融合哨兵2号时序特征与连续变化检测分类算法的优势树种识别

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关键词：优势树种识别；GEE；时序轨迹特征；归一化退化指数；CCDC算法；时间谐波分析中图分类号：S771.8 文献标识码：A DOI： 10.7525/j.issn.1006-8023.2025.03.00

Abstract：Theidentificationof dominant tree species isanimportant partofforestry resource surveys.Improving the accuracy of dominant tree species identification has significant practical implications for conducting forest resource surveys andrelated research.Using the Google Earth Engine（GEE）cloud platform，we obtained Sentinel-2 time series images forthe Huodong mining areafrom January to December 2O23.Theannual growth trajectory featuresof dominant tree species wereconstructed basedonthe CCDC algorithmand the NDFIindex.Adominant tree species hierarchical identification method combining "trajectory features + spectral features + texture features" of long-time series remote sensing images was proposed. A control group of "spectral features + texture features"was setup，and hierarchical classification andrandom forest clasificationalgorithms were used to identify7dominant treespecies （Pinus tabuliformis，Quercus wutaishansea，Betulaplayphylla，Lrixprincipis-rupprechtii，Platycladusorientalis，Populus davidiana，andpoplars spp.）inthe Huodong mining area.Theresultsshowed that：1）The NDFIindex can efectively distinguish between deciduous forests and evergreen forests；2）The dominant tree species identification based on "trajectory features + spectral features + texture features" performed well，with an overallclassification accuracy of 79.6%and a Kappa coeffcient of 0.742 in the study area，which was 7. 3 % higher than the control group.

Keywords：Dominant tree species identification；GEE；temporal trajectory features；normalized disturbance index; CCDC algorithm；time series harmonic analysis

0 引言

树种信息在森林资源动态监测、生物多样性评估以及森林生物量和碳储量估算中发挥着至关重要的作用[1]。（剩余18371字）