Method and system for evaluating ecological stability of saline-alkali soil based on unmanned aerial vehicle remote sensing image

Abstract

The present application relates to the technical field of image recognition, and particularly relates to a saline-alkali soil ecological stability evaluation method and system based on unmanned aerial vehicle remote sensing images. The method comprises the following steps: collecting a remote sensing orthographic image of an unmanned aerial vehicle of a target saline-alkali soil, dividing a ground salt frost distribution area in the remote sensing orthographic image, and determining a vegetation community distribution boundary; marking a plot with periodic salt frost precipitation traces in the remote sensing orthographic image, combining the vegetation community distribution boundary to construct a global subsurface salt accumulation risk layer; based on the remote sensing orthographic image, counting a vegetation coverage ratio, dividing an ecological stability grade according to the vegetation coverage ratio, and outputting a saline-alkali soil ecological partition. The present application identifies salt crust, powdery floating salt and vegetation boundary fracture in the saline-alkali soil remote sensing image, introduces a time sequence verification mechanism, constructs a spatial mapping relationship between the ground salt frost form and the subsurface salt accumulation risk, and realizes efficient and accurate evaluation of the ecological stability of the saline-alkali soil.

Description

Technical Field

[0001] This invention relates to the field of image recognition technology, and in particular to a method and system for assessing the ecological stability of saline-alkali land based on UAV remote sensing images. Background Technology

[0002] The assessment of the ecological status of saline-alkali land mainly relies on ground sampling surveys. This involves setting up sampling points in the target area to collect soil samples for laboratory physicochemical analysis, obtaining data on indicators such as soil salinity and pH value. Simultaneously, manual surveys are conducted to record vegetation cover, comprehensively determining the ecological stability of the area. However, this traditional assessment method has significant technical limitations. Ground sampling surveys require substantial manpower and resources, and the density of sampling points is limited by cost and time, making it difficult to conduct comprehensive assessments of large areas of saline-alkali land. More importantly, soil salinity exhibits a highly heterogeneous spatial distribution, and a limited number of sampling points cannot accurately reflect the overall salt accumulation pattern of the region. Summary of the Invention

[0003] Therefore, it is necessary to provide a method and system for assessing the ecological stability of saline-alkali land using UAV remote sensing images in order to solve at least one of the aforementioned technical problems.

[0004] To achieve the above objectives, a method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images is provided, the method comprising the following steps: Step S1: Collect remote sensing orthophotos of the target saline-alkali land by UAV, delineate the distribution area of ​​surface salt frost in the remote sensing orthophotos, and determine the distribution boundary of vegetation community. Step S2: Mark the plots in the remote sensing orthophotos that show traces of periodic salt frost precipitation, and construct a global subsurface salt accumulation risk layer by combining the vegetation community distribution boundaries; Step S3: Calculate the vegetation cover percentage based on remote sensing orthophotos, classify the ecological stability level according to the vegetation cover percentage, and output the ecological zoning of saline-alkali land. Step S4: Conduct a stability assessment of the ecological zoning of saline-alkali land based on the plot range of the subsurface salt accumulation risk layer to obtain saline-alkali land ecological stability assessment information.

[0005] This invention also provides a system for assessing the ecological stability of saline-alkali land based on UAV remote sensing images, used to execute a method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images. The system includes: The salt frost landform recognition module is used to collect remote sensing orthophotos of the target saline-alkali land from UAVs, delineate the distribution area of ​​surface salt frost in the remote sensing orthophotos, and determine the distribution boundary of vegetation communities. The salt accumulation plot marking module is used to mark plots in remote sensing orthophotos that show traces of periodic salt frost precipitation, and to construct a global subsurface salt accumulation risk layer by combining the vegetation community distribution boundary. The vegetation cover statistics module is used to count the vegetation cover percentage based on remote sensing orthophotos, classify the ecological stability level according to the vegetation cover percentage, and output the ecological zoning of saline-alkali land. The ecological stability assessment module is used to assess the stability of saline-alkali land ecological zones based on the plot range of the subsurface salt accumulation risk layer, and obtain saline-alkali land ecological stability assessment information.

[0006] The beneficial effects of the present invention are as follows: I. This invention establishes a spatial mapping relationship for directly inferring subsurface salt accumulation risk from surface salt crust morphology by jointly identifying three unique landform markers of saline-alkali land: closed-ring structure of salt crust, wavy grayscale variation of powdery floating salt, and unidirectional decreasing fracture of vegetation boundaries in remote sensing orthophotos. It also introduces a multi-frame temporal cross-validation mechanism to filter out interference from temporary surface salt patches. This technical solution abandons the lagging detection mode of traditional soil sampling and testing, and accurately locates the core risk area where salt crust, layered salt accumulation zone, and vegetation boundary fracture overlap using multi-element spatial overlay and intersection operations. This enables precise spatial location of salt accumulation risk areas in large-scale saline-alkali land, significantly improving the spatial accuracy of risk identification.

[0007] II. This invention constructs a two-layer assessment framework linking vegetation cover percentage and salt accumulation risk level. It calculates the effective vegetation cover percentage using natural plots as independent statistical units to classify initial ecological stability levels. Then, a salt accumulation risk layer is used to perform spatial overlap detection and hierarchical downgrading correction on plots with initial levels of one or two. This technical solution enables stability assessment to not only reflect the current vegetation cover status but also comprehensively characterize the potential stress trend of subsurface salt accumulation on vegetation communities, effectively avoiding the overestimation risk that may arise from relying solely on vegetation cover indicators, and achieving a forward-looking assessment of the ecological stability of saline-alkali land. Attached Figure Description

[0008] Figure 1 This is a schematic diagram illustrating the steps of a method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images. Figure 2 This is an example of an orthophoto image of a target saline-alkali land taken by an unmanned aerial vehicle (UAV). Figure 3 This is an example of a subsurface salt accumulation risk layer overlaid with a remote sensing base map; Figure 4 A schematic diagram of a module for assessing the ecological stability of saline-alkali land based on UAV remote sensing images; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0009] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0010] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0011] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0012] To achieve the above objectives, please refer to Figures 1 to 4 A method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images, the method comprising the following steps: Preferably, step S1: acquire remote sensing orthophotos of the target saline-alkali land by UAV, delineate the distribution area of ​​surface salt frost in the remote sensing orthophotos, and determine the distribution boundary of vegetation community. Optionally, step S1, which involves delineating the surface salt frost distribution area in the remote sensing orthophoto image, includes: The entire surface contour boundary of the remote sensing orthophoto is traversed, and closed patches with continuous and uninterrupted loops or polygonal broken lines and higher internal pixel brightness uniformity than the surrounding bare soil area are extracted as the spatial range corresponding to the salt crust. The strip-shaped region extending along the outer edge of vegetation patches in the remote sensing orthophoto image and exhibiting a wave-like change in gray value from the inside to the outside, first increasing and then suddenly decreasing, is extracted as the spatial range corresponding to the powdery floating salt. For pixel regions with gray values ​​between withered grass and bare soil, contour competition matching based on local gray response peaks is performed. The local gray response peaks are connected to form closed or semi-closed trajectories, and the regions with average gray values ​​inside the trajectory lower than the gray values ​​of the external background are classified into the salt frost spatial distribution range.

[0013] In this embodiment, a remote sensing orthophoto of the target saline-alkali land is acquired using a multispectral sensor mounted on a UAV, with a ground spatial resolution set to 0.05 meters to 0.15 meters. A full-area surface contour boundary traversal operation is performed on the remote sensing orthophoto, extracting all closed contours within the image. Edge detection thresholds are set to a low threshold of 30 and a high threshold of 90. For each extracted closed contour, the continuity of boundary line curvature and the integrity of closure are calculated. When the rate of change of the curvature of the closed contour boundary line is less than 15% and there are no breaks within the contour, the contour is determined to have continuous and uninterrupted ring-shaped boundary characteristics. The standard deviation of the gray values ​​of all pixels within the closed contour is calculated. When this standard deviation is less than 60% of the standard deviation of the gray values ​​of the entire remote sensing orthophoto, the pixel brightness uniformity within the contour is determined to be higher than that of the surrounding bare soil area.

[0014] Using the outer edge of the vegetation patch as a reference, the grayscale value change curve is scanned pixel by pixel in the direction away from the vegetation patch. When the grayscale value of the strip-shaped region shows a wave-like change pattern of first increasing to a peak and then decreasing from the side closer to the vegetation to the side farther away from the vegetation, and the width of the strip-shaped region is 5 to 20 pixels, and the angle between the strip extension direction and the tangent direction of the outer edge of the vegetation is less than 30 degrees, the strip-shaped region is extracted as the spatial range corresponding to the powdery floating salt. For pixels whose gray values ​​fall between the average gray value of the grass-covered area and the average gray value of the bare soil exposed area, a local window size of 7×7 pixels is set. Within each window, pixel locations with a gray value difference exceeding 15 gray levels are extracted as local gray response peak points. Peak points with a distance of less than 5 pixels between adjacent peak points are connected. When the connecting trajectory forms a closed or semi-closed shape and the average gray value of the pixels inside the trajectory is more than 10 gray levels lower than the average gray value of the adjacent area outside the trajectory, the area enclosed by the trajectory is classified into the spatial distribution range of salt frost.

[0015] It should be noted that three frames of UAV remote sensing orthophotos with a 10-day time interval were retrieved. Geographic coordinate spatial alignment processing based on SIFT feature point matching was performed on each frame to generate a time-stacked image stack, with the spatial alignment error controlled within 0.5 pixels. In the time-stacked image stack, the cumulative frequency of each pixel location being identified as a salt crust in the three frames was counted. Locations with a cumulative frequency of 3 times were marked as time-stable salt crust primitives, while locations with a cumulative frequency of only 1 time and corresponding locations in the other two frames with bare soil backgrounds were marked as temporary surface salt patches. An eight-neighborhood morphological dilation operation was performed on the time-stable salt crust primitives, with three dilation iterations. The boundary extension of each dilation was limited to a pixel connection chain where the absolute value of the grayscale difference between adjacent frames did not exceed 8 grayscale levels and the edge gradient direction difference was less than 20 degrees, forming a time-cross-validated global salt crust boundary contour.

[0016] See Figure 2 This image is an orthophoto of a saline-alkali land taken by UAV, showcasing the image features corresponding to various salt crust morphologies. The large, light-colored area on the left side of the image represents the spatial extent of the salt crust; this area has uniform brightness and its boundaries form a continuous, closed outline. The long, strip-shaped areas extending along the outer edge of the green vegetation patches represent powdery floating salt bands. The lower right side of the image shows a ring-shaped outline formed by connecting black dots, representing a semi-closed salt crust trajectory constructed based on local grayscale response peaks. This image distinguishes the visual differences of the three types of salt crust in the ground image, demonstrating the spatial distribution of different salt crust morphologies on the surface of the saline-alkali land.

[0017] Optionally, step S1, which involves delineating the surface salt frost distribution area in the remote sensing orthophoto image, may also include: Retrieve multiple time-series remote sensing images covering the same target saline-alkali land, perform spatial alignment processing based on geographic coordinates on each time-series remote sensing image, and generate a time-series overlay image stack. In the temporal overlay image stack, the frequency of each spatial location being determined as the spatial range corresponding to the salt shell in all frames of images is counted, and the locations in all frames of images that have a consistent salt shell determination are marked as temporally stable salt shell primitives. Locations where only a single frame of the image shows salt crust and the corresponding locations in the remaining frames are bare soil backgrounds are marked as temporary surface salt patches.

[0018] In this embodiment, three time-series remote sensing orthophotos covering the same target saline-alkali land are retrieved, with a 10-day acquisition time interval between adjacent frames. Feature point extraction based on scale-invariant feature transformation is performed on each frame of the time-series remote sensing orthophotos, extracting no fewer than 500 feature points in each frame. Descriptor Euclidean distance matching is performed on the extracted feature points between frames. The homography transformation matrix is ​​calculated based on the successfully matched feature point pairs. Each frame is then resampled to a unified geographic coordinate space, generating a time-series overlay image stack of the three frames. The spatial alignment error is controlled within 0.5 pixels.

[0019] A frequency statistics operation for salt crust determination is performed at each pixel location in the temporally overlaid image stack. For each spatial location, the determination results of the spatial range corresponding to the salt crust in the first, second, and third frames of the image are read. When the location is determined to be the spatial range corresponding to the salt crust in all three frames, the location is marked as a temporally stable salt crust primitive. When the location is determined to be the spatial range corresponding to the salt crust in only one frame, and the pixel gray value of the corresponding location in the other two frames is within the gray value range of the bare soil background, the location is marked as a temporary surface salt spot.

[0020] Spatial connectivity analysis is performed on the location set of all temporally stable salt shell primitives. Locations with adjacent temporally stable salt shell primitives in any of the eight adjacent directions are grouped into the same connected region. Connected regions with fewer than 10 temporally stable salt shell primitives are removed. Using the outer boundary of the connected regions of temporally stable salt shell primitives after area filtering as the starting contour line, each pixel adjacent to the outer side of the starting contour line is traversed. If the absolute value of the gray level difference between adjacent frames does not exceed 8 gray levels, and the difference between the edge gradient direction of the pixel location and the average edge gradient direction of the starting contour line is less than 20 degrees, the pixel is included in the extended contour line range. The above traversal and inclusion operation is repeated until no new pixels meet the conditions, finally forming a global salt frost boundary contour line correction base after three-frame temporal cross-validation.

[0021] Optionally, determining the vegetation community distribution boundary in step S1 includes: The vegetation index is calculated on the remote sensing orthophoto. The connected regions of pixels whose vegetation index values ​​are consistently in the preset high range are extracted as the vegetation core area. The vegetation core area is extended outward along the outer edge of the vegetation core area to the position where the vegetation index value first drops to the preset bare soil reference value. The transition zone where vegetation and salt crust intersect is delineated by connecting the positions at this location. Within the transition zone, trace the unidirectional decreasing path of the vegetation index value from a preset high value range to a preset low value range, and connect the points on each unidirectional decreasing path where the vegetation index value is equal to the benchmark value for distinguishing vegetation from bare soil to form the initial boundary line. Spatial connectivity correction is performed on the initial boundary line, removing isolated short line segments that have no spatial connection with the main boundary line, and retaining the main line segments that extend continuously and curve along the outer edge of the vegetation. The area enclosed by the corrected main line segments is used as the solid distribution boundary of the salt-tolerant vegetation community.

[0022] In this embodiment, a normalized vegetation index (NZI) calculation is performed on the remote sensing orthophoto to obtain the vegetation index value for each pixel location. A threshold of 0.30 is set for the high range of vegetation index values. Pixels with a vegetation index value greater than 0.30 and spatially adjacent are clustered into the same connected domain. The connected domain with the largest area among all connected domains is extracted as the vegetation core area. The vegetation index is calculated pixel by pixel along the outer edge of the vegetation core area. When the vegetation index value of a pixel location first drops below 0.15, that pixel location is recorded as the bare soil reference location. All bare soil reference locations are sequentially connected to form a closed curve. The strip area defined by this closed curve is used as the transition zone where vegetation and salt crust intersect.

[0023] Specifically, the vegetation index value variation curve is scanned line by line within the transition zone. For each scan line, the monotonic trend of the vegetation index value is tracked from the side closer to the vegetation core area to the side farther away from the vegetation core area. When the vegetation index value continuously decreases from greater than 0.30 to less than 0.15 without any upward fluctuations in between, the scan line segment is identified as a unidirectional decreasing path. On each unidirectional decreasing path, the isopleths with a vegetation index value equal to 0.20 are located, and isopleths on adjacent scan lines that are less than 5 pixels apart are connected to form the initial boundary line.

[0024] Spatial connectivity correction is performed on the initial boundary line. The longest continuous line segment in the initial boundary line is used as the main boundary line. All other line segments are traversed, and the shortest Euclidean distance from all pixels on each segment to the main boundary line is calculated. If more than 80% of the pixels on a line segment have a shortest Euclidean distance to the main boundary line greater than 10 pixels, the line segment is considered to have no spatial connection to the main boundary line and is removed from the initial boundary line. All line segments with a shortest Euclidean distance to the main boundary line less than or equal to 10 pixels and a continuous extension length greater than 50 pixels are retained. These retained line segments are connected sequentially according to the rule that the distance between their first and last endpoints is less than 3 pixels, forming a main trunk line segment that curves and extends along the outer edge of the vegetation. The closed spatial range enclosed by the corrected main trunk line segment is used as the physical distribution boundary of the salt-tolerant vegetation community.

[0025] Preferably, step S2: mark the plots in the remote sensing orthophoto that show traces of periodic salt frost precipitation, and construct a global subsurface salt accumulation risk layer in combination with the vegetation community distribution boundary; Optionally, in step S2, the specific areas marked with periodic salt frost patterns in the remote sensing orthophoto image are: The distribution range of surface salt frost in the whole region is traversed by grid. The grids in which the temporally stable salt crust units are covered in a continuous area and the salt crust units occupy the main salt frost in the grid are included in the set of periodic salt frost precipitation blocks. Grids containing only discontinuous areas of powdery floating salt along the vegetation edge and lacking a closed salt crust outline are marked as non-periodic surface salt patches. The first salt accumulation spatial mask is generated based on the overall spatial outer boundary of the set of periodically salt-frosting landmasses.

[0026] In this embodiment, a grid division operation is performed on the entire surface salt frost distribution range using a 50×50 pixel grid size to generate a grid array covering the entire surface salt frost distribution range. Each grid is traversed sequentially, and for all pixels within each grid, the number of pixels marked as time-stable salt crust primitives is counted, along with the total number of pixels within the grid that are classified as salt frost spatial distribution ranges. When the proportion of time-stable salt crust primitive pixels to the total number of pixels in the grid is greater than 35%, and the proportion of time-stable salt crust primitive pixels to the total number of pixels in the salt frost spatial distribution range within the grid is greater than 60%, it is determined that the time-stable salt crust primitives within the grid form a contiguous area coverage and that the salt crust primitives occupy the main body of the salt frost within the grid. The grid is then classified into a set of periodically salt frost precipitation areas.

[0027] The remaining grids not included in the set of periodic salt frost precipitates were subjected to secondary discrimination. If a grid contains no pixels marked as time-stable salt crust primitives, but contains pixels belonging to the spatial range corresponding to powdery floating salt, and these pixels are discontinuously distributed along the vegetation edge, and there is no closed-loop salt crust outline structure within the grid, then the grid is marked as an aperiodic surface salt precipitate patch. Aperiodic surface salt precipitates and the set of periodic salt frost precipitates form a mutually exclusive spatial division.

[0028] In another embodiment, for all grids in the set of periodically salt-frost-exposed areas, the spatial coordinates of each grid are extracted. The outer boundary points of all grids belonging to this set are then connected sequentially in a clockwise direction to form an overall spatial boundary encompassing all periodically salt-frost-exposed grids. Using this overall spatial boundary as a mask outline, the area inside the mask outline is assigned a value of 1, and the area outside the mask outline is assigned a value of 0, generating a first salt-accumulated area spatial mask. The spatial resolution of this first salt-accumulated area spatial mask is consistent with the spatial resolution of the remote sensing orthophoto, both ranging from 0.05 meters to 0.15 meters.

[0029] Optionally, in step S2, the areas marked with periodic salt frost patterns in the remote sensing orthophoto image also include: An annular scanning band is formed by pushing the boundary line of the salt-tolerant vegetation community outward to the outer edge of the powdery floating salt staining area. Within the annular scanning band, the gray value is detected as a convex peak-shaped gray profile feature that first increases and then decreases from the side near the boundary to the side away from the boundary. The annular area that extends continuously around the vegetation boundary and has the overall convex peak grayscale profile characteristics is marked as the salt-carrying zone of the vegetation root system. Using the closed curve of the outer edge of the salt accumulation zone away from vegetation as the spatial dividing line, the area on the side of the dividing line facing the vegetation is classified as the root-function type salt accumulation space, and the area on the side of the dividing line away from the vegetation is classified as the non-root bare salt space.

[0030] In this embodiment, the scan line is traversed pixel by pixel outwards from the boundary of the salt-tolerant vegetation community, with a traversal width set to 50 pixels. For each scan line, the grayscale value changes from near the boundary to far away. When the grayscale value continuously rises from its initial value near the boundary to a local maximum and then continuously decreases to the termination value at the outer edge of the powdery salt halo area, this segment of the curve is identified as a convex-peak grayscale profile. The pixel positions where convex-peak grayscale profiles are detected in all scan lines are marked, and the marked positions are connected according to the scan line sequence to form a convex-peak grayscale profile distribution trajectory within the annular scan band.

[0031] Spatial continuity detection was performed on the aforementioned convex-peak grayscale profile distribution trajectory. Peak points with a distance of less than 3 pixels between peak points of the convex-peak grayscale profile on adjacent scan lines were grouped into the same continuous trajectory segment, and the length of each continuous trajectory segment extending along the vegetation boundary was calculated. When the extension length of a certain continuous trajectory segment exceeds 30% of the perimeter of the vegetation boundary line of that segment, the annular area covered by the continuous trajectory segment was marked as the stratified salt zone of the vegetation root salt-carrying sphere.

[0032] Specifically, the outer edge pixel positions of the salt accumulation zone of the vegetation root system on the side away from the vegetation are extracted, and all outer edge pixels are connected sequentially in a clockwise direction to form an outer edge closed curve. Using this outer edge closed curve as a spatial dividing line, all pixel ranges on the side of the spatial dividing line facing the vegetation cover are classified as root-function salt accumulation space, and all pixel ranges on the side of the spatial dividing line away from the vegetation cover are classified as non-root bare salt space. The outer edge closed curve forms a clear spatial boundary between the root-function salt accumulation space and the non-root bare salt space, and the two do not overlap in spatial range.

[0033] Optionally, in step S2, the construction of a global subsurface salt accumulation risk layer based on vegetation community distribution boundaries is specifically as follows: The core overlapping area is generated by performing spatial overlay and intersection operations on the first salt accumulation space mask covered by the time-stable salt crust primitive, the second salt accumulation space region covered by the salt accumulation zone of the vegetation root salt-carrying layer, and the boundary fracture point layer where the vegetation index value shows intermittent fractures on the vegetation boundary. Taking the geometric center of each core overlapping area as the starting point of radiation, and taking the direction of the longest diameter of the circumscribed ellipse of each overlapping area as the dominant direction of skeleton extension, the skeleton extends outward to the boundary of the adjacent non-overlapping area to form the initial risk skeleton line. The basic spatial framework of the subsurface salt accumulation risk layer is generated by widening the initial risk skeleton line to the adjacent vegetation boundary line on both sides and using the vegetation boundary line as a hard truncation constraint.

[0034] In this embodiment, the first salt accumulation spatial mask, the second salt accumulation spatial region, and the boundary break point layer are loaded into the same geographic coordinate system, and their spatial resolution is uniformly resampled to 0.1 meters. The three layers are traversed pixel by pixel. When a pixel location has a value of 1 in the first salt accumulation spatial mask, a value of 1 in the second salt accumulation spatial region, and a value of 1 in the boundary break point layer, that pixel location is marked as a core overlapping pixel. Connected component clustering is performed on all core overlapping pixels. Locations with adjacent core overlapping pixels in any of the eight adjacent directions are grouped into the same connected component. The outer boundary line of each connected component is extracted, and the spatial range enclosed by each outer boundary line is taken as a core overlapping region.

[0035] Specifically, the row and column numbers of all pixels within the core overlapping area are extracted, and the average row and column numbers are calculated. The pixel position corresponding to the average row and column numbers is taken as the geometric center of the core overlapping area. All pixel coordinates on the outer boundary line of the core overlapping area are extracted. Starting from the geometric center, probe rays are emitted outward in all directions within a range of 0 to 360 degrees, with a step size of 1 degree. The detection distance of each probe ray is 500 pixels. The coordinates of the intersection points of each probe ray and the outer boundary line of the core overlapping area are recorded. The distance from the geometric center to each intersection point is calculated, and the direction of the probe ray corresponding to the maximum distance value is determined as the longest extension direction of the core overlapping area. Starting from the geometric center, the system extends outward pixel by pixel along the longest extension direction. Each time a pixel is extended, it checks whether the pixel's position belongs to any core overlapping area. When five consecutive pixels on the extension path do not belong to any core overlapping area, the extension stops and the stopping position is taken as the extension endpoint in that direction. Connecting the two extension endpoints forms an initial risk skeleton line segment that runs through the core overlapping area.

[0036] In another embodiment, after generating the initial risk skeleton segments corresponding to all core overlapping areas, a widening process is performed on each initial risk skeleton segment. Along the extension direction of the initial risk skeleton segment, each cell on both sides of the skeleton segment is traversed outwards column by column. Each time, the outward expansion is performed by one cell width, and it is checked whether the cell position coincides with the position of the adjacent vegetation boundary line. When the Euclidean distance between the cell position and the position of the adjacent vegetation boundary line is detected to be less than one cell, the expansion in that direction is stopped, and the stopping position is recorded as the widened boundary on that side. The spatial range enclosed by the widened boundaries on both sides and the lines connecting the two ends of the initial risk skeleton segment's expansion endpoints is used as the risk plot unit corresponding to the core overlapping area. All risk plot units are combined to form the basic spatial framework of the subsurface salt accumulation risk layer.

[0037] Of particular importance, step S2, which involves constructing a global subsurface salt accumulation risk layer by combining vegetation community distribution boundaries, also includes: Within each independent risk parcel unit covered by the basic spatial framework, determine whether the salt crust structure cell constitutes the main form of the land cover of the unit, and at the same time determine whether there is a spatial overlap between the fault points of the unit boundary and the vegetation boundary. Units whose salt crust structure constitutes the main form of the land cover and whose boundaries overlap with the pre-defined first part of the vegetation fault points are marked as high-level salt accumulation risk areas. Units whose salt crust structure constitutes a secondary form of land cover or whose boundaries overlap with vegetation fault points are marked as medium-level salt accumulation risk areas. Units whose salt crust structure does not constitute the main form of land cover and whose boundaries do not coincide with vegetation fault points are marked as general-level salt accumulation risk areas. Differentiated spatial markers are used to assign risk locations at each level, forming a multi-level risk level space within the layer.

[0038] In this embodiment, within each independent risk parcel unit covered by the basic spatial framework, the number of pixels marked as time-stable salt crust primitives within that unit is counted, along with the total number of pixels within that unit. The proportion of time-stable salt crust primitive pixels to the total number of pixels in that unit is calculated. When this proportion is greater than 50%, the salt crust structural pixels are determined to constitute the main form of the land cover of that unit; when the proportion is between 20% and 50%, the salt crust structural pixels are determined to constitute the secondary form of the land cover of that unit; when the proportion is less than 20%, the salt crust structural pixels are determined not to constitute the main form of the land cover of that unit.

[0039] Extract the boundary cell set of the independent risk parcel unit, and simultaneously extract all cell positions of the vegetation boundary fault point layer. Iterate through each cell on the boundary line of the unit, checking whether the cell position has a corresponding marker in the vegetation boundary fault point layer. If more than 5 consecutive boundary cells on the unit boundary line have corresponding markers in the vegetation boundary fault point layer, it is determined that the unit boundary and the vegetation fault point have a spatial overlap. If 1 to 5 consecutive boundary cells on the unit boundary line have corresponding markers in the vegetation boundary fault point layer, it is determined that the unit boundary and the vegetation fault point have a partial spatial overlap. If no cell on the unit boundary line has a corresponding marker in the vegetation boundary fault point layer, it is determined that the unit boundary and the vegetation fault point do not have a spatial overlap.

[0040] When the salt crust structure constitutes the main form of land cover and its boundary spatially overlaps with vegetation fault points, the unit is marked as a high-level salt accumulation risk area. When the salt crust structure constitutes a secondary form of land cover or its boundary partially overlaps with vegetation fault points, the unit is marked as a medium-level salt accumulation risk area. When the salt crust structure does not constitute the main form of land cover and its boundary does not spatially overlap with vegetation fault points, the unit is marked as a general-level salt accumulation risk area. Different spatial marker values ​​are assigned to each level of risk area: a value of 3 for high-level salt accumulation risk areas, a value of 2 for medium-level salt accumulation risk areas, and a value of 1 for general-level salt accumulation risk areas. The spatial marker values ​​of each level of risk area are then marked at the corresponding independent risk plot unit locations within the basic spatial framework, forming a multi-level risk level spatial distribution within the layer.

[0041] See Figure 3 This is a remote sensing base map overlaid with a subsurface salt accumulation risk layer, formed after grid discrimination processing. The blue outer contour represents the mask area enclosed by periodic salt frost patches. The red area inside the layer represents the main salt crust grid, within which there are continuous stable salt crusts. The yellow dashed lines delineate the edge floating salt grid; this area only contains discontinuously distributed powdery floating salt and no closed salt crust structure. This demonstrates the spatial division results of different salt frost patches using the grid block discrimination method, showcasing the spatial composition of the subsurface salt accumulation risk layer across the entire region.

[0042] Preferably, step S3: Based on remote sensing orthophotos, the vegetation cover percentage is statistically analyzed, the ecological stability level is divided according to the vegetation cover percentage, and the ecological zoning of saline-alkali land is output. Most importantly, step S3, which classifies the ecological stability level based on the vegetation cover percentage, specifically involves: Each independent closed plot enclosed by natural geographic boundaries or artificial feature boundaries in remote sensing orthophotos is taken as the basic statistical unit. Pixels in each unit with vegetation index values ​​higher than the vegetation existence benchmark value are clustered in connected domains and isolated spots that are not connected to the main vegetation community are removed. The area of ​​the remaining connected domains is taken as the effective vegetation cover area. Calculate the ratio of the effective vegetation cover area of ​​each independent closed plot to the total area of ​​the plot, and match the four ecological stability levels of primary stability zone, secondary stability zone, tertiary stability zone and quaternary stability zone according to the order of the ratio from high to low. An initial spatial distribution layer of ecological stability level is generated based on the hierarchical attributes obtained from matching each land parcel.

[0043] In this embodiment, each independent closed plot enclosed by natural geographic boundaries or artificial feature boundaries in remote sensing orthophotos is used as the basic statistical unit. For all pixels within each independent closed plot, pixels with a normalized vegetation index (NDI) greater than 0.15 are marked as vegetation-containing pixels. Spatial connectivity clustering is performed on all vegetation-containing pixels, grouping locations with adjacent vegetation-containing pixels in eight adjacent directions into the same connectivity region. The spatial connectivity between each connectivity region and the largest area connectivity region is determined. When a connectivity region has no adjacent pixel connections to the largest area connectivity region, it is identified as an isolated patch and removed from the vegetation cover area. The sum of the number of pixels in all remaining connectivity regions is taken as the total number of effective vegetation cover pixels for that plot.

[0044] Calculate the ratio of the total number of effective vegetation cover pixels to the total number of pixels in each independent, enclosed plot. Sort all independent, enclosed plots in descending order of this ratio. Set three ratio thresholds and divide the sorted plot sequence into four tiers based on the ratio from highest to lowest: plots in the top 25% of the ratio are assigned to the first tier; plots in the 25% to 50% are assigned to the second tier; plots in the 50% to 75% are assigned to the third tier; and plots in the bottom 25% are assigned to the fourth tier. Mark all plots in the first tier as Level 1 stable areas, all plots in the second tier as Level 2 stable areas, all plots in the third tier as Level 3 stable areas, and all plots in the fourth tier as Level 4 stable areas.

[0045] The stability level attributes obtained from matching each plot are used to assign attribute values ​​to the corresponding independent closed plots in the remote sensing orthophoto. The first-level stability zone is assigned a value of 4, the second-level stability zone is assigned a value of 3, the third-level stability zone is assigned a value of 2, and the fourth-level stability zone is assigned a value of 1. All plots with assigned values ​​are then stitched together within the spatial range of the remote sensing orthophoto to generate an initial spatial distribution layer of ecological stability level. Each pixel in this layer has a corresponding ecological stability level value.

[0046] Preferably, step S4: conduct a stability assessment of the ecological zoning of saline-alkali land based on the plot range of the subsurface salt accumulation risk layer to obtain saline-alkali land ecological stability assessment information.

[0047] Optionally, the specific details of determining the plot extent of the subsurface salt accumulation risk layer in step S4 are as follows: The initial spatial distribution layer of ecological stability level is compared with the subsurface salt accumulation risk layer by spatial location, and each independent closed plot is checked to see whether its spatial range overlaps with high- or medium-level salt accumulation risk areas. Land parcels with an initial risk level of Level 1 or 2 that spatially overlap with areas of high-level salt accumulation risk are included in the potential ecological fluctuation hazard set. Plots with an initial risk level of Level 1 or 2 that spatially overlap with areas of medium-level salt accumulation risk are also included in this hazard set; Generate a spatial mask to mark potential ecological disturbance sites and lock in the spatial extent of all potential ecological disturbance sites.

[0048] In this embodiment, the initial spatial distribution layer of ecological stability level and the subsurface salt accumulation risk layer are loaded into the same geographic coordinate system, with their spatial resolution uniformly set to 0.1 meters. The two layers are traversed pixel by pixel. For each independent closed plot, all pixel locations covered by that plot are extracted. Simultaneously, all pixel locations marked as high-level salt accumulation risk areas and all pixel locations marked as medium-level salt accumulation risk areas in the subsurface salt accumulation risk layer are extracted. Pixel by pixel, it is detected whether any pixel location within the plot simultaneously belongs to both the plot area and a high-level salt accumulation risk area. If at least one such pixel exists, it is determined that the plot and the high-level salt accumulation risk area spatially overlap. Similarly, it is detected pixel by pixel whether any pixel location within the plot simultaneously belongs to both the plot area and a medium-level salt accumulation risk area. If at least one such pixel exists, it is determined that the plot and the medium-level salt accumulation risk area spatially overlap.

[0049] The initial level attributes of each land parcel in the initial spatial distribution layer of ecological stability levels are read. If a land parcel's initial level is Level 1 or Level 2 stable and it spatially overlaps with a high-level salt accumulation risk area, it is included in the potential ecological fluctuation hazard set. Similarly, if a land parcel's initial level is Level 1 or Level 2 stable and it spatially overlaps with a medium-level salt accumulation risk area, it is also included in the potential ecological fluctuation hazard set. For land parcels with an initial level of Level 3 or Level 4 stable, regardless of whether they spatially overlap with any level of salt accumulation risk area, they are not included in the potential ecological fluctuation hazard set.

[0050] For all plots in the potential ecological fluctuation hazard set, extract all pixel locations covered by each plot, assign the value 1 to all pixel locations belonging to the set, and assign the value 0 to all pixel locations not belonging to the set, thus generating a spatial mask for hazard plot marking.

[0051] Optionally, step S4, which assesses the stability of saline-alkali land ecological zoning based on the plot extent of the subsurface salt accumulation risk layer, also includes: For all plots not included in the potential ecological fluctuation risk set, their initial ecological stability level remains unchanged and is directly output as the final stability level. For plots with potential hazards that are marked by spatial masks, the risk level will be downgraded based on the highest level of the overlapping risk areas. If the plots overlap with high-level salt accumulation risk areas, the risk level will be downgraded by two levels, down to the lowest level of level four stable area. If the plots overlap only with medium-level salt accumulation risk areas, the risk level will be downgraded by one level, down to the lowest level of level four stable area. All plots after the level was downgraded were spatially merged with the plots that were not adjusted to form a spatial distribution map of the final assessment results containing spatial distribution information of the four levels of stability. Output the spatial distribution map and the area statistics of each level of land parcel.

[0052] In this embodiment, all independent and enclosed plots are traversed, and the spatial mask values ​​for the hazard plot markers of each plot are read. When the spatial mask value for a plot is 0, the initial level attribute of that plot in the initial spatial distribution layer of ecological stability level is directly used as the final stability level output for that plot. When the spatial mask value for a plot is 1, the salt accumulation risk location level type overlapping with that plot in the subsurface salt accumulation risk layer is read. When the plot overlaps with a high-level salt accumulation risk location, the initial level is downgraded by two levels: Level 1 stability zone is downgraded to Level 3 stability zone, Level 2 stability zone is downgraded to Level 4 stability zone, and any level lower than Level 4 stability zone after downgrading is uniformly set to Level 4 stability zone. When a plot of land overlaps only with a medium-level salt accumulation risk area and not with a high-level salt accumulation risk area, the initial level will be downgraded by one level. The first-level stable area will be downgraded to the second-level stable area, the second-level stable area will be downgraded to the third-level stable area, and any area whose level is lower than the fourth-level stable area after downgrading will be uniformly set as the fourth-level stable area.

[0053] Specifically, the final stability level attributes of each land parcel after the hierarchical downgrading process are spatially merged with the final stability level attributes of land parcels not included in the hazard set. The images are then stitched together according to the spatial coordinates of each land parcel within the spatial range of the remote sensing orthophoto image to generate a spatial distribution map of the final assessment results containing the spatial distribution information of the four levels of stability. Each pixel in this distribution map has a corresponding final stability level value: the first-level stability zone is assigned a value of 4, the second-level stability zone is assigned a value of 3, the third-level stability zone is assigned a value of 2, and the fourth-level stability zone is assigned a value of 1.

[0054] The final evaluation spatial distribution map is calculated by counting the total number of pixels occupied by each level of stable zone. This total number of pixels is then multiplied by the ground area corresponding to each pixel. The ground area corresponding to a single pixel is determined by the ground spatial resolution of the remote sensing orthophoto. When the ground spatial resolution is 0.1 meters, the ground area corresponding to a single pixel is 0.01 square meters. This yields the statistical results of the ground area corresponding to each level of stable zone. The final evaluation spatial distribution map, along with statistical information on the areas of the first-level, second-level, third-level, and fourth-level stable zones, is output.

[0055] See Figure 4 The present invention also provides a system for assessing the ecological stability of saline-alkali land based on UAV remote sensing images, used to perform a method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images. The system includes: The salt frost landform recognition module 201 is used to collect remote sensing orthophotos of the target saline-alkali land by UAV, delineate the distribution area of ​​surface salt frost in the remote sensing orthophotos, and determine the distribution boundary of vegetation community. The salt accumulation plot marking module 202 is used to mark plots in remote sensing orthophotos that show traces of periodic salt frost precipitation, and to construct a global subsurface salt accumulation risk layer in combination with the vegetation community distribution boundary. The vegetation cover statistics module 203 is used to count the vegetation cover ratio based on remote sensing orthophotos, classify the ecological stability level according to the vegetation cover ratio, and output the ecological zoning of saline-alkali land. The ecological stability assessment module 204 is used to conduct stability assessments of saline-alkali land ecological zones based on the plot range of the subsurface salt accumulation risk layer, and obtain saline-alkali land ecological stability assessment information.

[0056] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0057] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images, characterized in that, Includes the following steps: Step S1: Collect remote sensing orthophotos of the target saline-alkali land by UAV, delineate the distribution area of ​​surface salt frost in the remote sensing orthophotos, and determine the distribution boundary of vegetation community. Step S2: Mark the plots in the remote sensing orthophotos that show traces of periodic salt frost precipitation, and construct a global subsurface salt accumulation risk layer by combining the vegetation community distribution boundaries; Step S3: Calculate the vegetation cover percentage based on remote sensing orthophotos, classify the ecological stability level according to the vegetation cover percentage, and output the saline-alkali land ecological zoning. Step S4: Conduct a stability assessment of the ecological zoning of saline-alkali land based on the plot range of the subsurface salt accumulation risk layer to obtain saline-alkali land ecological stability assessment information.

2. The method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images according to claim 1, characterized in that, Step S1 involves delineating the surface salt frost distribution area in the remote sensing orthophoto image, including: The entire surface contour boundary of the remote sensing orthophoto is traversed, and closed patches with continuous and uninterrupted loops or polygonal broken lines and higher internal pixel brightness uniformity than the surrounding bare soil area are extracted as the spatial range corresponding to the salt crust. The strip-shaped region extending along the outer edge of vegetation patches in the remote sensing orthophoto image and exhibiting a wave-like change in gray value from the inside to the outside, first increasing and then suddenly decreasing, is extracted as the spatial range corresponding to the powdery floating salt. For pixel regions with gray values ​​between withered grass and bare soil, contour competition matching based on local gray response peaks is performed. The local gray response peaks are connected to form closed or semi-closed trajectories, and the regions with average gray values ​​inside the trajectory lower than the gray values ​​of the external background are classified into the salt frost spatial distribution range.

3. The method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images according to claim 2, characterized in that, Step S1, which involves delineating the distribution areas of surface salt frost in the remote sensing orthophoto image, also includes: Retrieve multiple time-series remote sensing images covering the same target saline-alkali land, perform spatial alignment processing based on geographic coordinates on each time-series remote sensing image, and generate a time-series overlay image stack. In the temporal overlay image stack, the frequency of each spatial location being determined as the spatial range corresponding to the salt shell in all frames of images is counted, and the locations in all frames of images that have a consistent salt shell determination are marked as temporally stable salt shell primitives. Locations where only a single frame of the image shows salt crust and the corresponding locations in the remaining frames are bare soil backgrounds are marked as temporary surface salt patches.

4. The method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images according to claim 1, characterized in that, Step S1, determining the vegetation community distribution boundary, includes: The vegetation index is calculated on the remote sensing orthophoto. The connected regions of pixels whose vegetation index values ​​are consistently in the preset high range are extracted as the vegetation core area. The vegetation core area is extended outward along the outer edge of the vegetation core area to the position where the vegetation index value first drops to the preset bare soil reference value. The transition zone where vegetation and salt crust intersect is delineated by connecting the positions at this location. Within the transition zone, trace the unidirectional decreasing path of the vegetation index value from a preset high value range to a preset low value range, and connect the points on each unidirectional decreasing path where the vegetation index value is equal to the benchmark value for distinguishing vegetation from bare soil to form the initial boundary line. Spatial connectivity correction is performed on the initial boundary line, removing isolated short line segments that have no spatial connection with the main boundary line, and retaining the main line segments that extend continuously and curve along the outer edge of the vegetation. The area enclosed by the corrected main line segments is used as the solid distribution boundary of the salt-tolerant vegetation community.

5. The method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images according to claim 1, characterized in that, In step S2, the plots marked with periodic salt frost patterns in the remote sensing orthophoto image are specifically: The distribution range of surface salt frost in the whole region is traversed by grid. The grids in which the temporally stable salt crust units are covered in a continuous area and the salt crust units occupy the main salt frost in the grid are included in the set of periodic salt frost precipitation blocks. Grids containing only discontinuous areas of powdery floating salt along the vegetation edge and lacking a closed salt crust outline are marked as non-periodic surface salt patches. The first salt accumulation spatial mask is generated based on the overall spatial outer boundary of the set of periodically salt-frosting landmasses.

6. The method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images according to claim 5, characterized in that, In step S2, the areas marked with periodic salt bloom marks in the remote sensing orthophoto image also include: An annular scanning band is formed by pushing the boundary line of the salt-tolerant vegetation community outward to the outer edge of the powdery floating salt staining area. Within the annular scanning band, the gray value is detected as a convex peak-shaped gray profile feature that first increases and then decreases from the side near the boundary to the side away from the boundary. The annular area that extends continuously around the vegetation boundary and has the overall convex peak grayscale profile characteristics is marked as the salt-carrying zone of the vegetation root system. Using the closed curve of the outer edge of the salt accumulation zone away from vegetation as the spatial dividing line, the area on the side of the dividing line facing the vegetation is classified as the root-function type salt accumulation space, and the area on the side of the dividing line away from the vegetation is classified as the non-root bare salt space.

7. The method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images according to claim 1, characterized in that, In step S2, the construction of a global subsurface salt accumulation risk layer based on vegetation community distribution boundaries is specifically as follows: The core overlapping area is generated by performing spatial overlay and intersection operations on the first salt accumulation space mask covered by the time-stable salt crust primitive, the second salt accumulation space region covered by the salt accumulation zone of the vegetation root salt-carrying layer, and the boundary fracture point layer where the vegetation index value shows intermittent fractures on the vegetation boundary. Taking the geometric center of each core overlapping area as the starting point of radiation, and taking the direction of the longest diameter of the circumscribed ellipse of each overlapping area as the dominant direction of skeleton extension, the skeleton extends outward to the boundary of the adjacent non-overlapping area to form the initial risk skeleton line. The basic spatial framework of the subsurface salt accumulation risk layer is generated by widening the initial risk skeleton line to the adjacent vegetation boundary line on both sides and using the vegetation boundary line as a hard truncation constraint.

8. The method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images according to claim 1, characterized in that, In step S4, the specific scope of the plots in the subsurface salt accumulation risk layer is determined as follows: The initial spatial distribution layer of ecological stability level is compared with the subsurface salt accumulation risk layer by spatial location, and each independent closed plot is checked to see whether its spatial range overlaps with high- or medium-level salt accumulation risk areas. Land parcels with an initial risk level of Level 1 or 2 that spatially overlap with areas of high-level salt accumulation risk are included in the potential ecological fluctuation hazard set. Plots with an initial risk level of Level 1 or 2 that spatially overlap with areas of medium-level salt accumulation risk are also included in this hazard set; Generate a spatial mask to mark potential ecological disturbance sites and lock in the spatial extent of all potential ecological disturbance sites.

9. The method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images according to claim 8, characterized in that, Step S4 involves conducting a stability assessment of the saline-alkali land ecological zoning based on the land parcel extent of the subsurface salt accumulation risk layer. For all plots not included in the potential ecological fluctuation risk set, their initial ecological stability level remains unchanged and is directly output as the final stability level. For plots with potential hazards that are marked by spatial masks, the risk level will be downgraded based on the highest level of the overlapping risk areas. If the plots overlap with high-level salt accumulation risk areas, the risk level will be downgraded by two levels, down to the lowest level of level four stable area. If the plots overlap only with medium-level salt accumulation risk areas, the risk level will be downgraded by one level, down to the lowest level of level four stable area. All plots after the level was downgraded were spatially merged with the plots that were not adjusted to form a spatial distribution map of the final assessment results containing spatial distribution information of the four levels of stability. Output the spatial distribution map and the area statistics of each level of land parcel.

10. A system for assessing the ecological stability of saline-alkali land based on UAV remote sensing images, characterized in that, For executing the method for assessing the ecological stability of saline-alkali land based on UAV remote sensing images as described in claim 1, the system for assessing the ecological stability of saline-alkali land based on UAV remote sensing images comprises: The salt frost landform recognition module is used to collect remote sensing orthophotos of the target saline-alkali land from UAVs, delineate the distribution area of ​​surface salt frost in the remote sensing orthophotos, and determine the distribution boundary of vegetation communities. The salt accumulation plot marking module is used to mark plots in remote sensing orthophotos that show traces of periodic salt frost precipitation, and to construct a global subsurface salt accumulation risk layer by combining the vegetation community distribution boundary. The vegetation cover statistics module is used to count the vegetation cover percentage based on remote sensing orthophotos, classify the ecological stability level according to the vegetation cover percentage, and output the ecological zoning of saline-alkali land. The ecological stability assessment module is used to assess the stability of saline-alkali land ecological zones based on the plot range of the subsurface salt accumulation risk layer, and obtain saline-alkali land ecological stability assessment information.

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