复合植被指数在稀疏高寒草原植被盖度遥感反演中的应用

摘要

Based on the Landsat 8 remote sensing image data,a transect of alpine steppe from Shigatse City through Nanmulin County to Shenzha County in Tibet was selected as the research area.Four commonly used vegetation indices were used in this study,including the normalised difference vegetation index (NDVI),soiladjusted vegetation index (SAVI),modified soil-adjusted vegetation index (MSAVI),and transformational soil-adjusted vegetation index (TSAVI),which is sensitive to vegetation information with low coverage in semi-arid areas.Furthermore,the study improved the bare soil index (BI) and the shadow index (SI) using surface reflectance to construct the vegetation bare shadow index (VBSI) suitable for areas of low vegetation coverage.Then,based on the above vegetation indices,the quantitative inversion of vegetation coverage of the alpine steppe was conducted by the dimidiate pixel model.Finally,the inversion accuracy was analysed using the field vegetation coverage data by the grid method.The results showed that the inversion accuracy of VBSI (TSAVI) was the highest among the eight vegetation indices used,and the inversion accuracy was 85.66％.It was demonstrated that the dimidiate pixel model constructed by TSAVI based on the soil spectrum obtained by field collection has a certain practicality for the inversion of vegetation coverage of alpine steppe.The BI and SI of the improved FCD model can significantly reduce the influence of soil and shade on vegetation information.The constructed composite vegetation index is of great practical significance to extract the vegetation coverage information of sparse alpine steppe.%基于Landsat 8遥感影像数据,以西藏日喀则经南木林到申扎县的一条样带高寒草原作为研究对象,选择较为常用的归一化植被指数(normalized difference vegetation index,NDVI)、土壤调整植被指数(soil adjusted vegetation index,SAVI)、修改型土壤调整植被指数(modified soil adjusted vegetation index,MSAVI)以及对半干旱区低覆盖植被信息较为敏感的转换型土壤调整植被指数(transformational soil adjusted vegetation index,TSAVI),结合地表反射率改进运算的FCD模型(forest canopy density mapping model)裸土(bare soil index,BI)和阴影指数(shadow index,SI)构建适合低植被覆盖区域的复合植被指数(vegetation bare shadow index,VBSI);基于各植被指数构建像元二分模型,定量反演高寒草原植被盖度;并利用网格法实测的植被盖度分析反演精度.研究结果表明,8种植被指数所构建的像元二分模型对高寒草原植被盖度的反演精度以VBSI(TSAVI)最高,反演精度为85.66％;并证明了基于野外采集的土壤光谱曲线获取的TSAVI所构建的像元二分模型对高寒草原植被盖度信息的提取具有一定的实用性;改进运算的FCD模型裸土和阴影指数能较好地削弱土壤和阴影对植被信息的影响,所构建的复合植被指数对提取稀疏高寒草原植被盖度信息具有重要的实际意义.