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煤炭开采扰动下草地和灌木生长状态的差异化分析

Differentiation Analysis of Grassland and Shrub Growth Status Under Disturbance of Coal Mining
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摘要 针对开采沉陷区植被生长状况精细化研究较少的现状,基于无人机影像数据提取13种可见光植被指数,采用相关性分析和回归趋势分析法探究沉陷盆地内植被生长状态变化规律。相关性分析得到:草地的EXB(excess blue index)、NGRDI(normalized green-red difference index)等指数变化值与开采导致的变形具有强相关性;灌木RGRI(red green ratio index)指数、EXR(excess red index)指数、MGRVI(modify green-red vegetation index)等指数变化值与开采导致的变形具有强相关性。回归模型结果表明,煤矿开采对沉陷影响区的草地和灌木生长状况具有一定的负面影响,地表产生下沉1%时,草地的生长状态变差最为明显,而灌木的生长状态抵抗变形能力较强,随着下沉量增大才有所变差,下沉量为92%时,灌木变差情况最为明显。 The current status of fine-grained research on vegetation growth in subsidence mining areas is limited.In this study,we utilized unmanned aerial vehicle(UAV)image to extract 13 visible light vegetation indices and employed correlation analysis and regression trend analysis to explore the patterns of vegetation growth changes in the subsidence basin.The correlation analysis revealed strong correlations between the variations of indices such as excess blue index(EXB),normalized green-red difference index(NGRDI),and deformations caused by mining activities.Similarly,variations in indices like red green ratio index(RGRI),excess red index(EXR),modify green-red vegetation index(MGRVI),and deformations were found to be strongly correlated for shrubs.The results of the regression models indicated that coal mining negatively affected the growth conditions of grasslands and shrubs in the subsidence-affected areas.The growth status of grasslands deteriorated most significantly when the surface subsidence reached 1%.On the other hand,the growth status of shrubs showed a stronger resistance to deformations,with noticeable deterioration occurring only with an increase in subsidence of up to 92%.
作者 杨帆 王晨旭 李亮 严怀民 万梦媛 YANG Fan;WANG Chenxu;LI Liang;YAN Huaimin;WAN Mengyuan(Zaoquan Coal Mine,Ningxia Coal Industry Company,National Energy Group,Lingwu,Ningxia 750408,China;School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China)
出处 《遥感信息》 CSCD 北大核心 2024年第5期54-61,共8页 Remote Sensing Information
基金 国家自然科学基金(U22A20598)。
关键词 无人机影像 可见光植被指数 采矿扰动 相关分析法 UAV image visible light vegetation index mining disturbance correlation analysis
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