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With the development of vegetation indices, the reflection capability of vegetation indices to the state of vegetation has been improved in various degrees. Especially, the vegetation index of Terra/MODIS-EVI is believed to have the highest sensitivity to the seasonality of vegetation. This study compares the reflection susceptibility of three vegetation indices (NOAA/AVHRR-NDVI, Terra/MODIS-NDVI and Terra/MODIS-EVI) to the seasonal variations of vegetation in the mid-south of Yunnan Province of China. It has been found that Terra/MODIS-EVI does best in the elimination of external disturbance. Firstly, it obviously improves the linear relationship with vegetation cover degree, especially in the high vegetation coverage area. Secondly, it avoids the emergence of vegetation index saturation. Thirdly, it reduces the environmental influence including both effects of atmosphere and soil. So it is believed that the Terra/MODIS-EVI can offer excellent tool for quantitative research of remote sensing, and has realized to be oriented by data with high quality.
With the development of vegetation indices, the reflection capability of vegetation indices to the state of vegetation has been improved in various degrees. Particularly, the vegetation index of Terra / MODIS-EVI is believed to have the highest sensitivity to the seasonality of vegetation. study supported the reflection susceptibility of three vegetation indices (NOAA / AVHRR-NDVI, Terra / MODIS-NDVI and Terra / MODIS-EVI) to the seasonal variations of vegetation in the mid- south of Yunnan Province of China. Firstly, it obviously improves the linear relationship with vegetation cover degree, especially in the high vegetation coverage area. Secondly, it avoids the emergence of vegetation index saturation. Thirdly, it reduces the environmental influence including both effects of atmosphere and soil. So it is believed that the Terra / MODIS-EVI can offer excellent tool for quantitative research of remote sensing, and has realized to be oriented by data with high quality.