. Also, if certain vegetation under condition (3) meets certain conditions, the risk of larvae 3 inhabiting is likely to be assessed as high based on the biological theory that vegetation tends to provide an amount of dissolved oxygen that is easy for larvae 3 to inhabit.

[0052] A puddle 4 may be evaluated as having a relatively high risk if it satisfies at least two of the conditions (1) to (3). Furthermore, a more detailed risk assessment may be performed based on these conditions, further considering the degree of deviation between the respective condition values. Furthermore, the risk assessment may be performed by quantifying the degree of risk by comprehensively considering (1) to (3). Regarding factors and conditions, additional factors and conditions, such as the distance from residential areas to the puddle, water transparency, and temperature, may be considered in addition to or in place of the existing factors. After performing the risk assessment, the estimation device 12 proceeds to S6. For example, 20 of the 200 puddles 4 initially detected were determined to have a high risk of larvae 3 inhabiting them in evaluation step S5. Therefore, insecticide spraying may be performed only on puddles 4 determined to have a high risk of larvae 3 inhabiting them. This reduces the number of workers required and reduces the cost of pesticide use and pesticide use. This saves manpower and costs, allowing LSM to be performed over a wider area and increase the number of times it can be performed, resulting in a significant effect on reducing infectious diseases. When hundreds to thousands of puddles 4 are found in aerial images, reducing the number of puddles 4 used for insecticide spraying by 60% or less, more preferably 50% or less, and even more preferably 40% or less, would have a significant effect on significantly reducing the number of workers required. Biological knowledge indicates that Anopheles mosquitoes have a limit to the distance they can fly continuously and have a tendency to prefer vertical surfaces for perching and resting. Therefore, Anopheles mosquitoes have a habit of preferring puddles around plants, which can be used as resting places during flight if there are plants nearby. Anopheles mosquitoes tend to prefer plants with vertical surfaces that are easy to perch on. Furthermore, the temperature around plants (around vegetation) is lower due to the absorption of sunlight energy through photosynthesis, and the shading effect also moderates the rise in water temperature. Therefore, areas around plants tend to be favored by mosquitoes. If vegetation is present relatively close to puddle 4, for example, if the vegetation is present within a predetermined distance (for example, 50 m) from puddle 4, it can be evaluated as being a positive factor in creating conditions favorable for the habitation of Anopheles mosquitoes.

[0053] In S6, as shown in FIGS. 7 and 11 , the estimation device 12 executes an output step S6 in which puddles 4 evaluated as high risk in the evaluation step S5 are displayed on the display device 34a of the mobile information terminal 34, distinguishing them from other puddles (e.g., puddles 4 evaluated as low risk or puddles 4 not evaluated as high risk) in the image obtained from the flying object 6. A map display function for puddles 4 is implemented in the output step S6. In FIG. 11 , among the detected puddles 4, only puddles 4 evaluated as high risk or having a certain level of risk or higher are highlighted by being surrounded by four lines 4c (approximately as if they were surrounded by a circle). In this way, the estimation device 12 has a function of highlighting puddles 4 evaluated as high risk because their risk assessment value or assessment is above a certain level, so that they can be distinguished on a predetermined image. The predetermined image is, for example, an image obtained from the flying object 6 or an image based on the obtained image. The estimation device 12 can operate application software to implement each of these functions on the application software. For example, the estimation device 12 may realize a map display function of the puddles 4 in application software that runs on the mobile information terminal 34 .

[0054] By highlighting specific puddles 4 on the image, the estimation device 12 can easily identify puddles 4 to which the pesticide should be sprayed. Furthermore, by displaying an arc-shaped line 4c that surrounds the puddle 4, the location of the puddle 4 in the image can be easily seen. Furthermore, since each puddle 4 is individually assigned an identification index, management of the puddles 4 and information registration (such as information on whether the puddles have been treated) can be easily performed. Furthermore, the estimation device 12 has a function to display puddles 4 with a risk assessment value or assessment above a certain level on the image along with the current location of the worker (the location of the mobile information terminal 34). This makes it easier for the worker F who will be spraying the puddle 4 to determine the route to take to spray the puddle 4 in the future.

[0055] Furthermore, in the output step S6, the estimation device 12 displays multiple specified puddles 4 on a relatively wide-area map (map) from an aerial perspective, as shown in FIG. 11 . This allows workers spraying pesticides to easily grasp the overall picture of the spraying operation. This also makes it easier for workers to determine the route to take to spray puddles 4. Furthermore, because puddles 4 are displayed on a map based on actual images, workers can use surrounding trees, stones, roads, etc. as landmarks, allowing for more efficient work. Furthermore, because puddles 4 are displayed on a map based on actual images, workers can identify obstacles, such as rivers or forests, in advance by looking at the image when they are on the way to puddle 4. Furthermore, directions are displayed on the screen to help workers find puddles. Furthermore, the map output in the output step S6 can be attached to reports after pesticide spraying operations, etc. are completed. Since puddles 4 are individually identified and distinguished, work completion reports can be created for each individual puddle. Therefore, the worker can submit the puddle information on the map along with the photographic evidence of spraying and receive payment. In this way, the map with puddle information 4 can be used to leave evidence and records of work, and can be used as a fair report. After executing output step S6, the estimation device 12 proceeds to END and terminates the series of control processes.

[0056] According to one embodiment of the present invention configured as described above, the mosquito breeding control program can cause a computer to execute an estimation step S4 in which the depth of the puddle 4 is estimated based on the position and size of the puddle 4 acquired in the acquisition step S2 and the temperature of the puddle 4 acquired in the temperature measurement step S3. This makes it possible to estimate the depth of the puddle 4, which is a biologically important factor in analyzing puddles 4 that are likely to be inhabited by mosquito larvae 3, and to efficiently find puddles 4 that are likely to be inhabited by mosquito larvae 3 based on images obtained from the flying object. Therefore, since puddles 4 that are likely to be inhabited by mosquito larvae 3 can be efficiently found, a limited number of workers can spray insecticide on the found puddles 4, thereby reducing the number of workers, labor, and amount of insecticide used.

[0057] According to one embodiment of the present invention configured as described above, estimation step S4 estimates the depth of puddle 4 by comparing the temperature of puddle 4 with the temperature of reference puddle 30, the size and depth of which are specified. This allows the depth of puddle 4 to be estimated with higher accuracy based on the temperature of reference puddle 30.

[0058] According to one embodiment of the present invention configured as described above, in estimation step S4, the temperature of the puddle 4 is measured at least two times at different times, and the depth of the puddle 4 is estimated based on the measured temperature change. This makes it possible to estimate the depth of the puddle 4 with higher accuracy based on the temperature change of the puddle 4. If the temperature is compared with the temperature of the reference puddle 30, the accuracy of the estimation of the depth of the puddle 4 can be further improved.

[0059] According to one embodiment of the present invention configured as described above, the mosquito breeding control program 2 further includes an evaluation step S5 for evaluating the risk of mosquito larvae 3 inhabiting the puddles 4 based on the depth of the puddles 4. This allows evaluation of puddles 4 with a relatively high risk of mosquito larvae 3 inhabiting them, based on the biological theory that the shallower the puddle 4, the easier it is for the water temperature to rise to a predetermined temperature and the more likely it is for larvae 3 to inhabit it, among the many puddles 4 in the images obtained from the flying object 6. Therefore, puddles 4 likely to be inhabited by mosquito larvae 3 can be efficiently discovered using the images obtained from the flying object 6. Furthermore, whether or not to spray insecticide on the puddles 4 can be determined depending on the degree of risk of the puddles 4, thereby further reducing the number of workers, labor, and amount of insecticide used.

[0060] According to one embodiment of the present invention configured as described above, the mosquito breeding control program 2 further includes an output step S6 for displaying on the display device 34a puddles 4 evaluated as high risk in the evaluation step S5, distinguishing them from puddles 4 evaluated as low risk in the image obtained from the flying object 6. This makes it easier for an operator spraying puddles 4 to know which puddles 4 to spray with the insecticide, thereby improving the speed and efficiency of the operator's spraying work.

[0061] According to one embodiment of the present invention configured as described above, the output step S6 of the mosquito breeding control program 2 displays the positional relationship between the position of the portable information terminal 34 having the display device 34a and the puddles 4 evaluated as high risk in the image obtained from the flying object 6. This makes it easier for the worker spraying the puddles 4 to understand the positional relationship between the portable information terminal 34 in his / her hand and the puddles 4 evaluated as high risk. For example, even if there are many puddles 4 around the worker, the worker can recognize on the map which puddles 4 to spray the insecticide on, further improving the speed and efficiency of the worker's spraying work.

[0062] According to one embodiment of the present invention configured in this manner, a computer-readable recording medium having the above-described mosquito breeding suppression program 2 recorded thereon can be used to cause a computer to execute predetermined steps, thereby efficiently detecting puddles 4 that are likely to be inhabited by mosquito larvae 3.

[0063] According to one embodiment of the present invention configured as described above, the camera 10 mounted on the flying object 6 acquires a relatively wide-area image, and the estimation device estimates the depth of the puddle 4 based on the position and size of the puddle 4 acquired by the camera 10 and the temperature of the puddle 4 measured by the temperature measurement device 8. This makes it possible to estimate the depth of the puddle 4, which is a biologically important factor in analyzing puddles 4 that are likely to be inhabited by mosquito larvae 3, and to efficiently find puddles 4 that are likely to be inhabited by mosquito larvae 3 based on the image acquired from the flying object 6. Therefore, since puddles 4 that are likely to be inhabited by mosquito larvae 3 can be efficiently found, a limited number of workers can spray insecticide on the discovered puddles 4, thereby reducing the number of workers, labor, and amount of insecticide used.

[0064] According to one embodiment of the present invention configured as described above, the flying object 6 is a fixed-wing drone. As a result, a fixed-wing drone has a longer flight range than a multicopter drone, and therefore can capture aerial images of a wider area in a single flight, enabling detection and evaluation of more puddles 4. This makes it possible to quickly discover puddles 4 that are likely to be inhabited by mosquito larvae 3 over a wide area.

[0065] According to one embodiment of the present invention configured as described above, the mosquito breeding control method includes an acquisition step S2 of acquiring the position and size of a puddle 4 in an image acquired from the flying object 6, a temperature measurement step S3 of acquiring the temperature of the puddle 4 whose position and size are measured from the flying object 6, and an estimation step S4 of estimating the depth of the puddle 4 based on the position and size of the puddle 4 acquired in the acquisition step S2 and the temperature of the puddle 4 acquired in the temperature measurement step S3. This makes it possible to estimate the depth of the puddle 4, which is a biologically important factor in analyzing puddles 4 that are likely to be inhabited by mosquito larvae 3, and to efficiently find puddles 4 that are likely to be inhabited by mosquito larvae 3, based on the image acquired from the flying object 6. Therefore, since puddles 4 that are likely to be inhabited by mosquito larvae 3 can be efficiently found, a limited number of workers can spray insecticide on the found puddles 4, thereby reducing the number of workers, labor, and amount of insecticide used.

[0066] The embodiments of the present invention are not limited to those described above, and other modifications may be applied. Various alternative embodiments and examples will be apparent to those skilled in the art based on the disclosed technology. The components of the mosquito breeding control program 2 can be freely rearranged to configure the mosquito breeding control program 2. The computer-readable recording medium can be configured to include the mosquito breeding control program 2 with the components freely rearranged. It is expressly stated that the computer-readable recording medium, mosquito breeding control system, and mosquito breeding control method may each be configured as modifications including various variations of the components of the mosquito breeding control program 2.

[0067] The technology of this embodiment can be applied to the analysis of puddles where various mosquito larvae are likely to live. Therefore, the technology of this embodiment will be specifically described, including the following examples. Mosquitoes' preferred puddle conditions, such as size and depth, may vary depending on the type of mosquito. As an example, the technology of this embodiment can also be applied to the analysis of puddles 4 where Culex tritaeniorhynchus larvae are likely to live. Culex tritaeniorhynchus may transmit Japanese encephalitis. Culex tritaeniorhynchus larvae 3 prefer to live in relatively large puddles 4 formed in rice paddies, depressions, irrigation ditches, ponds, swamps, etc. Culex tritaeniorhynchus larvae 3 can live in water temperatures lower than those in which Anopheles larvae 3 live. Furthermore, Culex tritaeniorhynchus larvae 3 can live in puddles 4 that are larger than those in which Anopheles larvae 3 live and that have a current within them. In analyzing puddles 4 that are likely to be inhabited by Culex tritaeniorhynchus larvae, the estimation device 12 may evaluate the puddle 4 as having a high risk of being inhabited by larvae 3 if any, any combination, or all of the following conditions (1) to (3) are met: (1) the puddle is deeper than 20 cm (e.g., between 20 cm and 200 cm), (2) the water temperature is between 20°C and 34°C, and (3) vegetation is present within a predetermined distance from the puddle. Note that instead of or in addition to any of the conditions, the puddle 4 may be a relatively large puddle, such as one that is larger than 500 cm x 500 cm.

[0068] As another example, the technology of this embodiment can also be applied to the analysis of puddles 4 that are likely to be inhabited by larvae of Aedes aegypti or Aedes albopictus. Aedes aegypti or Aedes albopictus may transmit dengue fever. Larvae 3 of Aedes aegypti or Aedes albopictus prefer to inhabit not only small puddles 4 formed on the ground but also extremely small puddles 4 formed in depressions in everyday objects such as water bottles, flower vases, empty cans, old tires, tree stumps, and blue tarps. Larvae 3 of Aedes aegypti or Aedes albopictus can also inhabit water temperatures higher than the water temperatures inhabited by larvae 3 of Anopheles stephensi. Therefore, in analyzing puddles 4 that are likely to be inhabited by Aedes aegypti or Aedes albopictus larvae, the estimation device 12 may evaluate the puddle 4 as having a high risk of inhabiting larvae 3 if any, any combination, or all of the following conditions are met: (1) the puddle is shallower than 30 cm (e.g., between 1 cm and 30 cm), (2) the water temperature is between 25°C and 34°C, and (3) vegetation is present within a predetermined distance from the puddle. Note that instead of or in addition to any of these conditions, the puddle 4 may be relatively small, measuring less than 30 cm x 30 cm. In this way, the technology of this embodiment can also estimate the depth of puddles preferred by mosquitoes and analyze puddles preferred by mosquitoes for other mosquito-borne infectious diseases.

Claims

1. A mosquito breeding suppression program that analyzes puddles that are likely to be home to mosquito larvae based on images obtained from an aerial vehicle, the program causing a computer to execute the following steps: an acquisition step of acquiring the position and size of the puddle in the image obtained from the aerial vehicle; a temperature measurement step of acquiring the temperature of the puddle as measured from the aerial vehicle; and an estimation step of estimating the depth of the puddle based on the position and size of the puddle acquired in the acquisition step and the temperature of the puddle acquired in the temperature measurement step.

2. The mosquito breeding control program of claim 1, wherein the estimation step of the mosquito breeding control program estimates the depth of the puddle by comparing the temperature of the puddle with the temperature of a reference puddle whose size and depth are specified.

3. The mosquito breeding control program of claim 1, wherein the estimation step of the mosquito breeding control program measures the temperature of the puddle at least two or more times at different times and estimates the depth of the puddle based on the measured temperature change.

4. The mosquito breeding control program according to claim 1, further comprising an evaluation step of evaluating a risk of mosquito larvae inhabiting the puddle based on the depth of the puddle.

5. The mosquito breeding control program of claim 4, further comprising an output step of displaying on a display device puddles evaluated as high risk by the evaluation step, distinguished from other puddles in an image obtained from the flying object.

6. The mosquito breeding control program of claim 5, wherein the output step of the mosquito breeding control program displays the positional relationship between the position of the portable information terminal having the display device and a puddle assessed to be at high risk in an image obtained from the flying object.

7. A computer-readable recording medium having the mosquito breeding control program according to any one of claims 1 to 6 recorded thereon.

8. A mosquito breeding control system that analyzes puddles which are likely to be inhabited by mosquito larvae based on images obtained from an airborne object, comprising: a airborne object that flies above the ground; a temperature measuring device attached to the airborne object; a camera attached to the airborne object; and an estimation device that estimates the depth of the puddle based on the position and size of the puddle acquired by the camera and the temperature of the puddle measured by the temperature measuring device.

9. The mosquito breeding control system of claim 8, wherein the flying object is a fixed-wing drone.

10. A mosquito breeding control method that analyzes puddles that are likely to be inhabited by mosquito larvae based on images obtained from an aerial vehicle, the mosquito breeding control method executing the following steps: acquiring the position and size of the puddle in the image obtained from the aerial vehicle; a temperature measurement step acquiring the temperature of the puddle measured from the aerial vehicle and whose position and size have been acquired; and an estimation step estimating the depth of the puddle based on the position and size of the puddle acquired in the acquisition step and the temperature of the puddle acquired in the temperature measurement step.

Images