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通过地面光谱试验,验证了植被指数和线性光谱分解方法提取石漠化遥感评价因子的有效性,并基于光谱吸收特征发展了石漠化综合指数(karst rocky desertification synthesis indices,KRDSI)。结果表明,植被指数能够比较有效地提取绿色植被盖度,土壤背景对基于植被指数的喀斯特地区绿色植被盖度提取影响很小;植被指数和线性光谱分解技术均不能有效提取表征石漠化信息的非绿色植被覆盖信息,而KRDSI能够直接提取石漠化遥感评价因子。研究表明,利用Hyperion高光谱成像数据,基于植被指数和KRDSI能够比较有效地直接提取石漠化遥感评价因子。
The ground-based spectral test validated the effectiveness of vegetation index and linear spectral decomposition method for extracting remote sensing evaluation factors of rocky desertification and developed karst rocky desertification synthesis indices (KRDSI) based on spectral absorption characteristics. The results showed that vegetation index could extract green cover more effectively, and soil background had little effect on the extraction of green cover in karst area based on vegetation index. Both vegetation index and linear spectral decomposition technology could not effectively extract the information that characterized rock desertification Non-green vegetation cover information, and KRDSI can directly extract remote sensing evaluation factors for rocky desertification. The results show that remote sensing evaluation factors of rocky desertification can be directly and efficiently extracted by Hyperion hyperspectral imaging data based on vegetation index and KRDSI.