JP2013228261A - Method for estimating bottom material of water bottom - Google Patents

Abstract

PROBLEM TO BE SOLVED: To estimate a bottom material of a water bottom of a sea, a river, a lake, etc., by directly utilizing water depth data obtained by a three-dimensional side scan sonar etc.SOLUTION: There is provided a method for gathering reflection intensity of an ultrasonic wave and depth sounding data at many positions in a water bottom survey object water area using a sonar and estimating a bottom material from the gathered reflection intensity and depth sounding data by using a computer, the method including dividing the depth sounding data in the water area which is gathered using the sonar into grating-shaped sections, selecting sections whose bottom materials are to be estimated out of all the sections as divisions, calculating average values of depths of water for each of the selected sections, calculating a gradient of a water bottom from a difference in water depth from an adjacent section, and selecting a bottom material corresponding to the calculated gradient by reference to a table containing correspondence relation between gradients and bottom materials of water bottoms.

Description

  The present invention relates to a method for estimating the bottom sediment of a sea, a river, a lake and the like using a computer.

  As conventional techniques for estimating the bottom sediment of the seabed, there are a bottom survey device using a single beam sonar and a bottom survey device using a multi-beam sonar.

  For example, Patent Documents 1 to 3 are water bottom exploration devices using a single beam sonar, which transmits an ultrasonic pulse signal directly underwater and receives a reflection signal to detect a school of fish, The present invention relates to a so-called fish detector, which is used to determine the bottom sediment using the correspondence between the time width of the received reflected signal and the bottom sediment.

  In Patent Document 1, the time width of the received reflected signal is divided by the time from transmission of the ultrasonic pulse signal to reception, and normalized by the water depth to determine the bottom sediment.

  In Patent Document 2, the reception sensitivity for detecting a school of fish is different in the detection sensitivity for bottom sediment discrimination and for fish school detection in order to prevent the reflected signal from the seabed from being saturated. The directivity angle of the transmitter / receiver is used as a parameter for bottom sediment discrimination.

  Further, in Patent Document 3, the time width of the ultrasonic pulse signal to be transmitted is adjusted so as to be proportional to the seabed depth, and the time width of the reflected signal is extracted at a time interval proportional to the seabed depth, or the seabed depth is determined. The characteristic amount is obtained from the time width of the reflected signal using a value proportional to the signal width, and the bottom sediment is discriminated using a neural network.

Next, Patent Document 4 shows an example of a water bottom exploration device using a multi-beam sonar.
In this device, a plurality of received beams are formed with respect to an ultrasonic signal transmitted in a range of a predetermined angle in the seafloor direction, water depth data and reflected intensity data in the received beam direction are detected from the received signal, and the hull The sea bottom normal direction converted value of the reflection intensity data is calculated using the information on the position, bow direction, etc. and the water depth data.

The correspondence between the converted value of the seafloor normal direction of the reflection intensity data and the bottom sediment is stored in advance as a table as shown in FIG. 11, and is thus calculated using this stored correspondence. In addition, the bottom sediment is estimated from the converted value of the seafloor normal direction of the reflection intensity data. This correspondence is set in advance from known documents, or is set according to the result of previous sediment detection.
Note that the water bottom exploration device of Patent Document 4 is a so-called cross fan beam type device in which the spreading direction of the ultrasonic signal to be transmitted and the spreading direction of the received beam are orthogonal to each other.

  By the way, the three-dimensional side, which has a swath width wider than that of the cross-fan-beam-type water bottom exploration device and is capable of exploring water bottom topography with sharp and vertical undulations, which was difficult with the conventional method. Scan sonar is being used for bottom exploration.

  This three-dimensional side scan sonar has a configuration in which a plurality of receivers are provided for a common transmitter, and the difference in the arrival time of reflected waves to these receivers (position) This is a multi-beam type bottom exploration device that can calculate the angle at which the reflected wave arrives from the phase difference) and thus calculate the water depth. In other words, this three-dimensional side scan sonar is highly accurate by performing calculations using the CAATI (Computed Angle-of-Arrival Transient Imaging) algorithm developed by Paul H. Kraeutner and John S. Bird of Simon Fraser University. At low noise, reflection intensity data and water depth data can be obtained at each point within a wide exploration width. This CAATI algorithm is described in Patent Document 5, for example. The three-dimensional sounding system using this three-dimensional side scan sonar has been added to the NETIS (New Technology Information System) by the Ministry of Land, Infrastructure, Transport and Tourism “Technical name: Three-dimensional sounding technology system in extremely shallow water by C3D” -090015).

Japanese Patent No. 3088557 Japanese Patent No. 3450661 JP 2008-275351 A Japanese Patent No. 4585838 US Pat. No. 6,130,641

Takayuki Kumada, Takaaki Uta, Masumi Serizawa; “Contour and Grain Size Change Model Considering Equilibrium Gradient according to the Predominant Particle Size Group”, JSCE Proceedings B, Japan Society of Civil Engineers, June 2007, Vol. 63, no. 2, p. 154-167

Conventionally, it has not been possible to estimate bottom sediment by directly using water depth data obtained by a three-dimensional side scan sonar or the like.
An object of the present invention is to provide a method for estimating sediment by directly using such water depth data.

That is, in the present invention, in order to solve the above-mentioned problems, ultrasonic sonar reflection intensity and depth measurement data are collected at a number of positions in the water base exploration target water area using sonar, and the collected reflection intensity data and depth measurement data are collected. A method for estimating sediment using a computer,
The method
Correlating the water depth data of the depth measurement data with each section obtained by dividing the survey target water area into a grid in unit area;
Selecting a segment for estimating sediment from all the segmented segments;
Calculating an average value of water depth data for each selected category;
Calculating a difference between the average values of adjacent sections in a selected section and dividing the result by a distance between the centers of the adjacent sections to calculate a bottom gradient;
A method for estimating the bottom sediment by computer processing comprising the step of selecting a bottom sediment corresponding to the calculated gradient with reference to a table storing a correspondence relationship between the bottom gradient and the bottom sediment. It is what we propose.

Further, in the present invention, in the above configuration, a step of calculating a value indicating the degree of dispersion of water depth data for each selected section is provided,
A method for estimating the bottom sediment of a water bottom provided with a step of selecting a bottom sediment corresponding to the calculated value indicating a dispersion degree with reference to a table storing a correspondence relationship between a value indicating a dispersion degree and a bottom sediment suggest.

  Further, the present invention proposes a method for estimating the bottom sediment of the water bottom in which the classification of the bottom sediment in the above-described configuration is all sections obtained by dividing the search target water area into a grid pattern with a unit area.

  Further, in the present invention, in the above configuration, the classification for estimating the bottom sediment is a classification in which the target water area is divided into a grid pattern with a unit area, and is selected in a grid pattern at a predetermined interval. A method for estimating the bottom sediment quality is proposed.

  In the present invention, in the above configuration, it is proposed that the value indicating the degree of dispersion is a variance or a standard deviation value, or a range or a quartile range.

Further, in the present invention, in the above configuration, a step of calculating an average value of ultrasonic reflection intensity data for each category for estimating sediment,
Referring to a table storing the correspondence between the reflection intensity of ultrasonic waves and the bottom sediment, estimating the bottom sediment of the water bottom provided with a step of selecting the bottom sediment corresponding to the average value of the calculated reflection intensity data Suggest a method.

In the present invention, in the above configuration, the bottom sediment selected corresponding to the reflection intensity data is compared with the bottom sediment selected corresponding to the water depth data, and the estimated bottom sediment is output. A step to perform
In this step, if the compared bottom sediments match, the bottom sediment is output as the estimated bottom sediment, and if not, the selected bottom sediment corresponding to the reflection intensity data is given priority. A method for estimating the bottom sediment of the bottom of the water is proposed.

In the present invention, in the above configuration, the bottom sediment selected corresponding to the reflection intensity data is compared with the bottom sediment selected corresponding to the water depth data, and the estimated bottom sediment is output. A step to perform
In this step, if the compared bottom sediments match, the bottom sediment is output as the estimated bottom sediment, and if not, both bottom sediments are output as the estimated bottom sediment. Then, we propose a method for estimating the bottom sediment quality to notify the operator of the fact to that effect.

  In the present invention, it is proposed that, in the above configuration, the sonar is a three-dimensional side scan sonar.

  The present invention collects ultrasonic reflection intensity data and depth measurement data at a number of locations in the water base exploration target water area by sonar, and estimates the sediment using a computer from the collected reflection intensity data and depth measurement data. The depth data of the depth measurement data is associated with each section obtained by dividing the exploration target water area into a grid by unit area, and a section for estimating sediment is selected from all divided sections, and selected. The average value of the water depth data can be calculated for each section, and the difference between the average values of the adjacent sections can be divided by the distance between the centers of the adjacent sections to calculate the slope of the water bottom.

  By the way, it is known that the bottom sediment has a corresponding relationship with the presence or absence of the bottom and the degree of the slope, that is, the slope. For example, Non-Patent Document 1 states that “the steep slope near the shoreline contains a lot of gravel and coarse sand, while the offshore gentle slope has a high content of fine sand, silt and viscosity. As shown in Fig.3, it was found that the particle size range of the bottom sediment that constitutes the steep slope and the gentle slope is large. ", And the relationship between the bottom slope and bottom sediment is described. You can see that

  This is not necessarily the case because it is a natural phenomenon, but as a typical example, when the bottom of the water has a steep slope, mud, sand, and gravel tend to fall downward. It is assumed that the bottom sediment is often exposed with rocks. On the other hand, if the bottom of the water is flat or has a gentle slope, mud, sand, etc. dropped from above will accumulate and stay, so the bottom of the bottom of the water, such as a gentle slope, is often assumed to be mud or sand. Is done. In addition, if the bottom of the water has the above-mentioned intermediate slope, it is easy to fall if it is steep, but if it is a certain slope, gravel that is harder to fall than mud or sand remains, so if the bottom of the water is intermediate, It is assumed that it is often a sediment that is coarser than the bottom of the water and retains gravel.

  Therefore, if the correspondence between the bottom gradient and the bottom sediment is stored in advance as a table, the bottom sediment corresponding to the bottom gradient calculated as described above is obtained for the section of the survey target water area. Once selected, the selected bottom sediment can be output as an estimate of the bottom sediment of the corresponding segment.

  The bottom sediment changes not only by the slope, but also by various conditions such as sea area, coastal topography, the presence of rivers, ocean currents, etc. The correspondence between the gradient and the bottom sediment can be obtained and stored as a table, and the bottom of the bottom sediment can be constructed in consideration of these parameters.

  When considering the parameters in this way, the correspondence between the gradient of the bottom of the water and the bottom sediment is stored as a table for each parameter, and the parameters can be input by the operator of the computer. Corresponding processing can be performed by the computer by providing a step of selecting a table correspondingly.

  As described above, the unit area that divides the exploration target water area into a grid is determined according to the size of the exploration target water area and the information such as the bottom sediment that is assumed in advance by other materials and knowledge. It is desirable to set the area so that the bottom sediment does not substantially change.

  In addition, the classification for estimating the sediment may be all the sections obtained by dividing the exploration target water area in a grid pattern, or may be a section that is selected in a predetermined interval from all sections and arranged in a grid pattern. In the latter section arrangement, it is desirable that the distance between the centers of the adjacent sections is set to a distance within which the bottom sediment does not change substantially.

  Next, in this invention, the value which shows the dispersion | distribution degree of many water depth data is calculated for every division selected as mentioned above. The dispersion degree of the water depth data indicates the degree of unevenness of the bottom of the water due to the sediment, and it is assumed that the bottom of the water is smoother as the dispersion degree is smaller. Therefore, it is possible to estimate the bottom sediment of a desired section from the calculated dispersion of the water depth data using a table storing the correspondence relationship between the dispersion of the water depth data and the sediment stored in advance.

  Here, as described above, the bottom sediment estimated corresponding to the gradient of the bottom of the water is the bottom sediment due to the elements constituting the bottom of the water, such as mud, sand, gravel, and rock, from the small gradient side. On the other hand, since the bottom sediment estimated from the dispersion of the water depth data is the bottom sediment due to the surface shape of the bottom, as estimated from the small side of the dispersion, it is smooth and uneven. It can be output as bottom sediment combined with bottom sediment.

  For example, if the calculated slope of the bottom is small and the degree of dispersion is small, the elements that make up the bottom are mud and sand, which can be output as smooth, while the calculated bottom When the gradient is small but the dispersion is large, the elements that make up the bottom of the water are mainly mud and sand, but some rocks and so on protrude and can be output if they are bumpy.

  The value indicating the degree of dispersion of the water depth data can be, for example, a variance or standard deviation value, a range or a quartile range, and the correspondence between at least one of these values and the bottom sediment can be stored as a table. It ’s fine.

  Next, in the present invention, in addition to estimating the bottom sediment from the water depth data as described above, for example, a conventional method as described in Patent Document 4, for example, the ultrasonic reflection intensity data and the bottom sediment. The bottom sediment can be estimated from the corresponding relationship, and these can be combined to estimate the bottom sediment.

  At this time, if the bottom sediment estimated from the water depth data and the bottom sediment estimated from the reflection intensity data are different, it is estimated from the correspondence relationship between the reflection intensity data and the bottom sediment widely used in the past. By giving priority to the bottom sediment and outputting it as an estimated bottom sediment, and simultaneously notifying the operator of that fact, the operator can examine the output result as necessary.

  In addition, when the bottom sediment estimated from the water depth data and the bottom sediment estimated from the reflection intensity data are different, both bottom sediments are output as the estimated bottom sediment and at the same time to the computer operator. By notifying, the operator can examine the output result as necessary.

  As the sonar used in the above method, the above-described three-dimensional side scan sonar is appropriate.

FIG. 1 is an explanatory view schematically showing the operation of a three-dimensional side scan sonar used in the method of the present invention. FIG. 2 shows a part of the depth measurement data obtained by the three-dimensional side scan sonar, which is data after performing data correction such as fluctuation correction, sound speed correction, filter processing, noise removal and the like. FIG. 3 shows a water area corresponding to the depth measurement data of FIG. FIG. 4 shows an example in which the classification for estimating sediment is selected from all the classified sections. The sections indicated by hatching in the figure correspond to the sections surrounded by the one-dot chain line in FIG. is there. FIG. 5 is a flowchart showing the positioning of the process according to the method of the present invention. FIG. 6 is a flowchart showing the flow of processing from the water depth data in the depth measurement data until the bottom sediment is output by the method of the present invention. FIG. 7 is a flowchart showing the flow of processing from the dispersion of the water depth data in the depth measurement data to the output of the bottom sediment by the method of the present invention. FIG. 8 is a flowchart showing the flow of processing until the bottom sediment is output from the reflection intensity data and the depth measurement data by the method of the present invention. FIG. 9 is a flowchart showing another flow of processing until the bottom sediment is output from the reflection intensity data and the depth measurement data by the method of the present invention. FIG. 10 schematically shows an example of a table storing the correspondence between the gradient and the bottom sediment. FIG. 11 schematically shows an example of a table storing a correspondence relationship between values indicating the degree of dispersion of water depth data and sediment. FIG. 12 schematically shows an example of a table storing the correspondence between the reflection intensity data and the bottom sediment.

  Hereinafter, embodiments of the present invention will be described in detail.

  FIG. 1 is an explanatory view schematically showing the operation of the three-dimensional side scan sonar, which is shown in a plane orthogonal to the moving direction of the side scan sonar main body 1. The side scan sonar main body 1 is provided with a plurality of wave receivers for a common wave transmitting section (not shown). That is, reference numerals 2a and 2b are wave receiving portions provided on the left and right sides of the side scan sonar main body 1, and a plurality of, for example, six wave receivers are provided in the height direction in these wave receiving portions 2a and 2b. The angle at which the reflected wave arrives is calculated from the difference in arrival time (phase difference) of the reflected wave to those receivers using the CAATI algorithm described above, and therefore, with high accuracy, With low noise, reflection intensity data and water depth data can be obtained at each depth measurement point 4 within a wide exploration width. In the figure, reference numeral 3 is the bottom of the water, 4 is a depth measurement point, 5 is the direction of transmission of the ultrasonic signal, 6 is the wavefront, and 7 is the wave receiving state of the reflected wave.

The performance of this three-dimensional side scan sonar is exemplified as follows.
Frequency: 200kHz
Range (beam): 25-300m (one side)
Measurement range: 5-8 times the water depth Resolution: 4.5cm
Sounding resolution: 5.5cm
Number of depth measurement points: Up to 2000 points

FIG. 2 shows a part of the depth measurement data obtained by the three-dimensional side scan sonar, which is data after performing data correction such as shake correction, sound speed correction, filter processing, noise removal, and the like. Can be appropriately processed. And FIG. 3 shows the water area corresponding to the depth measurement data of FIG. ² , and the area of the section surrounded by the alternate long and short dash line in the figure is 1 m ² , and the data included in it is the data number of FIG. This is the data previously indicated by the symbol ◆.

  As shown in FIG. 5, in the method of the present invention, the bottom sediment is estimated by performing computer processing from ultrasonic reflection intensities and depth measurement data at a number of locations in the water survey target water area collected by the three-dimensional side scan sonar. Then, this is output, and as a next process, a bottom sediment classification map creation process or the like is performed. An embodiment of the processing method of the present invention will be described next.

FIG. 6 is a flowchart showing the flow of processing from the water depth data in the depth measurement data until the bottom sediment is output by the method of the present invention.
First, in step S1, the depth data of the depth measurement data is made to correspond to each division obtained by dividing the search target water area into a grid by unit area, and then in step S2, a classification for estimating sediment is selected from all the divided classifications. .

Fig. 4 shows an example of classification. In this example, the surveyed water area is divided into a grid pattern with division 8 with a unit area of 1 m ² , and the sediment is estimated by selecting a division every 10 m from all the divisions. Category 8E. In the figure, twelve sections 8E are shown, and these are distinguished by subscripts as necessary.

  Next, in step S3, the average value of the water depth data is calculated for each selected section 8E, the difference between the water depth data of the adjacent sections in the section selected in step S4 is calculated, and the distance between the centers of the adjacent sections is calculated. Divide by to calculate the slope of the bottom (in this case, the average slope).

For example, when the bottom gradient corresponding to the section 8E ₅ is obtained, the distance between the adjacent surrounding sections 8E ₁ , 8E ₂ , 8E ₃ , 8E ₄ , 8E ₆ , 8E ₇ , 8E ₈ , 8E ₉ is determined. The gradient corresponding to each direction can be obtained by performing the calculation in step S4.

  As mentioned above, it is known that the bottom sediment has a corresponding relationship with the presence or absence of the bottom and the degree of the slope, that is, the slope. Then, since mud, sand, and gravel easily fall downward, it is assumed that rocks are often exposed on the bottom of steep water bottoms. On the other hand, if the bottom of the water is flat or has a gentle slope, mud, sand, etc. dropped from above will accumulate and stay, so the bottom of the bottom of the water, such as a gentle slope, is often assumed to be mud or sand. Is done. In addition, if the bottom of the water has the above-mentioned intermediate slope, it is easy to fall if it is steep, but if it is a certain slope, gravel that is harder to fall than mud or sand remains, so if the bottom of the water is intermediate, It is assumed that it is often a sediment that is coarser than the bottom of the water and retains gravel.

  Therefore, the correspondence relationship between the bottom G and the bottom sediment is stored in advance as a table, for example, the table shown in FIG. 10, and is calculated in step S4 for all the survey area 8E in step S5. The bottom sediment is selected from the gradient G, and the selected bottom sediment is output in step S6.

  Next, FIG. 7 is a flowchart showing the flow of processing from the water depth data in the depth measurement data to the bottom sediment output by the method of the present invention. This process estimates the bottom sediment from both the bottom gradient and the dispersion of the water depth data.

  First, in step S11, the depth data of the depth measurement data is made to correspond to each division obtained by dividing the search target water area into a grid pattern by unit area, and then in step S12, a classification for estimating sediment is selected from all the divided classifications. . These steps S11 and S12 are the same as steps S1 and S2 described above.

  Next, in step S13, the average value of the water depth data and the degree of dispersion, for example, the standard deviation are calculated for each selected section 8E.

  Next, in step S14, as in step S4 described above, in the selected section 8E, the difference between the water depth data of the adjacent sections is calculated and divided by the distance between the centers of the adjacent sections to calculate the bottom G of the bottom G. To do.

  Here, as described above, the dispersion degree of the water depth data indicates the degree of unevenness of the bottom of the water due to the sediment, and it is assumed that the lower the dispersion condition, the smoother the water bottom. Therefore, if the correspondence between the degree of dispersion of the water depth data and the bottom sediment is stored as, for example, the table shown in FIG. 11, the bottom sediment of the desired section can be estimated from the degree of dispersion of the calculated water depth data. .

  Therefore, in step S15, the bottom sediment calculated in step S14 is selected with reference to the table of FIG. 10 in which the correspondence between the bottom sediment and the bottom sediment is stored, and the water depth data calculated in step S13 is scattered. From the value indicating the condition, in this case, the value of the standard deviation, the bottom sediment can be selected with reference to the table of FIG.

  Here, as described above, the bottom sediment estimated corresponding to the gradient of the bottom of the water is the bottom sediment due to the elements constituting the bottom of the water, such as mud, sand, gravel, and rock, from the small gradient side. On the other hand, since the bottom sediment estimated from the dispersion of the water depth data is the bottom sediment due to the surface shape of the bottom, as estimated from the small side of the dispersion, it is smooth and uneven. It is possible to output as bottom sediment combining bottom sediments.

  For example, if the calculated slope of the bottom is small and the degree of dispersion is small, the elements that make up the bottom are mud and sand, which can be output as smooth, while the calculated bottom When the gradient is small but the dispersion is large, the elements that make up the bottom of the water are mainly mud and sand, but some rocks and so on protrude and can be output if they are bumpy.

  Next, FIG. 8 is a flowchart showing the flow of processing from the reflection intensity data and the depth measurement data to the bottom sediment output by the method of the present invention. In this flow, the reflection intensity data and the depth measurement data are data-corrected in the same manner as the reflection intensity data and the depth measurement data in FIG.

  Step S22 is a process corresponding to S1 to S6 in FIG. 6 or S11 to S16 in FIG. Step S21 is a process of selecting and outputting the bottom sediment for each reflection intensity data using the table shown in FIG. 12 storing the correspondence between the reflection intensity and the bottom sediment.

  In step S23, the bottom sediment A selected corresponding to the reflection intensity data in step S21 is compared with the bottom sediment B selected corresponding to the water depth data in step S22.

  As a result of the comparison, when the bottom sediment A and the bottom sediment B coincide with each other, the bottom sediment A or the bottom sediment B is output in step S24. On the other hand, as a result of the comparison, if the bottom sediment A and the bottom sediment B are different, in step S25, the bottom sediment A selected in accordance with the reflection intensity data that has been widely used and has a large amount of data accumulated in the past is selected. While outputting, notification that bottom sediment A and bottom sediment B are different is performed.

  For this reason, since the operator of the computer can know that the bottom sediment A and the bottom sediment B are different, in the bottom sediment classification diagram creation process shown in FIG. 5, the core sampler, dredge, It is possible to discriminate sediment using other judgment materials by collecting data using a mud collector.

  Next, FIG. 9 is a flowchart showing the flow of processing until the bottom sediment is output from the reflection intensity data and the depth measurement data according to the method of the present invention. This processing flow is the processing of step S25 in the flow shown in FIG. Is changed to the process of step S26.

  That is, in this flow, when the bottom sediment A and the bottom sediment B are different as a result of the comparison in step S23, both the bottom sediment A and the bottom sediment B are output in step S26, and the bottom sediment A and the bottom sediment are output. Notification that quality B is different.

  For this reason, the computer operator can know that the bottom sediment A and the bottom sediment B are different and how they are different. Therefore, in the bottom sediment classification diagram creation process shown in FIG. On the other hand, it becomes possible to discriminate sediment using other judgment materials by collecting data using a core sampler, a dredge, a mud collector, or the like.

  In the present invention described above, when “C3D” published in the NETIS is used as a sonar, the data of the oscillation state at that time is recorded in this sonar for each oscillation (Ping). Therefore, the reflected intensity data can be effectively corrected using the receiver gain and the pulse length in the recorded data.

  The present invention is as described above, and it is possible to estimate the bottom sediments of the sea, rivers, lakes and the like by directly using the water depth data obtained by the three-dimensional side scan sonar.

1 side scan sonar body 2a, 2b wave receiver 3 underwater 4 bathymetry point 5 transmitting direction 6 wavefront 7 reflected wave 8E (8E ₁ ~8E ₁₂₎ Category

Claims (10)

This method uses ultrasonic sonar to collect ultrasonic reflection intensity and sounding data at a number of locations in the target area of the seafloor exploration, and estimates the bottom sediment using a computer from the collected reflection intensity data and sounding data. And
The method
Correlating the water depth data of the depth measurement data with each section obtained by dividing the survey target water area into a grid in unit area;
Selecting a segment for estimating sediment from all the segmented segments;
Calculating an average value of water depth data for each selected category;
Calculating a difference between the average values of adjacent sections in a selected section and dividing the result by a distance between the centers of the adjacent sections to calculate a bottom gradient;
The bottom of the bottom of the water is characterized in that the bottom of the bottom of the water is obtained by a computer process comprising a step of selecting a bottom corresponding to the calculated slope with reference to a table storing the correspondence between the bottom slope and the bottom sediment. Quality estimation method. Providing a step of calculating a value indicating the degree of dispersion of the water depth data for each selected section;
A step of selecting a bottom sediment corresponding to the calculated value indicating the dispersion state with reference to a table storing a correspondence relationship between the value indicating the dispersion state and the bottom sediment is provided. Estimation method of sediment. The method for estimating the bottom sediment according to claim 1 or 2, wherein the classification for estimating the bottom sediment is all sections obtained by dividing the survey target water area into a grid pattern with a unit area. The classification for estimating bottom sediment is a classification that is selected in a grid-like manner at a predetermined interval from all the sections obtained by dividing the search target water area in a grid pattern by unit area. The estimation method of the bottom sediment of the water bottom of 2. The method for estimating bottom sediment according to claim 2, wherein the value indicating the degree of dispersion is a variance or a standard deviation value. The method for estimating the bottom sediment according to claim 2, wherein the value indicating the degree of dispersion is a range or a quartile range. Calculating an average value of ultrasonic reflection intensity data for each category for estimating bottom sediment;
And a step of selecting a bottom corresponding to the average value of the calculated reflection intensity data with reference to a table storing a correspondence relationship between ultrasonic reflection intensity and bottom sediment. Item 7. The method for estimating bottom sediment according to any one of Items 1 to 6. Providing a step of comparing the bottom sediment selected corresponding to the reflection intensity data with the bottom sediment selected corresponding to the water depth data, and outputting the estimated bottom sediment;
In this step, if the compared bottom sediments match, the bottom sediment is output as the estimated bottom sediment, and if not, the selected bottom sediment corresponding to the reflection intensity data is given priority. 8. The method for estimating bottom sediment according to claim 7, wherein the bottom sediment is output as the estimated bottom sediment and the operator of the computer is notified to that effect. Providing a step of comparing the bottom sediment selected corresponding to the reflection intensity data with the bottom sediment selected corresponding to the water depth data, and outputting the estimated bottom sediment;
In this step, if the compared bottom sediments match, the bottom sediment is output as the estimated bottom sediment, and if not, both bottom sediments are output as the estimated bottom sediment. The method of estimating the bottom sediment according to claim 7, wherein the fact is notified to an operator of the computer. The sonar is a three-dimensional side scan sonar, The method for estimating the bottom sediment according to any one of claims 1 to 9.

Images