Method for estimating overground biomass of fresh songarus apetalus plant through photography

Abstract

The invention discloses a method for estimating overground biomass of a fresh songarus apetalus plant through photography. The method comprises the steps that five-lens oblique photography equipment obtains images of the fresh songarus apetalus plant land in the front view direction and the front, back, left and right directions; based on an improved CatBoost algorithm and the geographic position, the diameter at breast height, the crown breadth and the tree height of each tree, a geographic position weighted tree growth parameter nonlinear mapping model is constructed, and the tree growth parameter nonlinear mapping model is used for obtaining the diameter at breast height according to different geographic positions, the tree heights and the crown breadth; acquiring an image of a to-be-estimated fresh songarus apetala plant field in front view and front, back, left and right directions; the predicted diameter at breast height and the corresponding tree height are obtained from the obtained image, and the above-ground biomass of the fresh songarus apetalus plant of the image is obtained through calculation of the predicted diameter at breast height and the corresponding tree height based on a different-speed growth equation. According to the method, the overground biomass of the fresh songarus apetala plants can be estimated through low-cost and high-efficiency photography.

Description

Technical Field

[0001] The present invention relates to the field of estimating the aboveground biomass of fresh Sonneratia apetala plants, and in particular to a method for estimating the aboveground biomass of fresh Sonneratia apetala plants by photography. Background Art

[0002] Sonneratia apetala grows primarily on the outer edges of intertidal zones, making remote sensing the most effective method for measuring the distribution and biomass of this invasive mangrove. Existing methods often rely on expensive LiDAR data sources to estimate the biomass of Sonneratia apetala plants through interferometric coherence. Consumer drones can only capture images from a fixed perspective, requiring multiple flights to capture stereo image pairs from different angles. This inefficient multi-view image acquisition process has led to a lack of cost-effective methods for estimating the biomass of live Sonneratia apetala plants. Summary of the Invention

[0003] The object of the present invention is to provide a method for estimating the aboveground biomass of fresh Sonneratia apetala plants by using five-lens oblique photography, aiming to solve the problem of efficiently estimating the aboveground biomass of fresh Sonneratia apetala plants.

[0004] The present invention provides a method for estimating the aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography, comprising: S1. Obtain optical stereo images of the study area in the front, front, back, left and right directions using a five-lens oblique photography device; S2. Processing the optical stereoscopic image of the study area to obtain three-dimensional point cloud data; S3, generating a digital surface model and a digital elevation model after merging, denoising and separating ground points of the 3D point cloud data; S4, normalizing the data after ground point separation in S3 to obtain preprocessed data; S5, obtaining a canopy height model based on the digital surface model and the digital elevation model, generating seed points based on the canopy height model, and performing single tree segmentation based on the seed points to obtain a segmentation result; S6. For the patches obtained from the segmentation results, remove the patches containing trees that are not Sonneratia apetala based on tree height, count the crown width and tree height of Sonneratia apetala plants in each patch, and obtain the geographical location of each Sonneratia apetala plant in the study area based on ground survey data; S7. Based on the improved CatBoost algorithm and the geographical location, diameter at breast height, crown width, and tree height of the trees, constructing a geographical location-weighted nonlinear mapping model of tree growth parameters, wherein the nonlinear mapping model of tree growth parameters is used to predict the diameter at breast height based on the location, tree height, and crown width of Sonneratia apetala plants at different geographical locations; S8. predicting the diameter at breast height of Sonneratia apetala plants using the tree growth parameter nonlinear mapping model; S9. Based on the allometric growth equation, the aboveground biomass of fresh Sonneratia apetala plants was calculated using the tree height and predicted DBH of the Sonneratia apetala plants.

[0005] By adopting the embodiment of the present invention, the present invention can realize low-cost and high-efficiency photographic estimation of the aboveground biomass of fresh Sonneratia apetala plants.

[0006] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it is implemented in accordance with the contents of the specification, and in order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0008] Figure 1 4 is a flow chart of a method for estimating aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography according to an embodiment of the present invention; Figure 2 2. It is a schematic diagram of point cloud data preprocessing results of estimating aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography according to an embodiment of the present invention; Figure 3 2. This is a schematic diagram of the result of generating seed points for estimating the aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography according to an embodiment of the present invention; Figure 4 2. It is a schematic diagram of single tree segmentation and extraction results of estimating aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography according to an embodiment of the present invention; Figure 5 Schematic diagram of the tree height of Sonneratia apetala plants for estimating the aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography according to an embodiment of the present invention. DETAILED DESCRIPTION

[0009] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0010] Method Example According to an embodiment of the present invention, a flow chart of a method for estimating aboveground biomass of live Sonneratia apetala plants using five-lens oblique photography is provided. Figure 1 FIG. 1 is a flow chart of a method for estimating aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography according to an embodiment of the present invention. Figure 1 As shown, specifically including: S1. Obtain optical stereoscopic imaging data of the study area in the frontal, frontal, and left and right directions; In an embodiment of the present invention, a five-lens oblique camera module is used to obtain optical stereo imaging data of an area of interest containing fresh Sonneratia apetala plants in frontal, frontal, left, and right directions of an island; S2. Processing the image of the fresh Sonneratia apetala plant site to obtain LAS three-dimensional point cloud data; S3, merging, denoising and ground point separation of LAS 3D point cloud data to generate digital surface model and digital elevation model; The generating of the digital surface model and the digital elevation model based on the classified data specifically includes: inputting the point cloud data into any oblique photography software to generate the digital surface model and the digital elevation model.

[0011] S4, normalize the data after ground point separation in S3 to obtain pre-processed data, such as Figure 2 As shown; S5. Obtain a canopy height model based on the digital surface model and the digital elevation model, and generate seed points based on the canopy height model, such as Figure 3 As shown, single tree segmentation is performed based on the seed point to obtain the single tree segmentation result; The canopy height model based on the digital surface model and digital elevation model specifically includes: The canopy height model is obtained by subtracting the digital surface model from the digital elevation model.

[0012] In the embodiment of the present invention, the digital elevation model is in the form of an ordered numerical matrix.

[0013] The result of subtracting the digital elevation model (DEM) from the digital surface model (DSM) is the relative height information of surface cover (such as buildings, vegetation, etc.), that is, the vertical height of the surface cover.

[0014] The method of obtaining a segmentation result based on the seed point specifically includes: performing single tree segmentation according to the seed point and pre-processed data to obtain an initial segmentation result; setting constraint conditions to correct the seed point according to the initial segmentation result to obtain a corrected seed point; performing a second single tree segmentation according to the corrected seed point and pre-processed data to obtain a segmentation result, such as Figure 4 As shown, the white ones are others, and the colored ones are the Sonneratia apetala plants.

[0015] The constraints include: minimum crown diameter, minimum distance between trees and crown width data. The seed points are modified by human-computer interactive editing.

[0016] S6. For the patches obtained from the segmentation results, remove the patches containing trees that are not Sonneratia apetala based on tree height, count the crown width and tree height of Sonneratia apetala plants in each patch, and obtain the geographical location of each Sonneratia apetala plant in the study area based on ground survey data; Figure 5 This is a schematic diagram of the tree height of Sonneratia apetala plants for estimating the aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography according to an embodiment of the present invention. Different colors represent different Sonneratia apetala heights.

[0017] S7. Based on the improved CatBoost algorithm and the geographical location, diameter at breast height, crown width, and tree height of the trees, constructing a geographical location-weighted nonlinear mapping model of tree growth parameters, wherein the nonlinear mapping model of tree growth parameters is used to predict the diameter at breast height based on the location, tree height, and crown width of Sonneratia apetala plants at different geographical locations; In an embodiment of the present invention, an improved CatBoost algorithm is used to construct geographical location and diameter at breast height data from ground survey data, and a nonlinear mapping model of tree growth parameters is constructed to accurately depict the complex relationship between geographical location, diameter at breast height, tree height and crown width. The geographical location includes longitude, latitude and altitude, and the diameter at breast height is obtained based on the geographical location, tree height and crown width of Sonneratia apetala.

[0018] S8. predicting the diameter at breast height of Sonneratia apetala plants using the tree growth parameter nonlinear mapping model; S9. Based on the allometric growth equation, the aboveground biomass of fresh Sonneratia apetala plants was calculated using the tree height and predicted DBH of the Sonneratia apetala plants.

[0019] In an embodiment of the present invention, the aboveground biomass of fresh Sonneratia apetala plants is calculated based on the allometric growth equation, using the tree height obtained by tree segmentation and the DBH predicted by the model. The allometric growth equation of Sonneratia apetala plants is: , Where, W is the aboveground biomass of fresh Sonneratia apetala plants, D is the predicted DBH of Sonneratia apetala plants, in cm; H is the height of the Sonneratia apetala plant, in meters, where .

[0020] The beneficial effects of the present invention are as follows: The present invention uses a five-lens tilted camera to capture the aboveground biomass of Sonneratia apetala plants, solving the problems of high cost and poor anti-interference of laser radar and low efficiency of image acquisition by consumer-grade drones. The present invention processes optical stereo imaging data into LAS 3D point cloud data; performs tree segmentation using a human-computer interactive editing method for seed points; and constructs a nonlinear mapping model of tree growth parameters based on ground survey data using an improved CatBoost algorithm. This method predicts the DBH of Sonneratia apetala plants; constructs an allometric growth equation based on the tree height and predicted DBH, and calculates the aboveground biomass of live Sonneratia apetala plants. This method enables efficient and rapid estimation of the aboveground biomass of Sonneratia apetala.

[0021] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. These modifications or replacements of the technical solutions of the embodiments of the present invention do not cause the essence of the corresponding technical solutions to deviate from the scope of this solution.

Claims

1. A method for estimating the aboveground biomass of fresh Sonneratia apetala plants using five-lens oblique photography, characterized in that: include, S1. Obtain optical stereo images of the study area in the front, front, back, left and right directions using a five-lens oblique photography device; S2. Processing the optical stereoscopic image of the study area to obtain three-dimensional point cloud data; S3, generating a digital surface model and a digital elevation model after merging, denoising and separating ground points of the 3D point cloud data; S4, normalizing the data after ground point separation in S3 to obtain preprocessed data; S5, obtaining a canopy height model based on the digital surface model and the digital elevation model, generating seed points based on the canopy height model, and performing single tree segmentation based on the seed points to obtain a segmentation result; S6. For the patches obtained from the segmentation results, remove the patches containing trees that are not Sonneratia apetala based on tree height, count the crown width and tree height of Sonneratia apetala plants in each patch, and obtain the geographical location of each Sonneratia apetala plant in the study area based on ground survey data; S7. Based on the improved CatBoost algorithm and the geographical location, diameter at breast height, crown width, and tree height of the trees, constructing a geographical location-weighted nonlinear mapping model of tree growth parameters, wherein the nonlinear mapping model of tree growth parameters is used to predict the diameter at breast height based on the location, tree height, and crown width of Sonneratia apetala plants at different geographical locations; S8. predicting the diameter at breast height of Sonneratia apetala plants using the tree growth parameter nonlinear mapping model; S9. Based on the allometric growth equation, the aboveground biomass of fresh Sonneratia apetala plants was calculated using the tree height and predicted DBH of the Sonneratia apetala plants.

2. The method according to claim 1, characterized in that Said S1 specifically comprises: using a five-lens oblique camera to obtain optical stereo images of the field of living Sonneratia apetala plants in the front view and front, back, left and right directions.

3. The method according to claim 1, characterized in that The method of obtaining a canopy height model based on a digital surface model and a digital elevation model specifically includes: The canopy height model is obtained by subtracting the digital surface model from the digital elevation model.

4. The method according to claim 1, wherein The method of obtaining a segmentation result based on the seed point specifically includes: performing single tree segmentation according to the seed point and preprocessed data to obtain an initial segmentation result, correcting the seed point according to the initial segmentation result by setting constraint conditions, and performing a second single tree segmentation according to the corrected seed point and preprocessed data to obtain a segmentation result.

5. The method according to claim 4, characterized in that The constraints include: minimum crown diameter, minimum distance between trees and crown width range data.

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