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Identifying Regenerated Saplings by Stratifying Forest Overstory Using Airborne LiDAR Data  ( SCI-EXPANDED收录 EI收录)   被引量:5

文献类型:期刊文献

英文题名:Identifying Regenerated Saplings by Stratifying Forest Overstory Using Airborne LiDAR Data

作者:Du, Liming[1,2] Pang, Yong[1,2]

第一作者:杜黎明;Du, Liming

通信作者:Pang, Y[1];Pang, Y[2]

机构:[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Natl Forestry & Grassland Adm, Key Lab Forestry Remote Sensing & Informat Syst, Beijing 100091, Peoples R China

年份:2024

卷号:6

外文期刊名:PLANT PHENOMICS

收录:;EI(收录号:20240815618232);Scopus(收录号:2-s2.0-85185542839);WOS:【SCI-EXPANDED(收录号:WOS:001165159200001)】;

基金:Funding: This research was funded by the China National Key Research and Development Program (grant nos. 2023YFE0105100-3, 2022YFF1302100, and 2017YFD0600404) .

语种:英文

外文关键词:Clustering algorithms - Ecosystems - Laser applications - Mean square error - Optical radar - Plant shutdowns - Reforestation - Surveying instruments

摘要:Identifying the spatiotemporal distributions and phenotypic characteristics of understory saplings is beneficial in exploring the internal mechanisms of plant regeneration and providing technical assistances for continues cover forest management. However, it is challenging to detect the understory saplings using 2-dimensional (2D) spectral information produced by conventional optical remotely sensed data. This study proposed an automatic method to detect the regenerated understory saplings based on the 3D structural information from aerial laser scanning (ALS) data. By delineating individual tree crown using the improved spectral clustering algorithm, we successfully removed the overstory canopy and associated trunk points. Then, individual understory saplings were segmented using an adaptive-mean-shift-based clustering algorithm. This method was tested in an experimental forest farm of North China. Our results showed that the detection rates of understory saplings ranged from 94.41% to 152.78%, and the matching rates increased from 62.59% to 95.65% as canopy closure went down. The ALS-based sapling heights well captured the variations of field measurements [R-2 = 0.71, N = 3,241, root mean square error (RMSE) = 0.26 m, P < 0.01] and terrestrial laser scanning (TLS)-based measurements (R-2 = 0.78, N =443, RMSE = 0.23 m, P < 0.01). The ALS-based sapling crown width was comparable with TLS-based measurements (R-2 = 0.64, N = 443, RMSE = 0.24 m). This study provides a solution for the quantification of understory saplings, which can be used to improve forest ecosystem resilence through regulating the dynamics of forest gaps to better utilize light resources.

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