JP2013252096A - Method for measuring seaweed bed distribution, apparatus for measuring seaweed bed distribution, program for measuring seaweed bed distribution - Google Patents

Abstract

PROBLEM TO BE SOLVED: To easily and accurately measure distribution of seaweed bed areas 6 in relation to a method for measuring seaweed bed distribution, an apparatus for measuring seaweed bed distribution, and a program for measuring seaweed bed distribution by combining image processing and echo sounding.SOLUTION: A first candidate area 2 of a seaweed bed is determined based on superiority of the g-component intensity of a pixel in an aerial color image of a measuring objective water aria, as well as a second candidate area 4 of a seaweed bed is determined based on a change in a measured depth z of water by sonic water depth detection carried out in the measuring objective water area, and by comparing the first candidate area 2 with the second candidate area 4, the coincident area of the both is estimated as a seaweed bed area 6. Also, the thick growth amount in the seaweed bed area 6 is estimated by finding an influence amount za by seaweeds based on the change of the measured water depth z, as well as finding correlation between the thick growth amounts of samples measured at a plurality of spots in the measuring objective water area and the influence amount za by the seaweeds.

Description

  The present invention relates to an algal field distribution measuring method, an algal field distribution measuring apparatus, and an algal field distribution measuring program. More specifically, the present invention relates to an algal field distribution measuring method, an algal field distribution measuring apparatus, and an algal field distribution measuring program that combine image processing and acoustic sounding.

  In recent years, the decrease in seaweed beds has become an important environmental problem, and it is necessary to accurately measure the distribution of seaweed beds in order to grasp the current situation. As a method for measuring the distribution of seaweed beds, there is a method of irradiating sound waves from the ship bottom toward the seabed and measuring the seaweed beds based on the reflected waves. This technique discriminates between the seabed and the seaweed bed based on the reflected wave because the arrival time and intensity of the reflected wave differ depending on the reflection location of the sound wave. As an ultrasonic algae measuring device that distinguishes the seabed and algae ground using sound waves, for example, there is Patent Literature 1.

  As another method, there is also a method in which a camera is submerged in water to shoot a still image or a moving image, and the distribution of seaweed beds is measured based on these images (for example, Patent Document 2).

JP-A-8-271629 JP 2002-58370 A

  However, in the former method using sound waves, absorption / scattering of sound waves may occur other than in the algae ground. In this case, it is difficult to distinguish from the algae ground, and the measurement accuracy is poor. Further, the latter method using images requires long-time image / video observation by hand, and takes time and labor for measurement.

  An object of the present invention is to provide an algal field distribution measuring method, an algal field distribution measuring apparatus, and an algal field distribution measuring program that can be measured easily and accurately.

  In order to achieve this object, the method for measuring algae field distribution according to claim 1 determines the first algae field candidate region based on the superiority of the g component intensity of the pixel in the aerial color image of the measurement target water area. In addition, the second seaweed field candidate area is determined based on the change in the measurement water depth z of the acoustic water depth survey performed on the measurement target water area, and the first seaweed field candidate area and the second seaweed field candidate area are compared. Thus, the area where both coincide is estimated as the seaweed bed area.

  In addition, the method for measuring the distribution of seaweed beds according to claim 2 obtains the influence amount za by seaweed based on the change in the measured water depth z, and the amount of sample overgrowth and the influence amount za by seaweed measured at a plurality of points in the measurement target water area. The amount of overgrowth in the seaweed bed area is estimated.

  The apparatus for measuring algae field distribution according to claim 3 determines the first algae field candidate area based on the superiority of the g component intensity of the pixel in the aerial color image of the measurement target water area. Candidate area determining means, second seaweed field candidate area determining means for determining a second seaweed field candidate area based on a change in the measured water depth z of the acoustic water depth survey performed on the measurement target water area, and the first seaweed field The candidate area and the second seaweed bed candidate area are compared, and the area where both match is defined as the seaweed bed area.

  Moreover, the seaweed bed distribution measuring apparatus according to claim 4 shows the correlation between the amount of sample overgrowth measured at a plurality of points in the measurement target water area and the influence amount za of seaweed obtained based on the change in the measured water depth z. It is provided with a means for estimating the amount of overgrowth for estimating the amount of overgrowth in the seaweed bed area.

  According to a fifth aspect of the present invention, there is provided a program for measuring a seaweed bed distribution determining means for determining a first seaweed bed candidate area based on at least the g component intensity superiority of a pixel in an aerial color image of a measurement target water area. The means for determining the second seaweed field candidate area based on the change in the measured water depth z of the acoustic water depth survey performed on the measurement target water area is compared with the first seaweed field candidate area and the second seaweed field candidate area. Thus, the computer is caused to function as a means for setting the area where both coincide with each other as a seaweed bed area.

  Furthermore, the program for measuring the distribution of seaweed beds according to claim 6 further includes the amount of sample overgrowth measured at a plurality of points in the measurement target water area and the influence amount za of seaweed obtained based on the change in the measured water depth z. The computer is made to function as a means for estimating the amount of overgrowth in the seaweed bed area by obtaining the correlation.

  In the present invention, the seaweed field area is estimated by combining both the first seaweed field candidate area determined based on the aerial color image and the second seaweed field candidate area determined based on the acoustic water depth survey. Therefore, it is possible to cancel the measurement error in the case of the aerial color image and the measurement error in the case of the acoustic water depth search, and improve the measurement accuracy. Further, the labor and time required for observing images / videos taken underwater are not required, and measurement can be performed easily.

  Moreover, this invention can estimate the amount of overgrowth of a seaweed bed area simply and with high precision.

It is a conceptual diagram which shows 1st Embodiment of the seaweed bed distribution measuring method of this invention. It is a flowchart of the same algae field distribution measuring method. It is a block diagram which shows 1st Embodiment of the seaweed bed distribution measuring apparatus of this invention. It is a conceptual diagram which shows 2nd Embodiment of the seaweed bed distribution measuring method of this invention. It is a flowchart of the same algae field distribution measuring method. It is a block diagram which shows 2nd Embodiment of the seaweed bed distribution measuring apparatus of this invention.

  Hereinafter, the configuration of the present invention will be described in detail based on the form shown in the drawings.

  1 to 3 show a first embodiment of the present invention. The seaweed field distribution measuring device includes first seaweed field candidate area determining means 3 that determines the first seaweed field candidate area 2 based on the superiority of the g component intensity of the pixels in the aerial color image of the measurement target water area 1. And second seaweed field candidate area determining means 5 for determining the second seaweed field candidate area 4 based on the change in the measured water depth z of the acoustic water depth survey performed for the measurement target water area 1, and the first seaweed field candidate The area 2 and the second seaweed field candidate area 4 are contrasted, and the seam field area estimation means 7 having the area where both coincide with each other as the seam field area 6 is provided. Moreover, the seaweed bed distribution measuring apparatus is also realized by executing the seaweed bed distribution measuring program of the present invention on a computer. In the present embodiment, an example will be described in which an algal plot distribution measurement program (hereinafter simply referred to as a measurement program) is executed on a computer.

  FIG. 3 shows the overall configuration of the algae field distribution measuring apparatus of the present embodiment for executing the measurement program. The seaweed bed distribution measuring device includes a control unit 8, a storage unit 9, an input unit 10, a display unit 11, and a connection unit 12, which are connected to each other by a signal circuit 13 such as a bus.

  The control unit 8 performs calculations related to the control of the entire seaweed field distribution measuring device and the estimation of the seaweed field area 6 by the measurement program stored in the storage unit 9, for example, a CPU (central processing unit). is there. The storage unit 9 is a device that can store at least data, programs, and the like, and is, for example, a hard disk.

  The input unit 10 is for giving at least an operator's command or the like to the control unit 8 or the like, and is, for example, a keyboard or a mouse. The display unit 11 performs display / drawing and the like under the control of the control unit 8 and is, for example, a display. The connection unit 12 is an interface for connecting external devices, such as a USB port and a card slot.

  As a means for determining the first seaweed field candidate region 2 based on the superiority of the g component intensity of the pixels in the aerial color image of the measurement target water area 1 by executing the measurement program in the control unit 8. The first seaweed bed candidate area determining unit (first seaweed bed candidate area determining means) 3, the second seaweed bed candidate area 4 based on the change in the measured water depth z of the acoustic water depth survey performed on the measurement target water area 1. The second seaweed field candidate area determining unit (second seaweed field candidate area determining means) 5 as means for determining the first seaweed field candidate area 2 and the second seaweed field candidate area 4 are compared. An algae field area estimation unit 7 (algae field area estimation means 7) is configured as a means for setting the area where both coincide with each other as the algae field area 6. In the present embodiment, an alignment processing unit 14 that aligns the aerial color image and the acoustic water depth measurement data is also configured.

  In this embodiment, the photographing device 15 for photographing an aerial color image of the measurement target water area 1 can be automatically photographed at an arbitrary time interval, or can be photographed by a ground operator remotely. The digital camera is used, but is not limited to this. Further, as a means for performing aerial photography, for example, a balloon or a flying device capable of operating a radio control (a radio control airplane, a radio control helicopter, etc.) is used. The flying device equipped with the photographing device 15 is blown over the measurement target water area 1 and photographing is performed. The aerial color image to be used may be an image obtained by dividing the measurement target water area 1 into a plurality of images and combining them into one image, or an image obtained by photographing the entire measurement target water area 1 into one image. May be used.

  An aerial color image includes a location information mark. In the present embodiment, buoys floated at a plurality of locations in the measurement target water area 1 are used as position information marks. Each buoy is provided with a position measuring device such as a GPS device, and the mooring position can be accurately measured. Further, it is preferable to provide four or more position information marks. By providing four or more position information markers, it is easy to correct the inclination of the captured image. However, two or three locations may be used when tilt correction is not required. In addition, a device other than the buoy may be used as the position information mark.

  It is preferable that the aerial color image is a photograph of the measurement target water area 1 from directly above, but it is not possible to guarantee photographing in a state where the lens of the photographing device 15 is parallel to the water surface of the measurement target water area 1. Tilt correction is performed using a position information mark imprinted on the image after shooting. The tilt correction is performed using, for example, commercially available software. The data of the aerial color image after tilt correction is supplied from the connection unit 12 to the seaweed bed distribution measuring device and stored in the storage unit 9.

  Here, the aerial color image includes a sanitary image.

  The acoustic water depth exploration is performed by navigating a measurement ship equipped with an acoustic water depth exploration device 16 and a position measuring device such as a GPS device to the measurement target water area 1. As the acoustic water depth exploration device 16, for example, a fish finder can be used, but is not limited thereto. The measurement ship may be manned or unattended and remotely operated. The measurement ship is measured while navigating vertically and horizontally with respect to the measurement target water area 1, and a two-dimensional distribution map of the measurement water depth z of the measurement target water area 1 is created. The measurement data (two-dimensional distribution diagram) is supplied from the connection unit 12 to the seaweed bed distribution measurement device and stored in the storage unit 9.

  Next, a method for measuring the distribution of seaweed beds will be described. For example, as shown in FIG. 2, the seaweed field distribution measuring method determines the first seaweed field candidate region 2 based on the superiority of the g component intensity of the pixels in the aerial color image of the measurement target water region 1 ( Together with step S32), the second seaweed field candidate area 4 is determined based on the change in the measurement water depth z of the acoustic water depth survey performed for the measurement target water area 1 (step S33). The two seam field candidate areas 4 are compared with each other, and the area where both coincide with each other is estimated as the seam field area 6 (step S34).

  First, alignment between the aerial color image and the measurement data of the acoustic water depth survey is performed (step S31). The alignment is performed by the alignment processing unit 14 reading the aerial color image data and the acoustic water depth measurement data stored in the storage unit 9.

  For the alignment, for example, a position information mark imaged in an aerial color image is used. The position (coordinate x, y) corresponding to the position information mark in the aerial color image is determined for the two-dimensional distribution map created by the acoustic water depth survey, and the coordinates of the determined position and the position information mark in the aerial color image are determined. By aligning the position coordinates, the aerial color image and the two-dimensional distribution map of the acoustic water depth survey are aligned. Then, the RGB signals (r, g, b) of the pixels of the aerial color image at the coordinates (measurement coordinates (x, y)) at which the signal wave was transmitted and received in the acoustic water depth survey and the two-dimensional distribution of the acoustic water depth survey Obtain the measured water depth z in the figure.

  Here, in order to facilitate understanding of the explanation, it is assumed that in the acoustic depth survey, the measurement ship is navigating in a lattice pattern, and signal waves are transmitted and received at regular intervals, that is, measurement coordinates (x, y). The x coordinate is 1, 2, 3,... And the y coordinate is 1, 2, 3,. The actual distance between the positions indicated by the measurement coordinates (x, y) is, for example, about 0.5 m to 1.0 m, although it depends on the speed of the measurement ship, the transmission interval of the measurement wave, and the like.

  Next, the first seaweed bed candidate area 2 is determined based on the aerial color image of the measurement target water area 1 (step S32). The determination of the first seaweed bed candidate area 2 is performed by the first seaweed bed candidate area determination unit 3. In the aerial color image, the seaweed field appears in a greenish color, so the RGB signal of the pixels in that area has a superior (larger) g (green) component intensity than the b (blue) component intensity and r (red) component intensity. become. For each pixel of measurement coordinates (x, y), the measurement coordinates (x, y) in which the g component intensity of the RGB signal is superior to the b component intensity and the r component intensity are set as candidate coordinates, and the set is a first seaweed bed candidate. Region 2 is assumed. As a result, a region captured in a green color in the aerial color image can be extracted as the first seaweed bed candidate region 2.

  In this embodiment, as a determination of whether or not the g component strength is superior, a comparison is made with the b component strength, and when the g component strength is greater than the b component strength, it is determined that the g component strength is superior. That is, gb = (g component strength) ÷ (b component strength) is calculated, and it is determined that the g component strength is superior when gb> 1.0. However, the threshold value of gb is not limited to 1.0.

  However, the determination of the superiority of the g component strength is not limited to this. For example, the comparison with the r component strength (g component strength> r component strength) and the comparison between the b component strength and the r component strength (g component strength> b component strength and g component strength> r component strength) Also good. At this time, it may be determined based on a simple magnitude relationship (for example, g component strength> b component strength, gb> 1.0, etc.), or whether the magnitude relationship is greater than or equal to a predetermined value (for example, whether gr (= g component intensity / r component intensity) is equal to or greater than a predetermined threshold S1 (eg, 3.65, etc.), or whether the magnitude relationship is within a certain range. (For example, bg (= b component intensity ÷ g component intensity) may be determined based on a predetermined threshold S2 to a threshold S3 (for example, a range of S2 = 0.635, S3 = 0.665, etc.)).

  Next, the second seaweed bed candidate region 4 is determined based on the change in the measured water depth z by the acoustic water depth exploration (step S33). The second seaweed bed candidate area determining unit 5 determines the second seaweed bed candidate area 4. The area where the seabed does not exist and the sea bottom continues has almost no inclination, and the measured water depth z does not change greatly. On the other hand, in the seaweed bed, the signal wave from the acoustic water depth exploration device 16 is greatly scattered and absorbed compared to the seabed, and the water depth becomes shallow due to the height of the seaweed. And very different. Therefore, the seabed and the seaweed bed can be discriminated based on the change in the measured water depth z.

  First, for the measurement coordinates (1, 1), (1, 2), (1, 3),. If the measurement water depth z of the measurement coordinates (1, 1) is z11, the measurement water depth z of the measurement coordinates (1, 2) is z12, the measurement water depth z of the measurement coordinates (1, 3) is z13,. The sequence Z1 of the measurement water depth z of each measurement coordinate of = 1 is (z11, z12, z13,...).

  Then, for the sequence Z1, the nth measured water depth [zn] is compared with the (n-1) th measured water depth [z (n-1)], and [zn]-[z (n-1)]. <The nth measured water depth [zn] which becomes A1 is determined as the measured water depth zs of the reflected signal from the seabed. Here, A1 is a threshold value for discrimination, for example, 0.1 (m), but is not limited thereto. Since the water depth hardly changes in the region where the seabed continues, when [zn] and [z (n-1)] are substantially the same value, that is, when [zn]-[z (n-1)] <A1. It can be determined that the measurement coordinate (1, n) is the seabed, and the measurement water depth z of the measurement coordinate (1, n) is the measurement water depth zs of the reflected signal from the sea floor. On the other hand, in cases other than the above ([zn] − [z (n−1)] ≧ A1), it can be determined that the measurement coordinates (1, n) are seaweed beds. For example, when z13−z12 <A1, it is determined that the measurement coordinates (1, 3) are the seabed.

  Such determination is made for the measurement coordinates (1, 1), (1, 2), (1, 3),... With x coordinate = 1, and the y coordinate of the measurement coordinates (1, y) determined to be the seabed. And a measured water depth zs (for example, expressed as zs = ay + b). This correlation formula is referred to as a first correlation formula. The first correlation formula indicates the depth of water zs passing through the measurement coordinates (1,1), (1,2), (1,3),... With x coordinate = 1. The depth of water is shown, and the seaweed bed is the depth of the seabed where seaweed grows.

  Next, for each of the measurement coordinates (1, 1), (1, 2), (1, 3),... With x coordinate = 1, the y coordinate is substituted into the first correlation formula, Obtain the depth of the seabed zs. Then, for each of the measurement coordinates (1, 1), (1, 2), (1, 3),... With x coordinate = 1, the obtained water depth zs of the seabed and the measurement water depth z (apparent) of the measurement coordinates. The difference za from the water depth) (since the top of the algae is higher than the seabed of the algae ground, za = z−zs) is obtained. This za is the difference between the measured water depth z affected by the seaweed and the water depth zs of the seabed where the seaweed grows, and is referred to as an influence amount za by the seaweed. The influence amount za due to seaweed may be a value other than 0 for the seabed portion that is not a seaweed bed due to an error in the first correlation equation or the like. Thus, the influence amount za by seaweed is obtained for each of the measurement coordinates (1, 1), (1, 2), (1, 3),. .

  The processing performed for the measurement coordinate of x coordinate = 1 is also performed for x coordinate = 2, 3,..., And the influence amount za by seaweed is obtained for all measurement coordinates (x, y). Then, the measurement coordinates (x, y) satisfying the influence amount za> A2 by seaweed are set as candidate coordinates, and the set is set as a second seaweed bed candidate region 4. Here, A2 is a threshold value for discrimination, for example, 0.1 (m), but is not limited thereto. If za is affected by seaweed, the value becomes a certain size, and if za is not affected by seaweed, the value is small (about the error of the first correlation equation). It is considered to be. Therefore, if za> A2, it is affected by seaweed, and it can be determined that the measurement coordinates (x, y) are seaweed beds.

  Next, the first seaweed field candidate area 2 and the second seaweed field candidate area 4 are compared to estimate the area where both coincide with each other as the seaweed field area 6 (step S34). The seaweed area 6 is estimated by the seaweed area estimation unit 7. In step S32, the measurement coordinates (x, y) of gb> 1.0 are set as the first seaweed field candidate area 2, and in step S33, the measurement coordinates (x, y) of za> A2 are set as the second seaweed field candidate area. Four. Therefore, the measurement coordinates (x, y) satisfying (gb> 1.0) and (za> A2) are the coordinates where both coincide with each other, and the collected seaweed bed area 6 is defined. Thereby, distribution of the seaweed bed area 6 can be calculated | required. The obtained distribution of the seaweed bed area 6 is stored in the storage unit 9 and displayed on the display unit 11.

  In the discriminant of gb> 1.0 in step S32, for example, an area captured in a green color in an aerial color image can be discriminated, but an object having the same color as the algae field, for example, an algae field Can not be distinguished (first error). On the other hand, soft seabeds, bumpy stones, garbage, etc. appear in aerial color images in colors other than green, so they can be distinguished from seaweed beds.

  In addition, the influence amount za of seaweed obtained in step S33 is not necessarily all caused by seaweed, but causes scattering / absorption of measurement waves other than seaweed, such as soft seabed, uneven goro stone, garbage There is also a possibility that the measured water depth z is increased or decreased (second error) due to the influence. Therefore, the second error cannot be excluded from the discriminant of za> A2 in step S33. On the other hand, seaweed that is not rooted in the seafloor such as Aosa can be distinguished by acoustic water depth exploration because the measured water depth z is clearly different from the seaweed bed.

  In the present invention, the algae field region 6 is estimated by combining both the first algae field candidate area 2 obtained in step S32 and the second algae field candidate area 4 obtained in step S33. The first error in the case of using the image and the second error in the case of the acoustic water depth exploration can be canceled, and the seaweed bed area 6 can be accurately measured.

  Further, the labor and time required for observing images / videos taken underwater are not required, and measurement can be performed easily.

  The present invention is particularly suitable for the measurement of seaweed beds composed of seaweeds without bubbles (for example, sea bream, arame, seaweed, seaweed, kombu, etc.), and are composed of seaweeds with bubbles (for example, Honda Walla). It is not very suitable for measuring seaweed beds. In other words, seagrass with bubbles are not very suitable for measurement by acoustic depth exploration because the reflection of acoustic waves at acoustic depth is too strong, but seaweed without bubbles appropriately scatters and absorbs acoustic waves at acoustic depth. Therefore, it is easy to distinguish from the seabed and is suitable for measurement by acoustic depth survey, and is particularly suitable for application of the present invention.

  Next, a second embodiment to which the present invention is applied will be described with reference to FIGS. In addition, about the component same as the component of 1st Embodiment, the same code | symbol is attached | subjected and those detailed description is abbreviate | omitted.

  In the first embodiment, the seaweed basin area 6 is simply obtained, but in this embodiment, the amount of overgrowth of the algae basin area 6 is further estimated. Here, examples of the amount of overgrowth include the average number n per unit area, the average height h of seaweed, and the total weight tw per unit area of seaweed, but are not limited thereto.

  The algae field distribution measuring device of this embodiment further shows the correlation between the amount of sample overgrowth measured at a plurality of points in the measurement target water area 1 and the influence amount za of seaweed obtained based on the change in the measured water depth z. The amount of overgrowth estimation means 17 which estimates the amount of overgrowth of the seaweed bed area 6 is provided. That is, by executing the measurement program on the computer, the control unit 8 causes the influence amount of the seaweed obtained based on the sample overgrowth amount measured at a plurality of points in the measurement target water area 1 and the change in the measured water depth z. An overgrowth amount estimation unit (overgrowth amount estimation means) 17 for estimating the overgrowth amount of the seaweed bed area 6 by obtaining a correlation with za is configured.

  In this embodiment, since the influence amount za by seaweed about each measurement coordinate (x, y) is already calculated | required by the 2nd seaweed bed candidate area | region determination part 5, this is utilized.

  The amount of sample overgrowth is obtained in advance by a field survey and is stored in the storage unit 9 in advance. The field survey is performed as follows, for example, but is not limited thereto. The investigator dive into the site water area, set a sampling area with a unit area at the position corresponding to the measurement coordinates (x, y) of the acoustic water depth survey in the seaweed bed, the number n of seaweed in the sampling area, the average height While measuring h, the total weight tw of the seaweed in the sampling area is measured. The total weight tw is measured by, for example, collecting a predetermined number of seaweeds as a sample for weight measurement, measuring the weight, and converting the weight to the number of weights in the sampling region to obtain the total weight tw. For example, a 50 cm × 50 cm square frame is installed in the sea cucumber ground, and the number n and height of sea eels in the frame are measured, and the average height h is calculated. The eel is collected and weighed, and this weight is converted into the weight of the number n in the frame to obtain the total weight tw.

  Then, such a sampling survey is performed in a plurality of sampling areas, and the number n of seaweeds, the average height h of seaweeds, and the total weight tw of seaweeds are calculated for each sampling area. These sample overgrowth amounts are stored in advance in the storage unit 9 in association with the corresponding measurement coordinates (x, y).

  Next, a method for measuring the distribution of seaweed beds will be described. In the present embodiment, after the seaweed bed area 6 is obtained in step S34, the influence amount za of seaweed obtained based on the sample overgrowth amount measured at a plurality of points in the measurement target water area 1 and the change in the measured water depth z. And the amount of overgrowth in the seaweed bed area 6 is estimated (step S35). The overgrowth amount estimation of the seaweed bed area 6 is executed by the overgrowth amount estimation unit 17 reading the sample overgrowth amount and the influence amount za of seaweed from the storage unit 9.

  The influence amount za by seaweed is a value generated by scattering and absorption of signal waves by seaweed, and becomes larger as the seaweed grows more. A correlation equation between the influence amount za of the seaweed and the actual overgrowth of the seaweed is obtained. Since the sample survey of the amount of overgrowth is performed at a plurality of locations, a correlation formula between the amount of influence za caused by seaweed and the amount of overgrowth of the sample can be obtained. That is, a sampling survey is performed on the number of measurement coordinates (x, y) that can obtain the correlation equation. In the present embodiment, three items are set as the amount of overgrowth, the number n of seaweeds, the average height h of seaweeds, and the total weight tw of seaweeds. Therefore, a correlation equation is obtained for each item. For example, n = c · za + d (correlation equation for the number n of seaweeds, hereinafter referred to as a second correlation equation), h = e · za + f (correlation equation for the average height h of seaweeds) , Hereinafter referred to as a third correlation formula), tw = g · za + i (correlation formula for the total weight tw of seaweeds, hereinafter referred to as a fourth correlation formula).

  Then, by substituting the influence amount za into each of the second to fourth correlation expressions, the amount of overgrowth at the measurement coordinates (x, y) of the influence amount za is obtained. And the amount of overgrowth is calculated | required about each measurement coordinate (x, y) in the seaweed bed area 6, respectively. Thereby, the distribution of the amount of overgrowth can be calculated | required. The obtained amount of overgrowth is stored in the storage unit 9 and displayed on the display unit 11.

  In the above description, the number of seaweeds n, the average height h of seaweeds, and the total weight tw of seaweeds are all obtained as the amount of overgrowth, but it is not always necessary to obtain all of them, either one or two You may ask for one.

  Moreover, you may make it not employ | adopt the amount of overgrowth about a thing with low correlation R among the 2nd-4th correlation formula. By not adopting those having a low correlation R, the measurement reliability can be further increased. For example, the correlation R is larger than the threshold value 0.9. However, the adoption threshold value is not limited to 0.9, and is appropriately determined according to the required degree of reliability.

  The above-described embodiment is an example of a preferred embodiment of the present invention, but is not limited thereto, and various modifications can be made without departing from the scope of the present invention.

  For example, in the above description, since the resolution of the aerial color image is high or the shooting altitude is low, and another pixel corresponds to each position (measurement point) where signal waves are transmitted and received in the acoustic water depth survey, Processing is performed using the coordinates of each measurement point in water depth exploration as measurement coordinates (x, y), but the resolution of the aerial color image is low or the imaging altitude is high, and multiple measurement points overlap the same pixel. In some cases, the processing may be performed by thinning out the measurement points.

DESCRIPTION OF SYMBOLS 1 Measurement target water area 2 1st seaweed field candidate area 3 1st seaweed field candidate area determination means 4 2nd seaweed field candidate area 5 2nd seaweed field candidate area determination means 6 Seaweed field area 7 Seaweed field area estimation means 17 Overgrowth estimation means

Claims (6)

  The first seaweed bed candidate region is determined based on the superiority of the g component intensity of the pixel in the aerial color image of the measurement target water area, and the change in the measurement water depth z of the acoustic water depth exploration performed on the measurement target water area. A second seaweed field candidate area is determined based on the first seam field candidate area and the second seaweed field candidate area, and a region where both coincide with each other is estimated as a seaweed field area. A method for measuring the distribution of seaweed beds.   The amount of influence za by seaweed is obtained based on the change in the measured water depth z, and the correlation between the amount of sample overgrowth measured at a plurality of points in the measurement target water area and the amount of influence za by the seaweed is obtained to obtain the seaweed area. 2. The method for measuring the distribution of seaweed beds according to claim 1, wherein the amount of overgrowth is estimated.   First seaweed field candidate area determining means for determining the first seaweed field candidate area based on the superiority of the g component intensity of the pixel in the aerial color image of the measurement target water area, and the sound performed on the measurement target water area Second seaweed field candidate area determining means for determining a second seaweed field candidate area based on a change in the measured water depth z of the water depth exploration, the first seaweed field candidate area and the second seaweed field candidate area, A seaweed bed distribution measuring apparatus comprising a seaweed bed area estimating means that compares the two and sets a region where both coincide with each other as a seaweed bed area.   The amount of sample overgrowth measured at a plurality of points in the measurement target water area and the influence amount za of seaweed obtained based on the change in the measured water depth z is obtained to estimate the overgrowth quantity in the seaweed bed area. 4. The seaweed bed distribution measuring device according to claim 3, further comprising an overgrowth amount estimating means.   Means for determining a first seaweed bed candidate region based on at least the g component intensity superiority of the pixels in the aerial color image of the measurement target water area, and the measurement water depth z of the acoustic water depth exploration performed on the measurement target water area A means for determining a second seaweed field candidate area based on the change of the first seam field candidate area and the second seaweed field candidate area, and comparing the two areas as a seaweed field area A program for measuring the distribution of seaweed beds for causing a computer to function as a means to perform.   Further, the amount of overgrowth in the seaweed bed area is obtained by obtaining the correlation between the amount of sample overgrowth measured at a plurality of points in the measurement target water area and the influence amount za of seaweed obtained based on the change in the measured water depth z. The program for measuring algae distribution according to claim 5 for causing a computer to function as the estimating means.

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