CN-116934831-B - Tree canopy effective coverage estimation method and system based on three-dimensional point cloud data

CN116934831BCN 116934831 BCN116934831 BCN 116934831BCN-116934831-B

Abstract

The invention relates to a tree canopy effective coverage estimation method and system based on three-dimensional point cloud data. The tree canopy effective coverage estimation method and system based on the three-dimensional point cloud data comprise the steps of obtaining the three-dimensional point cloud data of a target area, preprocessing the three-dimensional point cloud data, setting pulses in the three-dimensional point cloud data, inputting the three-dimensional point cloud data into a tree canopy effective coverage estimation model, obtaining canopy data and weights of points on the pulses, and estimating the tree canopy effective coverage according to the three-dimensional point cloud data, the canopy data and the weights of the points on the pulses. The tree canopy effective coverage estimation method and system based on the three-dimensional point cloud data have the advantages of being simple in data acquisition mode, fast and accurate in calculating the tree canopy effective coverage.

Inventors

LI SHAORUI
ZHU ZHENCHANG
ZHU QIN
HE HAOMING
ZHANG YUAN
YANG ZHIFENG

Assignees

广东工业大学

Dates

Publication Date: 20260508
Application Date: 20230710

Claims (8)

1. A tree canopy effective coverage estimation method based on three-dimensional point cloud data is characterized by comprising the following steps: acquiring three-dimensional point cloud data of a target area; Preprocessing the three-dimensional point cloud data; setting pulses in the three-dimensional point cloud data; training a tree canopy effective coverage estimation model, comprising: acquiring three-dimensional point cloud training data of a preset area, and preprocessing the three-dimensional point cloud training data; dividing the three-dimensional point cloud data into small sample square point cloud data according to longitude and latitude points; extracting two data points at the left upper end of the small sample square point cloud data, and acquiring the widths of the two data points; setting pulses from left to right according to the width; labeling the coronary layer data, the non-coronary layer data and the weights of points on the pulse in the small sample square point cloud data; Taking the weight of the point on the pulse in the small sample square point cloud data and the weight of the point on the pulse as the input of the tree canopy effective coverage estimation model, and taking the ratio of the weight of the point on the pulse in the canopy data and the weight of the point on the pulse in the small sample square point cloud data as the output of the tree canopy effective coverage estimation model; Evaluating the accuracy of the tree canopy effective coverage estimation model through error analysis; and inputting the three-dimensional point cloud data into a tree canopy effective coverage estimation model, acquiring canopy data and the weights of points on the pulse, and estimating the tree canopy effective coverage according to the three-dimensional point cloud data, the canopy data and the weights of the points on the pulse.
2. The method for estimating the tree canopy effective coverage based on the three-dimensional point cloud data according to claim 1, wherein the step of obtaining the three-dimensional point cloud data of the target area comprises the steps of: acquiring an unmanned aerial vehicle route through route planning software according to the target area; and controlling the unmanned aerial vehicle to fly in the target area according to the unmanned aerial vehicle route, and acquiring three-dimensional point cloud data of the target area.
3. The method for estimating the tree canopy effective coverage based on the three-dimensional point cloud data according to claim 1, wherein the preprocessing of the three-dimensional point cloud data comprises the following steps: fitting the elevation of the data points in the three-dimensional point cloud data into a preprocessing elevation curve, obtaining a preprocessing slope mutation part in the preprocessing elevation curve, and taking the preprocessing slope mutation part as a preprocessing division point; acquiring preliminary data of ground data points and non-ground data points according to the preprocessing partition points, and selecting a designated field according to the preliminary data; Calculating a high Cheng Panduan value for each data point in the specified domain; if the elevation judgment value is higher than a preset threshold value, the data point is a non-ground point, and if the elevation judgment value is lower than the preset threshold value, the data point is a ground point; and subtracting the ground point from the data points in the three-dimensional point cloud data to obtain normalized three-dimensional point cloud data.
4. The method for estimating the coverage of tree canopy based on three-dimensional point cloud data according to claim 3, wherein the preprocessing of the three-dimensional point cloud data further comprises the steps of: setting a sphere radius for each data point in the point cloud data, and counting the number of neighbor points in the sphere radius; And if the number of the neighbor points is smaller than a set threshold value, defining the data points as isolated points, and deleting the isolated points.
5. The method for estimating the tree canopy effective coverage based on the three-dimensional point cloud data according to claim 1, wherein the labeling of canopy data, non-canopy data and weights of points on pulses in the small sample side point cloud data comprises the following steps: fitting the elevation numerical value of the data point in the small sample square point cloud data into an elevation curve; Acquiring a slope abrupt change position of the elevation curve, and taking the slope abrupt change position as a division point; labeling canopy data and non-canopy data of the small sample square point cloud data according to the segmentation points; and extracting the point on each pulse, and calculating and marking the weight of the point on each pulse.
6. A tree canopy effective coverage estimation system based on three-dimensional point cloud data, comprising: the data acquisition device is used for acquiring three-dimensional point cloud data of the target area; the data preprocessing device is used for preprocessing the three-dimensional point cloud data; pulse setting means for setting a pulse in the three-dimensional point cloud data; an effective coverage estimation device for training a tree canopy effective coverage estimation model, comprising: acquiring three-dimensional point cloud training data of a preset area, and preprocessing the three-dimensional point cloud training data; dividing the three-dimensional point cloud data into small sample square point cloud data according to longitude and latitude points; extracting two data points at the left upper end of the small sample square point cloud data, and acquiring the widths of the two data points; setting pulses from left to right according to the width; labeling the coronary layer data, the non-coronary layer data and the weights of points on the pulse in the small sample square point cloud data; Taking the weight of the point on the pulse in the small sample square point cloud data and the weight of the point on the pulse as the input of the tree canopy effective coverage estimation model, and taking the ratio of the weight of the point on the pulse in the canopy data and the weight of the point on the pulse in the small sample square point cloud data as the output of the tree canopy effective coverage estimation model; Evaluating the accuracy of the tree canopy effective coverage estimation model through error analysis; and inputting the three-dimensional point cloud data into a tree canopy effective coverage estimation model, acquiring canopy data and the weights of points on the pulse, and estimating the tree canopy effective coverage according to the three-dimensional point cloud data, the canopy data and the weights of the points on the pulse.
7. Computer device comprising a processor, a memory and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the tree canopy effective coverage estimation method based on three-dimensional point cloud data according to any of claims 1 to 5 when the computer program is executed by the processor.
8. A computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the steps of the tree canopy coverage estimation method based on three-dimensional point cloud data according to any one of claims 1 to 5.

Description

Tree canopy effective coverage estimation method and system based on three-dimensional point cloud data Technical Field The invention relates to the technical field of tree canopy effective coverage monitoring, in particular to a tree canopy effective coverage estimation method and system based on three-dimensional point cloud data. Background Mangrove is woody plant community growing in the tidal zone of the coast of the tropical and subtropical zone and periodically submerged by seawater, has great ecological value and social value, and especially has strong carbon fixing capability for the mangrove ecological system. The biomass of mangrove forest is estimated to have great carbon fixing capacity, and the biomass of mangrove forest and the canopy of tree have great correlation and the effective canopy coverage of tree is also one indispensable parameter. The existing method for extracting the effective coverage of the tree is mainly based on an image, the proportion of vegetation is analyzed by utilizing the difference of vegetation and soil pixels, so that the effective coverage of the tree is obtained, and the effective coverage of the canopy is difficult to extract because the image is a two-dimensional model. There are, of course, also tree canopy effective coverage estimates based on canopy height models, but their grid size and height thresholds are difficult to determine. Disclosure of Invention Based on the above, the invention aims to provide a tree canopy effective coverage estimation method and system based on three-dimensional point cloud data, which have the advantage of rapidly, simply and accurately estimating the tree canopy effective coverage. A tree canopy effective coverage estimation method based on three-dimensional point cloud data comprises the following steps: acquiring three-dimensional point cloud data of a target area; Preprocessing the three-dimensional point cloud data; setting pulses in the three-dimensional point cloud data; and inputting the three-dimensional point cloud data into a tree canopy effective coverage estimation model, acquiring canopy data and the weights of points on the pulse, and estimating the tree canopy effective coverage according to the three-dimensional point cloud data, the canopy data and the weights of the points on the pulse. A tree canopy effective coverage estimation system based on three-dimensional point cloud data, comprising: the data acquisition device is used for acquiring three-dimensional point cloud data of the target area; the data preprocessing device is used for preprocessing the three-dimensional point cloud data; pulse setting means for setting a pulse in the three-dimensional point cloud data; the effective coverage estimating device is used for inputting the three-dimensional point cloud data into a tree canopy effective coverage estimating model, acquiring canopy data and weights of points on the pulse, and estimating the tree canopy effective coverage according to the three-dimensional point cloud data, the canopy data and the weights of the points on the pulse. A computer device comprising a processor, a memory and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the tree canopy effective coverage estimation method based on three-dimensional point cloud data as described above when the computer program is executed. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of the tree canopy effective coverage estimation method based on three-dimensional point cloud data as described above. According to the tree canopy effective coverage estimation method based on the three-dimensional point cloud data, the three-dimensional point cloud data in the target area are obtained and preprocessed, then pulses are set in the three-dimensional point cloud data, finally the three-dimensional point cloud data are input into a tree canopy effective coverage estimation model, the weight of points on the crown data and the pulses is obtained, and the tree canopy effective coverage is estimated according to the three-dimensional point cloud data, the crown data and the weight of the points on the pulses. The tree canopy effective coverage estimation method based on the three-dimensional point cloud data is simple in data acquisition mode and does not damage the original environment, and in the tree canopy effective coverage estimation, weight estimation is adopted, so that the accuracy of coverage estimation is further improved. For a better understanding and implementation, the present invention is described in detail below with reference to the drawings. Drawings FIG. 1 is a flow chart of steps of a tree canopy effective coverage estimation method based on three-dimensional point cloud data in an embodiment of the application; FIG. 2 is a flowchart illustrating steps for acquiring three-dimensio