Turbidity evaluation method and turbidity evaluation system

Abstract

To provide a turbidity evaluation method and a turbidity evaluation system capable of quantitatively grasping an influence range of planarly spreading turbidity.SOLUTION: A turbidity evaluation system 1 for evaluating turbidity of a water area includes an air vehicle 2 as water surface image acquisition means for photographing a water surface of the water area, and a turbidity evaluation device 3 for creating a turbidity distribution from a water surface image photographed by the air vehicle 2. The turbidity evaluation device 3 creates the turbidity distribution on the basis of correlation data indicating a correlation between the information on the color or brightness of the water area and the degree of turbidity, the information on the color or brightness is a difference in color or brightness with reference to a pixel value of a portion not affected by turbidity, and the correlation data is created in association with one or both of the color and illuminance of the water area at the time of photographing.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a turbidity evaluation method and a turbidity evaluation system for evaluating the turbidity of a water body. [Background technology]

[0002] In marine construction work that generates turbidity due to landfilling, dredging, etc., it is necessary to monitor turbidity daily to ensure that turbidity-related items (e.g., turbidity, SS (suspended solids), etc.) do not exceed set standard values, with the aim of preserving the ecosystem and marine environment. Turbidity monitoring is generally performed by measuring turbidity and SS at monitoring points several times a day. One example of technology related to turbidity monitoring is the technology described in Patent Document 1. The technology described in Patent Document 1 uses a Doppler current meter to determine underwater turbidity. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2007-071881 Summary of the Invention [Problem to be solved by the invention]

[0004] The method of measuring turbidity using a measuring instrument, as in Patent Document 1, is not suitable for determining the turbidity over a wide area. In other words, the actual turbidity generated by offshore construction work spreads over a surface due to the overlap of multiple point sources and past residues, so measurements using a measuring instrument are point-based measurements, which poses the problem of not being able to fully grasp the turbidity generated by offshore construction work. While increasing the number of measurement points can provide planar information, this requires a great deal of effort.

[0005] From this perspective, the present invention provides a turbidity evaluation method and a turbidity evaluation system that can quantitatively grasp the extent of the influence of turbidity that spreads over a surface. [Means for solving the problem]

[0006] The turbidity evaluation method according to the present invention is a method for evaluating the turbidity of a water body. This turbidity evaluation method includes a water surface image acquisition step of photographing the water surface of the water body, and a turbidity evaluation step of creating a turbidity distribution from the water surface image photographed in the water surface image acquisition step. In the turbidity evaluation step, the turbidity distribution is created based on correlation data that indicates the correlation between information about the color or brightness of the water body and the degree of turbidity. The information about color or brightness is the difference in color or brightness when pixel values ​​of an area not affected by turbidity are used as a reference. The correlation data is created in association with one or both of the color and illuminance of the water body at the time of photographing.

[0007] The turbidity evaluation method according to the present invention evaluates the degree of turbidity from a water surface image captured of a water body. Therefore, it is possible to quantitatively grasp the extent of the impact of turbidity that spreads over a surface without performing measurements at multiple points in the water body using measuring instruments. Furthermore, rather than directly determining the degree of turbidity from pixel values ​​(e.g., RGB values) of the turbidity-affected area, the degree of turbidity is determined based on correlation data that indicates the correlation between information about the color or brightness of the water body and the degree of turbidity. Therefore, even if the appearance of color varies depending on the date, time, weather, etc., the method is less susceptible to such influences. Furthermore, the correlation data is created in association with one or both of the color and illuminance of the water body at the time of image capture. Therefore, the correlation data corresponds to the actual water body and image capture conditions, enabling accurate evaluation of the degree of turbidity.

[0008] The correlation data may be created corresponding to a plurality of colors, a plurality of illuminances, or a plurality of colors and a plurality of illuminances. In this case, in the turbidity evaluation step, one piece of correlation data is selected based on one or both of the color and the illuminance of the water body at the time of photographing, and the selected correlation data is used to create the turbidity distribution. This makes it easy to adapt to changes in the environment and shooting conditions during shooting.

[0009] The method may further include a correlation data creation step of creating the correlation data. In the correlation data creation step, a plurality of sample images are taken of a non-turbid water sample and a turbid water sample having different degrees of turbidity, with one or both of a background color that imitates the color of the water body and illuminance being changed. Then, the correlation data is created from the plurality of sample images, which are associated with one or both of the background color and the illuminance.

[0010] In the water surface image acquisition step, the water surface may be photographed from an aircraft flying above the water area, which makes it easy to photograph the water surface image.

[0011] The turbidity evaluation system according to the present invention is a system for evaluating the turbidity of a water body. This turbidity evaluation system includes a water surface image acquisition means for photographing the water surface of the water body, and a turbidity evaluation device for creating a turbidity distribution from the water surface image photographed by the water surface image acquisition means. The turbidity evaluation device creates the turbidity distribution based on correlation data that indicates the correlation between information about the color or brightness of the water body and the degree of turbidity. The information about color or brightness is the difference in color or brightness when pixel values ​​of an area not affected by turbidity are used as a reference. The correlation data is created in association with one or both of the color and illuminance of the water body at the time of photographing.

[0012] The turbidity evaluation system according to the present invention evaluates the degree of turbidity from a water surface image captured of a water body. Therefore, it is possible to quantitatively grasp the extent of the impact of turbidity that spreads over a surface without performing measurements at multiple points in the water body using measuring instruments. Furthermore, rather than directly determining the degree of turbidity from pixel values ​​(e.g., RGB values) of the turbidity-affected area, the system determines the degree of turbidity based on correlation data that indicates the correlation between information about the color or brightness of the water body and the degree of turbidity. Therefore, even if the appearance of color varies depending on the date, time, weather, etc., the system is less susceptible to such influences. Furthermore, the correlation data is created in association with one or both of the color and illuminance of the water body at the time of image capture. Therefore, the correlation data corresponds to the actual water body and image capture conditions, enabling accurate evaluation of the degree of turbidity. [Effects of the Invention]

[0013] According to the present invention, it is possible to quantitatively grasp the area affected by turbidity. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a configuration diagram of a turbidity evaluation system according to an embodiment of the present invention. [Figure 2] 1 is an example of a flowchart illustrating the overall steps of a turbidity evaluation method according to an embodiment of the present invention. [Figure 3] 10 is an example of a flowchart illustrating a process for creating correlation data. [Figure 4] 1 is an example of a flowchart illustrating a process for evaluating turbidity. [Figure 5] This is an example of a turbid water sample in which the concentration (content) of bottom sediment material was gradually changed. [Figure 6] This is an example of a sample created using a turbid water sample. [Figure 7] 1A and 1B are diagrams for explaining sample images, in which (a) is an example of a sample image, and (b) shows the characteristics of the sample. [Figure 8] 1 is an example of a graph showing the relationship between color difference and turbidity. [Figure 9A]1 is an example of a graph showing the relationship between color difference and turbidity. [Figure 9B] 1 is an example of a graph showing the relationship between color difference and turbidity. [Figure 9C] 1 is an example of a graph showing the relationship between color difference and turbidity. [Figure 10] 10 is a combination example of creating correlation data. [Figure 11] These are images of correlation data for different illumination levels when the ocean is green and blue, where (a) shows the case when the background color is blue, and (b) shows the case when the background color is green. [Figure 12] This is an example of correlation data obtained in a demonstration test. [Figure 13] 10 is an example of a water surface image. [Figure 14] 10 is an example of illuminance data. [Figure 15] FIG. 10 is a diagram illustrating an example of selection of correlation data. [Figure 16] 10 is an example of correlation data. [Figure 17] 1 is an example of a turbidity distribution diagram. DETAILED DESCRIPTION OF THE INVENTION

[0015] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. Each drawing is merely a schematic illustration to allow a sufficient understanding of the present invention. Therefore, the present invention is not limited to the illustrated examples. In each drawing, common or similar components are designated by the same reference numerals, and redundant explanations thereof may be omitted.

[0016] <Regarding the Turbidity Evaluation System According to the Embodiment> The configuration of a turbidity evaluation system 1 according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a configuration diagram of the turbidity evaluation system 1 according to an embodiment.

[0017] The turbidity evaluation system 1 shown in FIG. 1 is a system for evaluating the turbidity of a water area to be monitored. In this embodiment, the monitoring object is assumed to be the ocean, and an explanation will be given assuming a case where the turbidity of a specific sea area due to offshore construction work is to be evaluated. Note that the monitoring object may be other than the ocean (for example, a lake, pond, river, etc.), and the cause of turbidity is not limited to offshore construction work. The cause of turbidity may also be, for example, wastewater from a factory. In this embodiment, turbidity is calculated as the degree of turbidity.

[0018] The turbidity evaluation system 1 mainly comprises an air vehicle 2 having a photographing function and a turbidity evaluation device 3 capable of communicating with the air vehicle 2. Note that the configuration of the turbidity evaluation system 1 shown in Fig. 1 is merely an example and is not limited to that shown in Fig. 1. For example, the system may have a device that relays communication between the air vehicle 2 and the turbidity evaluation device 3, or a separate device may be provided that stores some or all of the information stored by the turbidity evaluation device 3.

[0019] (Aircraft configuration) The aircraft 2 has a flight function and can fly above the water area to be monitored. The aircraft 2 flies above the water area to be monitored and photographs the water surface of the water area from above. The aircraft 2 is, for example, a drone, and flies under remote control using a controller or based on pre-set control. The aircraft 2 mainly comprises an image capture unit 21, a communication unit 22, and a control unit 23. Note that the aircraft 2 in this embodiment is an example of a "water surface image acquisition means."

[0020] The photographing unit 21 is, for example, a digital camera, and is capable of photographing color images (digital images having RGB values). The photographing unit 21 is installed at the bottom of the flying object 2. The communication unit 22 is configured by a network interface or the like, and transmits and receives data to and from the turbidity evaluation device 3. The communication unit 22 transmits the captured image to the turbidity evaluation device 3. The control unit 23 is composed of a CPU (Central Processing Unit) and peripheral devices, and controls the overall processing operations of the aircraft 2 (including flight, photography, and communication).

[0021] (Configuration of Turbidity Evaluation Device) The turbidity evaluation device 3 has a calculation function and evaluates the turbidity of the water area to be monitored based on photographed images of the water surface. The installation location of the turbidity evaluation device 3 is not particularly limited, and it may be portable. The turbidity evaluation device 3 may be, for example, a server, a personal computer (PC), a tablet terminal, a smartphone, etc. The turbidity evaluation device 3 has correlation data that serves as a standard for evaluating the turbidity of the water area, and evaluates the turbidity using the correlation data and the photographed images.

[0022] The turbidity evaluation device 3 mainly includes a storage unit 31 , a communication unit 32 , and a control unit 33 . The storage unit 31 is configured with a non-volatile memory or the like (for example, a hard disk drive (HDD) or a solid state drive (SSD)). The storage unit 31 stores programs and various data required for evaluating the turbidity of a water body. The storage unit 31 stores, for example, a turbidity evaluation program, correlation data, water surface images, illuminance data, etc.

[0023] The turbidity evaluation program is a program for causing a computer to execute the turbidity evaluation method. The correlation data is information that indicates the correlation between information about the color or brightness of the water body and the degree of turbidity (e.g., turbidity). The information about color or brightness is the difference in color or brightness (e.g., color difference) when pixel values ​​of areas not affected by turbidity are used as a reference. The correlation data is created in association with one or both of the color and illuminance of the water body at the time of photographing. The correlation data may be created in association with multiple colors, multiple illuminances, or multiple colors and multiple illuminances. In this case, one correlation data is selected based on one or both of the color and illuminance of the water body at the time of photographing. The correlation data is registered in advance by the administrator who manages the turbidity evaluation system 1 or by personnel involved in marine construction work.

[0024] The water surface image is an image of the water surface of the body of water, and is a color image (a digital image having RGB values). The water surface image is captured by the aircraft 2, and the image transmitted from the aircraft 2 is stored. The illuminance data is the illuminance of the water body measured at the time of photographing. Instead of actual measurement, the illuminance at the time of photographing may be estimated from information related to illuminance. For example, in this embodiment, instead of measuring the illuminance, the illuminance is estimated from the global solar radiation amount from AMeDAS.

[0025] The communication unit 32 is configured with a network interface or the like, and transmits and receives data to and from the aircraft 2. The communication unit 32 receives captured images from the aircraft 2. The control unit 33 is configured by a CPU (Central Processing Unit) and peripheral devices, and controls the processing operations of the turbidity evaluation device 3 (including image analysis, turbidity evaluation, and communication) in an integrated manner.

[0026] <Method for evaluating turbidity according to the embodiment> A turbidity evaluation method according to an embodiment will be described with reference to Fig. 2 (and Fig. 1 as appropriate). Fig. 2 is an example of a flowchart showing the overall steps of the turbidity evaluation method according to an embodiment. In this embodiment, the description will be made assuming a case where turbidity evaluation is carried out targeting turbidity that occurs in a construction area, such as in pile driving work.

[0027] The turbidity evaluation method according to the embodiment mainly includes a correlation data creation step S10, an image acquisition step S20, and a turbidity evaluation step S30. The correlation data creation step S10 is a preliminary step, while the image acquisition step S20 and the turbidity evaluation step S30 are actual monitoring steps. The correlation data creation step S10 may be performed for each offshore construction site, or, if the sea area characteristics (e.g., bottom sediment characteristics, water depth, seawater color, etc.) are similar between sites, the results of the correlation data creation step S10 performed in one offshore construction project can be used in another offshore construction project. The image acquisition step S20 and the turbidity evaluation step S30 are performed, for example, several times a day during the offshore construction project.

[0028] <Correlation data creation process "S10"> The correlation data creation step S10 will be described with reference to Fig. 3. Fig. 3 is a flowchart showing an example of the correlation data creation step S10. The correlation data creation step S10 mainly includes a turbid water creation step S11, a sample image acquisition step S12, an image color difference calculation step S13, and a correlation data plotting and approximation step S14.

[0029] (Muddy water creation process "S11") In the turbid water creation step S11, turbid water with gradually varying turbidity (degree of turbidity) is created. Each turbid water recreates the turbidity that occurs in the water area being monitored. For example, pure water and substances that cause turbidity are used to create liquid turbid water of different concentrations. Instead of pure water, tap water, water obtained from the water area being monitored, clean water, etc. may be used. When turbidity that occurs in a construction area, such as during pile driving work, is anticipated, turbid water should be created using bottom sediment material (e.g., soil or sand) from the construction area. If it is not possible to collect bottom sediment material from the construction area, turbid water may be created using bottom sediment material with similar color, mineral composition, etc.

[0030] For example, if the source of the turbid water is bottom sediment in the construction area, the bottom sediment is collected in advance and used to create the turbid water. In this embodiment, we assume that the turbidity does not settle completely even after time has passed and remains for a while. In other words, we target particles with small particle sizes and slow settling speeds. Therefore, the collected bottom sediment is sieved through a 75 μm sieve, and bottom sediment with particle sizes less than 75 μm is used to create the turbid water. Turbidity is set to a maximum of several hundred mg / L, and turbid water is created in six to eight levels. Turbidity levels that require attention during construction can be set, and the turbid water can be created to include these levels.

[0031] The turbid water samples we created are shown in Figure 5. Figure 5 shows an example of a turbid water sample in which the concentration (content) of bottom sediment material was changed in stages. From left to right, the concentrations are 13, 27, 45, 57, 85, 102, and 192 mg / L.

[0032] (Sample image acquisition process "S12") In the sample image acquisition step S12, a sample is created using the turbid water sample created in the turbid water creation step S11, and an image of the sample (referred to as a "sample image") is acquired. The sample is a reproduction of the turbidity that occurs in the water area to be monitored, and includes non-turbid water samples made of pure water only (tap water, wash water, etc. are also possible), and turbid water samples with different degrees of turbidity. The image is preferably taken, for example, from directly above the sample in order to capture the color of the sample image. The sample image is, for example, an RGB image.

[0033] When photographing, we take into consideration factors that affect the color of images acquired in the construction area. Factors that affect the color of the sample image include the "color of the turbid water" and the "color and brightness of the sea area." The color of the sea area is the original color of the sea before turbid water reaches it, and the factors that determine this vary depending on the water depth, transparency, and type of seabed (rock, mud, etc.), but the result of these interrelated factors is reflected in the color of the sea area image. Since the construction area is generally an area of ​​about "several hundred meters" square, we assume that the color of the sea within the construction area is uniform. Brightness changes depending on the season, weather, and time of day, and affects the brightness of the image.

[0034] A specific example of the sample image acquisition step S12 is as follows: Tap water and turbid water of different turbidities are placed in transparent containers measuring approximately 30 cm long x 30 cm wide x 20 cm high. Figure 6 shows an example of a sample. Eight samples make up one set. In other words, Figure 6 illustrates two sets of samples. The bottom sediment material differs between the first and second sample sets. In each sample set, the sample located at the bottom right is a non-turbid water sample made from tap water, and the other samples are turbid water samples. Color plates are placed under the samples to take into account the color of the sea area.

[0035] The sample image 51 will be described with reference to Figure 7. Figure 7 is a diagram for explaining the sample image, where (a) is an example of a sample image and (b) shows the sample characteristics (density and color difference). Note that the sample image 51 shown in Figure 7 is actually a color image (a digital image with RGB values). The sample image 51 was repeatedly captured by changing the color of the color plate and the capture time. This allows it to be adapted to the water area being monitored or the capture conditions when actually capturing that water area. Here, we used color plates with a green color characteristic of a closed bay and a blue color characteristic of the open sea. It is also possible to use color plates with colors such as dark green or emerald green to match the actual color of the sea. Furthermore, to change the brightness during capture, images were captured at different times on different days. As an indicator of brightness, the illuminance at the same height as the surface of the sample was measured.

[0036] (Image color difference calculation process "S13") In the image color difference calculation step S13, the color difference is calculated using the sample image 51 captured in the sample image acquisition step S12. The color difference is an index that numerically represents the difference between two colors, and can be calculated using the following formula (1). In this embodiment, one of the two colors for which the color difference is to be calculated is used as a reference color, and the color difference from the reference color is calculated. The reference color is the color of clear water. In formula (1), "R0, G0, B0" are the RGB values ​​of the reference color, and "R1, G1, B1" are the RGB values ​​of the other color. ·Color difference C= ((R1-R0) 2 +(G1-G0) 2 +(B1-B0) 2 ) (1 / 2) ...Equation (1)

[0037] An example of a color difference calculation method is explained using Figure 7. The sample image 51 shown in Figure 7(a) is an image of containers filled with turbid water of varying densities from "1" to "7" and a green plate placed inside each container to represent the color of the ocean. The container with a density of "0" contains tap water. The illuminance at the time of capture was approximately 31,420 lx. The average RGB values ​​of the tap water area 51a and the turbid water area 51b in the sample image 51 shown in Figure 7(a) are calculated. Areas containing shadows or reflections within the areas 51a and 51b are excluded. The average RGB values ​​of the tap water area 51a in Figure 7(a) are defined as "R0, G0, B0," and the color difference is calculated using the average RGB values ​​of each turbid water area 51b. The calculated color difference and the concentration within each container are shown in Figure 7(b). The top row shows sample identification information, the middle row shows the concentration of each sample, and the bottom row shows the color difference calculated using Equation (1).

[0038] (Graphing and approximating correlation data process "S14") The color difference and turbidity data shown in Figure 7(b) are graphed as shown in Figure 8. Figure 8 is a graph showing the relationship between color difference and turbidity. The relationship between color difference and turbidity can be approximated by a curve such as an exponential function, where the range of change in turbidity increases as the color difference increases. Using a similar process, approximate curves (correlation data) for each case are obtained using images with different ocean colors (bottom plate colors) and illuminances. Examples of graphs showing the relationship between color difference and turbidity other than that shown in Figure 8 are shown in Figures 9A to 9C. Figure 9A shows data for bottom sediment A with different illuminances for the blue background. Figure 9B shows data for bottom sediment A with different illuminances for the green background. Figure 9C shows data for bottom sediment B with different illuminances for the green background.

[0039] Figure 10 shows an example of a combination for creating correlation data. Figure 11 shows an image of correlation data when the color of the sea is green and blue and the illuminance is different. Figure 10(a) shows the case when the color of the sea (background color) is blue, and (b) shows the case when the color of the sea (background color) is green. Figure 12 is an example of correlation data obtained in a demonstration test.

[0040] <Image acquisition process "S20"> In the image acquisition step S20 shown in FIG. 2, an image of the water surface of the water area to be monitored is taken at an actual marine construction site.

[0041] A specific example of the image acquisition step S20 is as follows: The air vehicle 2 (for example, a drone) captures images of the sea surface directly below at the timing when turbidity occurs during construction or at a predetermined time. The image capture range includes areas where the turbidity has not reached and the original sea color is visible. For example, when turbidity occurs, 10 images are captured at 30-second intervals over a 5-minute period. Although a single image can be used, considering the possibility of extreme reflections or short-term shadows (clouds), it is desirable to capture several images in a short period of time to obtain an image of the average situation at that time.

[0042] An example of an acquired water surface image is shown in Figure 13. The water surface image 71 shown in Figure 13 is actually a color image (a digital image with RGB values). In the water area shown in Figure 13, a fence 72 has been installed to create an area within the water area that is not affected by turbidity. The fence 72 is intended to prevent turbid water from flowing out, and is composed of, for example, a float part that floats on the water surface and a curtain part that hangs down from the float part. The curtain part is made of, for example, polyester.

[0043] In addition, illuminance is measured at sea level when photographing the water surface. Instead of actual measurement, illuminance at the time of photographing may be estimated from information related to illuminance. In this embodiment, instead of measuring illuminance, illuminance is estimated from global solar radiation. Global solar radiation at the time of photographing is obtained from past data from AMeDAS, and global solar radiation is converted to illuminance. The relationship between global solar radiation and illuminance was determined, for example, by reference to "Planning Journal of the Architectural Institute of Japan, Vol. 526, pp. 17-24, December 1999." The estimated illuminance data is shown in FIG. 14.

[0044] <Turbidity evaluation process "S30"> In the turbidity evaluation step S30 shown in Fig. 2, turbidity is evaluated from the acquired water surface image 71. As shown in Fig. 4, the turbidity evaluation step S30 mainly includes a correlation data selection step S31 and a conversion step S32 from image data to turbidity.

[0045] (Correlation data selection process "S31") In the correlation data selection step S31, the "ocean color" and "illuminance" of the acquired water surface image 71 are determined, and correlation data is selected based on these determinations. The ocean color is the color of the area in the same image where turbidity has not occurred (reached). For example, an area where turbidity has not occurred is selected by visually inspecting the image. Using the water surface image 71 shown in FIG. 13, this is a position outside the area surrounded by the fence 72, and the RGB values ​​of this position are confirmed. In this example, the RGB values ​​were "60, 90, 85." Here, "green" was selected as the color with the smallest color difference between the GB value of the point where turbidity has not occurred (reached) and the GB value of the color plate (green and blue) used to create the correlation data.

[0046] Regarding illuminance, the illuminance data at the time of shooting is checked from the graph in Figure 14, and an "illuminance" close to the illuminance data created from the correlation data is determined. An example of correlation data selection is shown in Figure 15. Figure 15 is a diagram showing an example of correlation data selection. In this example, the illuminance at the time of shooting of the water surface image 71 was "41000 [lx]", so "40000 [lx]" is determined to be the closest to the illuminance at the time of shooting from the illuminances of "20000, 40000, 80000 [lx]" of the created green correlation data.

[0047] (Process "S32" for converting image data into turbidity) The image data to turbidity conversion step S32 is a step of converting the acquired water surface image 71 into turbidity. Using the correlation data selected in the correlation data selection step S31, each pixel of the captured water surface image 71 is converted into turbidity. Here, the conversion into turbidity is performed using the approximation formula (correlation data) shown in Figure 16 obtained in the same step as above. Figure 16 is an example of correlation data.

[0048] This creates a turbidity distribution diagram 81 for turbidity, for example, as shown in Figure 17. By displaying the turbidity distribution diagram 81 in Figure 17, it is possible to evaluate, for example, that the turbidity in the area surrounded by the dotted line is about 15 mg / L. The created turbidity distribution diagram 81 is displayed on a terminal used by, for example, personnel involved in marine construction work. Photographs of the water surface and the distribution may be created at predetermined time intervals, and the spread and movement of turbidity may be displayed in chronological order.

[0049] As described above, the turbidity evaluation method according to this embodiment evaluates the degree of turbidity from a water surface image 71 (see FIG. 13) captured of a water body. Therefore, the extent of the influence of turbidity, which spreads over a surface, can be quantitatively grasped without performing measurements at multiple points in the water body using measuring instruments. Furthermore, the degree of turbidity is not directly determined from pixel values ​​(e.g., RGB values) of the turbidity-affected area, but is determined based on correlation data (see FIG. 12) that indicates the correlation between information about the color or brightness of the water body and the degree of turbidity. Therefore, even if the appearance of color varies depending on the date, time, weather, etc., the method is less susceptible to such influences. Furthermore, the correlation data is created in association with one or both of the color and illuminance of the water body at the time of capture. Therefore, the correlation data corresponds to the actual water body and capture conditions, enabling accurate evaluation of the degree of turbidity.

[0050] Although the embodiment of the present invention has been described above, the present invention is not limited to this and can be practiced within the scope of the claims. In the embodiment, the turbidity was calculated from the sample image 51 and the water surface image 71 using color difference. However, it is also possible to use values ​​related to color or brightness other than color difference (for example, luminance or brightness). Since both are proportional to turbidity, it is possible to use the difference in brightness instead of the color difference in the evaluation method described in the embodiment. [Explanation of symbols]

[0051] 1. Turbidity evaluation system 2. Aircraft (means for acquiring water surface images) 3 Turbidity evaluation device 21 Photography Department 22 Communications Department 23 Control Unit 31 Storage section 32 Communications Department 33 Control Unit 51 Sample images 71 Water surface images 81 Turbidity distribution map

Claims

1. A turbidity evaluation method for evaluating the turbidity of a water body, comprising: a water surface image acquisition step of photographing the water surface of the water area; a turbidity evaluation step of creating a turbidity distribution from the water surface image taken in the water surface image acquisition step, In the turbidity evaluation step, the turbidity distribution is created based on correlation data indicating a correlation between information about the color or brightness of the water body and the degree of turbidity; The information about color or brightness is a difference in color or brightness when a pixel value of a portion not affected by turbidity is used as a reference, The correlation data is created in association with one or both of the color and the illuminance of the water body at the time of photographing. A method for evaluating turbidity.

2. the correlation data is created in association with a plurality of colors, a plurality of illuminances, or a plurality of colors and a plurality of illuminances; In the turbidity evaluation step, one piece of correlation data is selected based on one or both of the color and the illuminance of the water body at the time of photographing, and the turbidity distribution is created using the selected correlation data. The method for evaluating turbidity according to claim 1 .

3. The method further includes a correlation data creation step of creating the correlation data, In the correlation data creation step, a plurality of sample images are taken of a non-turbid water sample and a turbid water sample having different degrees of turbidity, with one or both of a background color simulating the color of the water body and illuminance changed, and the correlation data corresponding to one or both of the background color and the illuminance are created from the plurality of sample images. The method for evaluating turbidity according to claim 2 .

4. 2. The turbidity evaluation method according to claim 1, wherein the water surface image acquisition step involves photographing the water surface from an aircraft flying above the water area.

5. A turbidity evaluation system for evaluating the turbidity of a water body, comprising: a water surface image acquisition means for capturing an image of the water surface of the water area; a turbidity evaluation device that creates a turbidity distribution from the water surface image taken by the water surface image acquisition means, the turbidity evaluation device creates the turbidity distribution based on correlation data indicating a correlation between information about the color or brightness of the water body and the degree of turbidity; The information about color or brightness is a difference in color or brightness when a pixel value of a portion not affected by turbidity is used as a reference, The correlation data is created in association with one or both of the color and the illuminance of the water body at the time of photographing. A turbidity evaluation system characterized by:

Images