融合哨兵2號(hào)時(shí)序特征與連續(xù)變化檢測(cè)分類算法的優(yōu)勢(shì)樹種識(shí)別

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關(guān)鍵詞：優(yōu)勢(shì)樹種識(shí)別；GEE；時(shí)序軌跡特征；歸一化退化指數(shù)；CCDC算法；時(shí)間諧波分析中圖分類號(hào)：S771.8 文獻(xiàn)標(biāo)識(shí)碼：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

樹種信息在森林資源動(dòng)態(tài)監(jiān)測(cè)、生物多樣性評(píng)估以及森林生物量和碳儲(chǔ)量估算中發(fā)揮著至關(guān)重要的作用[1]。（剩余18371字）