CN116934753A - Water and soil conservation monitoring method based on remote sensing image - Google Patents
Water and soil conservation monitoring method based on remote sensing image Download PDFInfo
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- 239000002689 soil Substances 0.000 title claims abstract description 80
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- 230000003628 erosive effect Effects 0.000 claims abstract description 112
- 238000004162 soil erosion Methods 0.000 claims abstract description 112
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/10—Segmentation; Edge detection
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- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
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Abstract
The invention relates to the technical field of image processing, and provides a water and soil conservation monitoring method based on remote sensing images, which comprises the following steps: respectively carrying out edge detection on remote sensing images of water and soil conservation areas of two adjacent months to obtain an erosion ditch edge line, calculating an erosion ditch central line, further obtaining a gully span, and calculating a gully span ratio; acquiring the highest point of a local soil surface area and the deepest point of a suspected soil erosion area according to gray values of pixel points at two sides of a pixel point on an erosion ditch edge line, further calculating the sinking degree of single-side ditches, and acquiring the soil erosion significance; and acquiring a soil erosion degree weight image, extracting a soil erosion region, and further evaluating the soil erosion degree. The invention aims to solve the problem that the accuracy is not high when the remote sensing image of the soil and water conservation area is segmented by the traditional image segmentation.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a water and soil conservation monitoring method based on remote sensing images.
Background
The water and soil conservation monitoring is used as a basic link of water and soil conservation, and is a precondition for developing comprehensive water and soil loss treatment and ecological environment construction. The apparent phenomenon of water and soil loss is soil erosion, and is an important content of water and soil conservation monitoring. The formation of soil erosion includes natural factors such as precipitation, topography, soil properties and the like, and also includes artificial factors of unreasonable land utilization, so that the soil quality is reduced, the land is barren, and the land degradation process is accelerated.
With the development of remote sensing technology, the high-resolution remote sensing image can provide detailed spatial information, which is beneficial to classification and change monitoring of ground features. Therefore, the remote sensing images at different time points are segmented, soil erosion areas are obtained, and the change of the soil surface is analyzed and compared, so that the method becomes an important method for monitoring and evaluating the soil erosion degree. But aiming at the remote sensing image of the soil and water conservation area, the soil erosion characteristics show diversity and complexity, and the precision of image segmentation is not high.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a water and soil conservation monitoring method based on remote sensing images, so as to solve the problem of low precision when the existing image segmentation technology segments the remote sensing images of a water and soil conservation area, and the adopted technical scheme is as follows:
the embodiment of the invention provides a water and soil conservation monitoring method based on remote sensing images, which comprises the following steps of:
acquiring high-resolution remote sensing images of water and soil conservation areas of two adjacent months, and preprocessing the high-resolution remote sensing images to obtain two gray images;
respectively carrying out edge detection on the two gray images to obtain an erosion ditch edge line, and further obtaining a suspected soil erosion area and a local soil surface area; calculating the center line of the erosion trench according to the coordinates of the pixel points on the edge line of each erosion trench, and further obtaining a gully span and a gully span line; acquiring a gully span ratio according to the gully span;
obtaining the highest point of the local soil surface area according to the gray values of pixel points at two sides of the erosion gully edge line and the gully span line; obtaining the deepest point of the suspected soil erosion area according to the gray values of pixel points at two sides of the erosion ditch edge line and the gully span line; calculating the single-side valley sagging degree according to the gray value and the coordinates of the highest point of the local soil surface area and the deepest point of the suspected soil erosion area; calculating the soil erosion significance according to the gully span ratio and the single-side gully sinking degree;
soil erosion degree weight is given to each pixel point according to Euclidean distance between each pixel point and an erosion ditch edge line in the image; and extracting a soil erosion area by using a threshold segmentation method for the soil erosion weight, and evaluating the soil erosion degree according to a preset evaluation standard so as to reflect the water and soil conservation effect.
Further, the method for respectively performing edge detection on the two gray level images to obtain an erosion ditch edge line and further obtain a suspected soil erosion area and a local soil surface area comprises the following specific steps:
detecting the edges of the images by adopting an edge detection operator to obtain edge lines, and taking the closed edge lines as erosion trench edge lines;
the inner region of the erosion trench edge line is designated as the suspected soil erosion region, and the outer region of the erosion trench edge line is designated as the localized soil surface region.
Further, the method for calculating the center line of the erosion trench according to the coordinates of the pixel points on the edge line of each erosion trench to further obtain the gully span and the gully span line comprises the following specific steps:
respectively taking the pixel points on each erosion ditch edge line as pixel points to be analyzed, and acquiring corresponding points positioned on the other side of the erosion ditch edge line according to the abscissa of the pixel points to be analyzed, wherein each pixel point to be analyzed corresponds to 0 or 1 corresponding point;
taking the coordinate midpoint between each pixel point to be analyzed and the corresponding point as an erosion trench center point, and taking the pixel point to be analyzed as the erosion trench center point if the pixel point to be analyzed has no corresponding point;
fitting all the center points of the erosion trenches with straight lines to obtain the center line of the erosion trench corresponding to each suspected soil erosion area;
and acquiring a gully span and a gully span line according to Euclidean distance from the pixel point to be analyzed to the center line of the erosion gully.
Further, the method for obtaining the gully span and the gully span line according to the Euclidean distance from the pixel point to be analyzed to the center line of the erosion gully comprises the following specific steps:
and (3) for each pixel point to be analyzed on the erosion trench edge line, making a gully span line perpendicular to the erosion trench center line by the pixel point to be analyzed, marking the intersection point of the gully span line and the erosion trench edge line on the other side as a span point, acquiring the Euclidean distance between the pixel point to be analyzed and the span point, and taking the Euclidean distance between the pixel point to be analyzed and the span point as the gully span of the pixel point to be analyzed.
Further, the method for obtaining the gully span ratio according to the gully span comprises the following specific steps:
and obtaining the maximum value of the gully span of all the pixel points on each erosion gully edge line, taking the maximum value of the gully span as the maximum span value, and taking the ratio of the gully span to the maximum span value as the gully span ratio of the pixel points on the erosion gully edge line.
Further, the method for obtaining the highest point of the local soil surface area according to the gray values of the pixel points at two sides of the erosion gully edge line and the gully span line comprises the following specific steps:
and acquiring gray values of pixel points on a gully span line in the local soil surface area, and taking a maximum point of the gray values closest to the pixel points on an erosion gully edge line as the highest point of the local soil surface area.
Further, the method for obtaining the deepest point of the suspected soil erosion area according to the gray values of the pixel points at two sides of the erosion trench edge line and the gully span line comprises the following specific steps:
and acquiring gray values of pixel points on a gully span line in the suspected soil erosion area, and taking a minimum value point of the gray values nearest to the pixel points on the edge line of the erosion gully as the deepest point of the suspected soil erosion area.
Further, the calculating the single-side valley sagging degree according to the gray value and the coordinates of the highest point of the local soil surface area and the deepest point of the suspected soil erosion area comprises the following specific steps:
acquiring the absolute value and Euclidean distance of a gray value difference value between each pixel point on the erosion ditch edge line and the deepest point of the suspected soil erosion area, and taking the ratio of the absolute value of the gray value difference value to the Euclidean distance as the local ditch depth;
calculating the absolute value of the gray value difference value and the Euclidean distance of the highest point of the local soil surface area and the deepest point of the suspected soil erosion area, and taking the ratio of the absolute value of the gray value difference value and the Euclidean distance as the whole gully depth;
the specific gravity of the local valley depth to the whole valley depth is defined as the single-side valley sagging degree.
Further, the method for calculating the soil erosion significance according to the gully span ratio and the single-side gully sinking degree comprises the following specific steps:
the product of the gully span ratio and the single-sided gully sag is taken as the soil erosion prominence of each pixel point on the erosion gully edge line.
Further, the soil erosion degree weight is given to each pixel point according to the Euclidean distance between each pixel point and the erosion ditch edge line in the image, and the specific method comprises the following steps:
for pixel points in an imageAcquisition distance->The midline of the erosion pit in the nearest suspected soil erosion zone, too +.>Perpendicular to the line of the etching pit, intersecting the edge line of the etching pit at the edge point +.>According to edge points->Is significant to the soil erosion of the pixel pointsGiving soil erosion degree weight->The calculation formula is as follows:
wherein ,is pixel point in the image->Soil erosion weighting of (2); />For edge points->Is a significant degree of soil erosion; />Is pixel point in the image->Euclidean distance to the erosion trench centerline; />Is a parameter adjusting factor; />Is a normalized coefficient.
The beneficial effects of the invention are as follows: according to the method, analysis is carried out according to the characteristic of soil erosion in a high-resolution remote sensing image, the gap ratio of the ravines is constructed according to the direction and width change of the erosion gaps, the local span of the ravines is reflected, then the single-side valley sagging index is constructed according to the corresponding relation between the depth of the erosion gaps and the gray value change of the image, and the soil erosion significance is calculated by combining the gap ratio of the ravines so as to reflect the soil erosion degree. In order to improve the precision of the segmentation of the soil erosion area image, different weights are given to each pixel point in combination with the soil erosion saliency index, and then the soil erosion area is extracted by adopting a maximum inter-class variance method, so that the segmentation precision of the soil erosion area in the image is improved.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic flow chart of a water and soil conservation monitoring method based on remote sensing images according to an embodiment of the invention;
FIG. 2 is a high resolution remote sensing image of a soil and water conservation area;
FIG. 3 is a schematic view of an etch trench edge line;
fig. 4 is a schematic view of a cross section of a soil surface.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a flow chart of a water and soil conservation monitoring method based on remote sensing images according to an embodiment of the invention is shown, the method comprises the following steps:
and S001, acquiring a high-resolution remote sensing image of the soil and water conservation area through an unmanned aerial vehicle, and preprocessing the high-resolution remote sensing image to obtain a gray image.
The purpose of this embodiment is to evaluate the soil erosion degree according to the high-resolution remote sensing image of the soil and water conservation area, so as to reflect the soil and water conservation effect, so that the high-resolution remote sensing image of the soil and water conservation area needs to be acquired first. The water and soil conservation area should monitor the water and soil loss condition once a month, and evaluate the water and soil conservation treatment effect by taking the year as a unit. And shooting the earth surface of the water and soil conservation area by carrying a high-resolution CCD digital camera on the unmanned aerial vehicle to obtain two high-resolution remote sensing images of adjacent months. Preprocessing the shot image, correcting the image point position by correcting the distortion of an objective lens, and splicing a plurality of images obtained by the unmanned aerial vehicle through space three encryption to obtain global information of a research area. Matching and correcting images acquired in different periods to finish image registration, carrying out radiation correction to eliminate illumination and atmospheric influence in the images, improving brightness and contrast of the images, obtaining images of two RGB channels, and converting the obtained RGB images into gray images.
And S002, extracting an erosion ditch edge line by adopting an edge detection algorithm aiming at the characteristics of the soil erosion ditch in the obtained image, and further obtaining the soil erosion significance according to the direction, span and sinking degree of each erosion ditch.
It should be noted that, the soil erosion state in the remote sensing image is mainly represented by erosion trenches on the soil surface, and the more serious the erosion, the greater the depth and width of the erosion trenches. As shown in fig. 2, the erosion trench is a region with a darker color in the image, and firstly, a sobel detection operator is used to detect the image edge of the gray image obtained by preprocessing to obtain an edge line, wherein sobel edge detection is a well-known technology, and the specific process is not repeated. Because the erosion trenches have certain widths, edge lines after edge detection should be closed, non-closed edge lines are removed, the closed edge lines are used as the erosion trench edge lines, the inner areas of the erosion trench edge lines are suspected soil erosion areas, and the outer areas of the erosion trench edge lines are local soil surface areas.
Specifically, each erosion trench has a difference in direction, width, and length, and the width cannot be calculated based on only the horizontal or vertical axis. As shown in FIG. 3, for the pixel points on the edge line of the erosion trenchAccording to->And (3) acquiring corresponding points on the other side of the erosion ditch edge line, wherein each pixel point on the erosion ditch edge line corresponds to 0 or 1 corresponding point. Get->The coordinate midpoint between the corresponding point and the corresponding point is the center point of the erosion trench, if no corresponding point exists, the coordinate midpoint is taken as +.>The central point is taken as the central point of the erosion ditch, and the least square method is adopted to fit all the central points of the erosion ditch to obtain the central line of the erosion ditch +.>Each suspected soil erosion area has an erosion midline in the direction of the erosion trench.
Further, a gully span is obtained according to Euclidean distance from the pixel point on each erosion gully edge line to the erosion gully center line, and the pixel point on the erosion gully edge line is obtainedThrough this point a line perpendicular to the midline of the etch pit is made +.>Is a ravine span line->Gully span->The other side of the boundary line of the erosion trench is located at point N, then +.>Euclidean distance from N as +.>Ravine span->。
The gully span is an important index reflecting the erosion amount of soil, and the erosion amount of places with large span is large for the whole erosion gully; the erosion amount at the places with small span is small. Therefore, according to the pixel point on the edge line of the erosion trenchRavine span->Acquisition ofRavine span ratio at->The calculation formula is as follows:
wherein ,for etching the pixel point on the trench edge line +.>Ravines span ratio at; />Is->The gully span of the position,maximum value of the gully span for all pixel points on the erosion gully edge line.
Values of (2)The larger the description->The wider the ravines at the points are +.>The bigger the->The larger the gap between the gaps of the gaps is relative to the whole gaps; />The smaller the value of (2), the description +.>The narrower the ravines at the points are +.>Smaller (less)>The smaller the gap between the gaps at the points relative to the entire gap.
Further, for each erosion trench edge line, the steepness of the edges of the trenches reflects the sinking degree of the trenches, the steeper the edges of the trenches, the deeper the sinking degree of the trenches, and the greater the erosion amount; the flatter the edges of the ravines, the shallower the sinking degree of the ravines, and the smaller the erosion amount. The higher the soil surface, the higher the brightness, the greater the gray value of the pixel, and the deeper the erosion trench, the lower the brightness, the smaller the gray value of the pixel, due to the illumination effect. Thus, as shown in FIG. 4, for the pixel points on the etch trench edge lineLocating a gully span in a local soil surface area>Upper distance->The nearest maximum point A of gray value is the most local soil surfaceHigh points; finding a gully span in a suspected soil erosion area>Upper distance->The nearest gray value minimum point B is the deepest point of the suspected soil erosion area, and the +.>The Euclidean distance between the point B and the point B is +.>Calculating Euclidean distance between points A and B as +.>。
The principle of sobel detection operator shows that the local gray value variation gradient of the pixel points on the edge line obtained by detection is the largest, if the pixel points on the edge line are subjected to sunlight irradiationThe soil surface profile at the location is approximately curve +.>For inflection point, let go of>The longitudinal distance to the deepest point B of the suspected soil erosion area is the gully depth. Because the depth of the ravines cannot be measured in the image, the larger the gray value change between the A, B two points is, the deeper the ravines are; A. the smaller the gray value variation between the two points B, the shallower the ravines. As shown in FIG. 4, which shows the soil surface profile, when the depth of the ravine remains unchanged, the ++>The greater the depth of the local valley between the two points B, the steeper the ravines and the +.>The smaller the local valley depth between the two points B, the more gentle the ravines. Pixel point on each erosion ditch edge line is set +.>Degree of single-sided valley sinking at the site +.>The calculation formula is as follows:
wherein ,for etching the pixel point on the trench edge line +.>Single-sided valley sagging degree at the position; />Is->Absolute value of gray value difference value of deepest point B of suspected soil erosion area; />The absolute value of the gray value difference between the highest point A of the local soil surface and the deepest point B of the suspected soil erosion area; />Is->Euclidean distance from point B; />Is the euclidean distance between points a and B.
When (when)The larger and +.>The smaller the gray value difference between points A and B is, the smaller the distance is, the shallower the ravines are, and +.>The greater the value +.>The smaller, the description->The larger the difference in gray value between the points B and the smaller the distance, the deeper the local valley depth, the greater the specific gravity of the whole of the partial valley depth-occupied ravines, the +.>The larger the gully, the steeper the gully, i.e., the greater the extent of the gully sag; when->Smaller and +.>The larger the difference between the gray values of points A and B, the smaller the distance, the deeper the ravines, and +.>The smaller the value is +.>The larger the description->The smaller the difference in gray value to the point B and the larger the distance, the shallower the local valley depth, the smaller the specific gravity of the whole of the local valley depth-occupied ravines, and +.>The smaller the ravines, the more gradual the ravines, i.e. the less the ravines sink.
For each erosionThe pixel point on the ditch edge line takes the point as the center, and the local soil erosion degree is influenced by the width and depth of the erosion ditch, so that the soil erosion significance is calculated according to the gully span ratio and the single-side gully sinking degreeThe formula is:
wherein ,for etching the pixel point on the trench edge line +.>A degree of soil erosion significance at the site; />Is->Ravines span ratio at; />Is->Single-sided valley sagging at the point.
When (when)The bigger the->The larger the trench, the deeper and the wider the trench, the +.>The larger the soil erosion, the more serious; when (when)Smaller (less)>Smaller indicates shallower and narrower width of the erosion trench, then +.>The smaller the soil erosion, the lighter.
And S003, giving soil erosion degree weight to each pixel point according to Euclidean distance between the pixel point and the nearest erosion ditch edge line.
In order to extract the soil erosion area in the remote sensing image more accurately, the invention aims at pixel points in the image according to the soil erosion characteristicsObtaining the center line of the erosion pit of the suspected soil erosion area nearest to the center line>Excessive->Do->Is perpendicular to the etch trench edge line at the edge point +.>And calculate +.>To->Is>For pixel dot->Giving soil erosion degree weight->The calculation formula is as follows:
wherein ,is pixel point in the image->Soil erosion weighting of (2); />For edge points->Is a significant degree of soil erosion; />Is pixel dot +.>To->Is a vertical distance of (2); />The value of the parameter adjusting factor is 0.1, and the parameter adjusting factor is used for preventing pixel points from being +.>At->The denominator is 0, so that the formula is meaningless; />Is a normalized coefficient.
When (when)The bigger the->The smaller the soil erosion characteristic of the pixel point is, the greater the soil erosion characteristic of the pixel point is>The larger the soil erosion condition at this point, the more severe; when->Smaller (less)>The larger the soil erosion characteristic of the pixel point is, the smaller the soil erosion characteristic of the pixel point is>The smaller the soil erosion condition at this point, the less likely.
And S004, extracting a soil erosion area from the obtained soil erosion weight by adopting a maximum inter-class variance method, and evaluating the soil erosion degree according to an evaluation standard so as to reflect the soil and water conservation effect.
The method comprises the steps of counting the weight of each pixel point in an image, replacing a gray value with the soil erosion weight of each pixel point to obtain a soil erosion weight image, dividing the soil erosion weight image by using a maximum inter-class variance method to obtain an optimal division threshold value, and taking a region with the weight larger than the division threshold value as a foreground according to the soil erosion weight distribution of the image, wherein the foreground is the divided soil erosion region.
According to the segmentation results of the high-resolution remote sensing images of two adjacent months, a CSLE soil erosion model and a soil erosion classification standard are adopted to evaluate the soil erosion degree, and the soil erosion intensity level and the area of each two adjacent months of the water and soil conservation area are counted to realize quantitative and qualitative information of soil erosion. And comparing the soil erosion rates before and after the soil and water conservation measures are implemented, and if the soil erosion rate is obviously reduced, indicating that the soil and water conservation measures have good effects. By comparing the soil erosion intensity indexes before and after the implementation of the soil and water conservation measures, the improvement degree and the treatment direction of the soil and water conservation effect can be evaluated.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. The foregoing description of the preferred embodiments of the present invention is not intended to be limiting, but rather, any modifications, equivalents, improvements, etc. that fall within the principles of the present invention are intended to be included within the scope of the present invention.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the invention, but any modifications, equivalent substitutions, improvements, etc. within the principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. The water and soil conservation monitoring method based on the remote sensing image is characterized by comprising the following steps of:
acquiring high-resolution remote sensing images of water and soil conservation areas of two adjacent months, and preprocessing the high-resolution remote sensing images to obtain two gray images;
respectively carrying out edge detection on the two gray images to obtain an erosion ditch edge line, and further obtaining a suspected soil erosion area and a local soil surface area; calculating the center line of the erosion trench according to the coordinates of the pixel points on the edge line of each erosion trench, and further obtaining a gully span and a gully span line; acquiring a gully span ratio according to the gully span;
obtaining the highest point of the local soil surface area according to the gray values of pixel points at two sides of the erosion gully edge line and the gully span line; obtaining the deepest point of the suspected soil erosion area according to the gray values of pixel points at two sides of the erosion ditch edge line and the gully span line; calculating the single-side valley sagging degree according to the gray value and the coordinates of the highest point of the local soil surface area and the deepest point of the suspected soil erosion area; calculating the soil erosion significance according to the gully span ratio and the single-side gully sinking degree;
soil erosion degree weight is given to each pixel point according to Euclidean distance between each pixel point and an erosion ditch edge line in the image; and extracting a soil erosion area by using a threshold segmentation method for the soil erosion weight, and evaluating the soil erosion degree according to a preset evaluation standard so as to reflect the water and soil conservation effect.
2. The method for monitoring soil and water conservation based on remote sensing images according to claim 1, wherein the steps of performing edge detection on two gray level images to obtain an erosion ditch edge line and further obtain a suspected soil erosion area and a local soil surface area respectively comprise the following specific steps:
detecting the edges of the images by adopting an edge detection operator to obtain edge lines, and taking the closed edge lines as erosion trench edge lines;
the inner region of the erosion trench edge line is designated as the suspected soil erosion region, and the outer region of the erosion trench edge line is designated as the localized soil surface region.
3. The water and soil conservation monitoring method based on remote sensing images according to claim 1, wherein the calculating the center line of the erosion trench according to the coordinates of the pixel points on the edge line of each erosion trench to obtain the gully span and the gully span line comprises the following specific steps:
respectively taking the pixel points on each erosion ditch edge line as pixel points to be analyzed, and acquiring corresponding points positioned on the other side of the erosion ditch edge line according to the abscissa of the pixel points to be analyzed, wherein each pixel point to be analyzed corresponds to 0 or 1 corresponding point;
taking the coordinate midpoint between each pixel point to be analyzed and the corresponding point as an erosion trench center point, and taking the pixel point to be analyzed as the erosion trench center point if the pixel point to be analyzed has no corresponding point;
fitting all the center points of the erosion trenches with straight lines to obtain the center line of the erosion trench corresponding to each suspected soil erosion area;
and acquiring a gully span and a gully span line according to Euclidean distance from the pixel point to be analyzed to the center line of the erosion gully.
4. The water and soil conservation monitoring method based on remote sensing images according to claim 3, wherein the method for obtaining a gully span and a gully span line according to the euclidean distance from the pixel point to be analyzed to the center line of the erosion gully comprises the following specific steps:
and (3) for each pixel point to be analyzed on the erosion trench edge line, making a gully span line perpendicular to the erosion trench center line by the pixel point to be analyzed, marking the intersection point of the gully span line and the erosion trench edge line on the other side as a span point, acquiring the Euclidean distance between the pixel point to be analyzed and the span point, and taking the Euclidean distance between the pixel point to be analyzed and the span point as the gully span of the pixel point to be analyzed.
5. The water and soil conservation monitoring method based on remote sensing images according to claim 1, wherein the step of obtaining the ravines span ratio according to the ravines spans comprises the following specific steps:
and obtaining the maximum value of the gully span of all the pixel points on each erosion gully edge line, taking the maximum value of the gully span as the maximum span value, and taking the ratio of the gully span to the maximum span value as the gully span ratio of the pixel points on the erosion gully edge line.
6. The method for monitoring soil and water conservation based on remote sensing images according to claim 1, wherein the method for obtaining the highest point of the local soil surface area according to the gray values of pixel points at two sides of the erosion trench edge line and the gully span line comprises the following specific steps:
and acquiring gray values of pixel points on a gully span line in the local soil surface area, and taking a maximum point of the gray values closest to the pixel points on an erosion gully edge line as the highest point of the local soil surface area.
7. The method for monitoring soil and water conservation based on remote sensing images according to claim 1, wherein the obtaining the deepest point of the suspected soil erosion area according to the gray values of pixel points at two sides of the erosion trench edge line and the gully span line comprises the following specific steps:
and acquiring gray values of pixel points on a gully span line in the suspected soil erosion area, and taking a minimum value point of the gray values nearest to the pixel points on the edge line of the erosion gully as the deepest point of the suspected soil erosion area.
8. The water and soil conservation monitoring method based on remote sensing images according to claim 1, wherein the calculating the single-side valley sagging degree according to the gray value and the coordinates of the highest point of the local soil surface area and the deepest point of the suspected soil erosion area comprises the following specific steps:
acquiring the absolute value and Euclidean distance of a gray value difference value between each pixel point on the erosion ditch edge line and the deepest point of the suspected soil erosion area, and taking the ratio of the absolute value of the gray value difference value to the Euclidean distance as the local ditch depth;
calculating the absolute value of the gray value difference value and the Euclidean distance of the highest point of the local soil surface area and the deepest point of the suspected soil erosion area, and taking the ratio of the absolute value of the gray value difference value and the Euclidean distance as the whole gully depth;
the specific gravity of the local valley depth to the whole valley depth is defined as the single-side valley sagging degree.
9. The water and soil conservation monitoring method based on remote sensing images according to claim 1, wherein the calculating the soil erosion saliency according to the ravines span ratio and the single-side ravines sinking degree comprises the following specific steps:
the product of the gully span ratio and the single-sided gully sag is taken as the soil erosion prominence of each pixel point on the erosion gully edge line.
10. The water and soil conservation monitoring method based on remote sensing images according to claim 1, wherein the method for giving soil erosion degree weight to each pixel point according to euclidean distance between each pixel point and an erosion ditch edge line in the image comprises the following specific steps:
for pixel points in an imageAcquisition distance->The midline of the erosion pit in the nearest suspected soil erosion zone, too +.>Perpendicular to the line of the etching pit, intersecting the edge line of the etching pit at the edge point +.>According to edge points->Is to the soil erosion significance of pixel point +.>Giving soil erosion degree weight->The calculation formula is as follows:
wherein ,is pixel point in the image->Soil erosion weighting of (2); />For edge points->Is a significant degree of soil erosion; />Is pixel point in the image->Euclidean distance to the erosion trench centerline; />Is a parameter adjusting factor; />Is a normalized coefficient.
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