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根据结构化植被因子指数的概念,以TM影像为信息源,探讨了利用遥感技术提取陕北黄土区结构化植被因子指数(Cs)的途径与方法.结果表明:在陕北黄土区,Cs能更好地描述植被群落的水土保持效益,其与绿度植被指数(归一化植被指数NDVI、修正土壤调整植被指数MSAVI)和黄度植被指数(归一化差异衰败指数NDSVI、归一化耕作指数NDTI)等单一的遥感植被指数虽然均存在良好的相关关系,但用绿度与黄度植被指数相结合可综合反映植被的水土保持功能,能较好地克服单一指数在描述植被控制水土流失中的不足;MSAVI、NDTI分别是基于遥感影像提取Cs较为理想的绿度和黄度植被指数;根据群落结构化植被因子指数与遥感植被指数的关系推算区域尺度上的结构化植被因子指数是可行的,但由于不同地区植物物候期的差异,要使该方法在其他地区适用,仍需开展相应的率定和验证工作.
According to the concept of structured vegetation factor index, taking TM image as the information source, this paper discussed the ways and methods of extracting structured vegetation factor index (Cs) by using remote sensing technology in the loess region of northern Shaanxi.The results showed that Cs Better describe the benefits of soil and water conservation of vegetation communities, which are closely correlated with the vegetation indices of greenness index (NDVI, MSAVI) and yellowness index (NDV NDSVI, normalized tillage Index NDTI) and other single remote sensing vegetation index although there is a good correlation, but with the greenness and the yellowness index can be combined to comprehensively reflect the function of vegetation and water and soil conservation, can better overcome the single index in describing vegetation erosion and soil erosion . MSAVI and NDTI are the ideal vegetation index of greenness and yellowness respectively based on remote sensing image extraction Cs. Based on the relationship between the index of community structure vegetation index and remote sensing vegetation index, it is feasible to calculate the index of structured vegetation on regional scale However, due to the differences in plant phenology in different regions, the corresponding calibration and validation work still needs to be carried out to make the method suitable for other regions.