Biomass Inversion of Highway Slope Based on Unmanned Aerial Vehicle Remote Sensing and Deep Learning

被引:2
|
作者
Hao, Guangcun [1 ,2 ]
Dong, Zhiliang [1 ,2 ]
Hu, Liwen [1 ,2 ]
Ouyang, Qianru [3 ]
Pan, Jian [4 ]
Liu, Xiaoyang [3 ]
Yang, Guang [3 ,5 ]
Sun, Caige [3 ,5 ]
机构
[1] CCCC Fourth Harbor Engn Inst Co Ltd, Guangzhou 510230, Peoples R China
[2] CCCC, Key Lab Environm & Safety Technol Transportat Infr, Guangzhou 510230, Peoples R China
[3] South China Normal Univ, Sch Geog, Guangzhou 510631, Peoples R China
[4] Guangxi Pinglu Canal Construct Co Ltd, Nanning 530022, Peoples R China
[5] SCNU Qingyuan Inst Sci & Technol Innovat Co Ltd, Qingyuan 511517, Peoples R China
来源
FORESTS | 2024年 / 15卷 / 09期
关键词
deep learning; slope; vegetation biomass; UVA remote sensing; FOREST BIOMASS; VEGETATION; SOIL; IMAGE; COMBINATIONS; STATISTICS; INDEXES; RATIO; LEAF; RED;
D O I
10.3390/f15091564
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Biomass can serve as an important indicator for measuring the effectiveness of slope ecological restoration, and unmanned aerial vehicle (UAV) remote sensing provides technical support for the rapid and accurate measurement of vegetation biomass on slopes. Considering a highway slope as the experimental area, in this study, we integrate UAV data and Sentinel-2A images; apply a deep learning method to integrate remote sensing data; extract slope vegetation features from vegetation probability, vegetation indices, and vegetation texture features; and construct a slope vegetation biomass inversion model. The R2 of the slope vegetation biomass inversion model is 0.795, and the p-value in the F-test is less than 0.01, which indicates that the model has excellent regression performance and statistical significance. Based on laboratory biomass measurements, the regression model error is small and reasonable, with RMSE = 0.073, MAE = 0.064, and SE = 0.03. The slope vegetation biomass can be accurately estimated using remote-sensing images with a high precision and good applicability. This study will provide a methodological reference and demonstrate its application in estimating vegetation biomass and carbon stock on highway slopes, thus providing data and methodological support for the simulation of the carbon balance process in slope restoration ecosystems.
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收藏
页数:15
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