CN-121540647-B - Water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing

CN121540647BCN 121540647 BCN121540647 BCN 121540647BCN-121540647-B

Abstract

The application provides a water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing, and relates to the technical field of image analysis. The method comprises the steps of firstly collecting multispectral image data and laser point cloud data to generate a first vegetation index change map, constructing a digital surface model, obtaining terrain change point cloud data through the digital surface model, then carrying out space superposition analysis on the change map and the point cloud data to obtain a space superposition area, extracting vegetation change map spots and terrain deformation map spots which are in the space superposition area and accord with a first preset condition to obtain a potential erosion area, then dividing the active erosion area from the terrain change point cloud data according to three-dimensional point cloud characteristics, calculating soil loss according to the three-dimensional point cloud data, and finally generating a water and soil conservation monitoring result according to space distribution information of the active erosion area and the soil loss.

Inventors

LI PING
ZHANG RUI
ZHANG PING
Liu Qionghai

Assignees

黄河水利委员会晋陕蒙接壤地区水土保持监督局

Dates

Publication Date: 20260508
Application Date: 20260116

Claims (9)

1. The water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing is characterized by comprising the following steps of: generating a three-dimensional flight path of the unmanned aerial vehicle according to a historical erosion trench distribution diagram of the target monitoring slope surface so as to control the unmanned aerial vehicle to acquire multispectral image data and laser point cloud data of the target monitoring slope surface along the three-dimensional flight path; Generating a first vegetation index change map of the target monitoring slope according to the multispectral image data; Constructing a digital surface model of the target monitoring slope according to the laser point cloud data, and comparing the digital surface model with a preset reference digital surface model to obtain terrain change point cloud data; carrying out space superposition analysis on the first vegetation index change map and the terrain change point cloud data to obtain a space superposition area, and extracting vegetation change map spots and terrain deformation map spots which accord with a first preset condition in the space superposition area to obtain a potential erosion area; According to the three-dimensional point cloud characteristics corresponding to the potential erosion areas, segmenting an active erosion area from the terrain change point cloud data, and calculating soil loss according to the three-dimensional point cloud data of the active erosion area; Generating a water and soil conservation monitoring result according to the spatial distribution information of the active erosion area and the soil loss; the step of segmenting the active erosion area from the terrain change point cloud data according to the three-dimensional point cloud characteristics corresponding to the potential erosion area comprises the following steps: extracting points located in the potential erosion area from the terrain change point cloud data to form a first point cloud set; calculating a plurality of characteristic parameters of each terrain change point in the first point cloud set, wherein the characteristic parameters comprise the inclination angle of a normal vector of the terrain change point, the point density in a preset range around the terrain change point and the elevation change gradient of the terrain change point along the direction of a target monitoring slope; determining terrain change points in the first point cloud set according to the characteristic parameters, and determining points with inclination angles of normal vectors larger than a preset inclination angle threshold value, point densities smaller than a preset density threshold value and elevation change gradients larger than a first preset gradient threshold value as erosion characteristic points; clustering the erosion feature points, and aggregating the erosion feature points with the three-dimensional space distance smaller than a preset distance threshold value into a point cloud cluster; Screening point cloud clusters with the number of the terrain change points larger than a preset number threshold value from all the point cloud clusters, and taking the point cloud clusters as alternative erosion clusters; Marking alternative erosion clusters in a buffer zone of ravines identified by the historical erosion trench profile as active erosion zones; And calculating the average elevation change gradient of all points in each alternative erosion cluster from the rest alternative erosion clusters, and marking the alternative erosion clusters with the average elevation change gradient larger than a second preset gradient threshold as active erosion areas.
2. The method of claim 1, wherein generating a first vegetation index change map of the target monitored slope from the multispectral image data comprises: the first multispectral image and the second multispectral image of the target monitoring slope are respectively acquired at a first preset time point and a second preset time point; respectively calculating a first vegetation index distribution diagram of the target monitoring slope at the first preset time point and a second vegetation index distribution diagram of the target monitoring slope at the second preset time point based on the reflectivity data of the red light wave band and the near infrared wave band in the first multispectral image and the second multispectral image; dividing the target monitoring slope into a plurality of analysis units, and determining the dominant slope direction of each analysis unit according to the slope area covered by the three-dimensional flight path; Performing illumination condition compensation on the vegetation index values of the first vegetation index distribution diagram and the second vegetation index distribution diagram in the analysis units, and calculating a vegetation index difference value of each analysis unit between the second preset time point and the first preset time point after the illumination condition compensation is completed; Superposing the historical erosion groove distribution map of the target monitoring slope with the analysis unit to obtain a second analysis unit; And adjusting the vegetation index difference value of the second analysis unit through a preset first adjustment coefficient to generate a first vegetation index change chart.
3. The method of claim 1, wherein constructing a digital surface model of the target monitoring slope from the laser point cloud data comprises: classifying the laser point cloud data to obtain a ground point cloud subset and non-ground points Yun Ziji; Calculating the point cloud density weight of each target point in the ground point cloud subset according to the flight angle of each navigation band in the three-dimensional flight path; constructing an initial triangular mesh model in the area where the target monitoring slope is based on the three-dimensional coordinates of each target point in the ground point cloud subset and the corresponding point cloud density weight; Identifying triangular patches which are overlapped with the historical erosion ditch distribution diagram of the target monitoring slope in the initial triangular mesh model in space and taking the triangular patches as patches to be processed; According to the trend of the erosion furrows in the historical erosion furrow distribution diagram, adjusting the point cloud density weight of the target point contained in the to-be-processed surface patch, and performing curved surface reconstruction on the to-be-processed surface patch by using the adjusted point cloud density weight to obtain a target surface patch; And merging the target surface patch with the triangular surface patches except the surface patch to be processed in the initial triangular network model to obtain a digital surface model.
4. The method of claim 1, wherein extracting vegetation change map and topography deformation map meeting a first predetermined condition in the spatially coincident region to obtain a potential erosion region comprises: Determining a plurality of candidate subareas in the space coincidence region; Acquiring a vegetation index change value corresponding to each candidate subarea from the first vegetation index change map, and acquiring a terrain deformation value corresponding to each candidate subarea from the terrain change point cloud data; marking the candidate subarea with the vegetation index change value smaller than a first preset threshold value as a vegetation degradation subarea; Marking the candidate subareas with the absolute values of the terrain deformation values larger than a second preset threshold value as surface deformation subareas; Identifying candidate subareas marked as vegetation degradation subareas and surface deformation subareas simultaneously as alternative erosion subareas; determining the alternative erosion sub-region as a potential erosion region within the spatial range covered by the historical erosion trench profile; and determining a potential erosion area from the alternative erosion subarea according to the consistency of the vegetation index change value and the change direction of the terrain deformation value in the alternative erosion subarea in the uncovered space range of the historical erosion ditch distribution diagram.
5. The method of claim 1, wherein calculating the soil erosion amount from the three-dimensional point cloud data of the active erosion zone comprises: generating a current terrain surface model of the active erosion area based on the three-dimensional point cloud data of the active erosion area; acquiring a target reference terrain surface model corresponding to the active erosion area; Comparing the current terrain surface model with the target reference terrain surface model to obtain an elevation change value of each sampling point in the active erosion area; calculating the preliminary soil loss volume of the active erosion area according to the elevation change value; acquiring a slope direction corresponding to the active erosion area, and determining a volume correction coefficient according to the slope direction; correcting the preliminary soil loss volume by using the volume correction coefficient to obtain an intermediate soil loss volume; Acquiring a historical erosion intensity level of the active erosion area, and determining a soil volume weight parameter according to the historical erosion intensity level; and calculating the soil loss amount of the active erosion area according to the intermediate soil loss volume and the soil volume weight parameter.
6. The method of claim 1, wherein generating a soil and water conservation monitoring result based on the spatial distribution information of the active erosion area and the soil loss amount comprises: acquiring soil loss of each active erosion area, and dividing the active erosion area into a plurality of loss levels according to a preset loss threshold range; from the active erosion areas with the multiple erosion levels, the erosion level of the active erosion area with the spatial position within a preset range of the extending direction of the ravines marked by the historical erosion trench distribution diagram is increased by one level; According to the central point coordinates of each active erosion area, calculating the relative position of each active erosion area on the target monitoring slope, and sequencing the active erosion areas after the level is increased based on the relative position to generate an area distribution sequence; Marking active erosion areas with corresponding grades and positions on a digital surface model of the target monitoring slope according to the area distribution sequence, and generating a water and soil loss grade distribution map; and integrating the soil loss amount and the water and soil loss level distribution map of each active erosion area, and outputting a water and soil conservation monitoring result.
7. A water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing, which is applied to the water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing as claimed in any one of claims 1 to 6, and is characterized by comprising: the acquisition module is used for generating a three-dimensional flight path of the unmanned aerial vehicle according to the historical erosion trench distribution diagram of the target monitoring slope so as to control the unmanned aerial vehicle to acquire multispectral image data and laser point cloud data of the target monitoring slope along the three-dimensional flight path; the first calculation module is used for generating a first vegetation index change map of the target monitoring slope according to the multispectral image data; The construction module is used for constructing a digital surface model of the target monitoring slope according to the laser point cloud data, and comparing the digital surface model with a preset reference digital surface model to obtain terrain change point cloud data; the analysis module is used for carrying out space superposition analysis on the first vegetation index change map and the terrain change point cloud data to obtain a space superposition area, and extracting vegetation change map spots and terrain deformation map spots which accord with a first preset condition in the space superposition area to obtain a potential erosion area; The second calculation module is used for dividing an active erosion area from the terrain change point cloud data according to the three-dimensional point cloud characteristics corresponding to the potential erosion area, and calculating the soil loss according to the three-dimensional point cloud data of the active erosion area; And the generation module is used for generating a water and soil conservation monitoring result according to the spatial distribution information of the active erosion area and the soil loss.
8. The computing device is characterized by comprising a processing component and a storage component, wherein the storage component stores one or more computer instructions, and the one or more computer instructions are used for being invoked and executed by the processing component to realize the water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing according to any one of claims 1-6.
9. A computer storage medium, wherein a computer program is stored, and when the computer program is executed by a computer, the method for monitoring water and soil conservation based on unmanned aerial vehicle remote sensing according to any one of claims 1 to 6 is realized.

Description

Water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing Technical Field The application relates to the technical field of image analysis, in particular to a water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing. Background Along with the increasing refinement of the requirements for water and soil conservation supervision of production and construction projects and natural sloping fields, how to quickly and accurately master the soil erosion dynamics of specific slopes, especially the areas with historic erosion grooves, becomes an urgent requirement for current monitoring work. The technical scheme adopted at present comprises the steps of acquiring optical images and laser point cloud data of a monitoring area by using an unmanned aerial vehicle, firstly analyzing multispectral images, delineating vegetation degradation ranges by comparing vegetation indexes in different periods, simultaneously processing the laser point cloud data to generate a digital elevation model, extracting an earth surface deformation area by comparing the digital elevation model with a historical model, finally performing direct spatial superposition on the vegetation degradation ranges and the earth surface deformation area, judging the superposition area of the vegetation degradation ranges and the earth surface deformation area as a soil erosion area, and estimating soil loss based on point cloud change of the area. However, the existing scheme has obvious limitation on the accuracy and reliability of monitoring results in practical application, particularly in complex slope scenes of gully development, is extremely easy to introduce misjudgment due to the fact that the mechanism difference and space-time consistency of multispectral data and laser point cloud data in representing the surface change are not fully considered, such as misjudgment of vegetation change caused by crop harvesting as degradation caused by erosion, and more importantly, fails to integrate the historical erosion pattern and evolution rule of a monitoring area into an analysis flow as key priori knowledge, so that the judgment of erosion activity lacks constraint of historical continuity, is insensitive to the identification of new erosion trenches, and is difficult to accurately evaluate the activation degree and the development trend of the existing erosion trenches Disclosure of Invention The application provides a water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing, which are used for solving the problem that complex slope erosion monitoring accuracy is low due to the fact that multi-source data fusion analysis is coarse and historical erosion priori information is not utilized enough in the prior art. In a first aspect, the application provides a water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing, which comprises the following steps: generating a three-dimensional flight path of the unmanned aerial vehicle according to a historical erosion trench distribution diagram of the target monitoring slope surface so as to control the unmanned aerial vehicle to acquire multispectral image data and laser point cloud data of the target monitoring slope surface along the three-dimensional flight path; Generating a first vegetation index change map of the target monitoring slope according to the multispectral image data; Constructing a digital surface model of the target monitoring slope according to the laser point cloud data, and comparing the digital surface model with a preset reference digital surface model to obtain terrain change point cloud data; Carrying out space superposition analysis on the first vegetation index change map and the terrain change point cloud data to obtain a space superposition area, and extracting vegetation change map spots and terrain deformation map spots which are in the space superposition area and accord with a first preset condition to obtain a potential erosion area; According to the three-dimensional point cloud characteristics corresponding to the potential erosion areas, segmenting an active erosion area from the terrain change point cloud data, and calculating soil loss according to the three-dimensional point cloud data of the active erosion area; and generating a water and soil conservation monitoring result according to the spatial distribution information of the active erosion area and the soil loss. Optionally, generating a first vegetation index change map of the target monitoring slope according to the multispectral image data includes: the first multispectral image and the second multispectral image of the target monitoring slope are respectively acquired at a first preset time point and a second preset time point; respectively calculating a first vegetation index distribution diagram of the target monitoring slope at t