The Applicability Of The Regional Vegetation Coverage Study Vegetation Index Calculation

The vegetation coverage is an important quantitative index of the ground vegetation. Meanwhile it is an important one factor in the research of soil erosion. The vegetation coverage is mainly through remote sensing vegetation index to derive. Research the atmosphere correction method of vegetation index deriving, analysis the suitability of vegetation index calculation surface layer of different vegetation coverage area, has important significance for land/vegetation coverage change research and controlling soil erosion.This paper selected Jiangxi red soil region as a case study. Landsat TM5was selected and processed by two methods of atmosphere correction:6s model and FLAASH model. Discuss the appropriate atmosphere correction method for vegetation indices deriving. A kinds of green vegetation indices and yellow vegetation indices are derived which based on the winter and summer TM images. Doing correlation analyses between the vegetation indices and the observed sample data in field, then selected the optimal green vegetation index and the optimal yellow vegetation index. Analysis the method of applicability for vegetation coverage calculation by area vegetation index, made the following results:(1)6S model is the appropriate atmosphere correction method for vegetation index deriving.TM images of Jiangxi (winter, summer) were processed by radiation calibration and atmosphere correction which used6S model and the FLAASH model. Analyzes the two feature by histogram contrast、spectrum curve contrast and vegetation index calculation accuracy contrast. The results show6S model is suitable method for vegetation index derived.(2) Deriving vegetation indices based on Landsat TM imagesThrough calculating the soil line equation of Jiangxi red soil region, have derived the green index include NDVI, MSAVI and PVI which based on summer image of the study area.The yellow index are NDTI、NDSVI and SACRI which based on winter image. Analyzes the maximum、minimum and mean value of all kinds of vegetation indices, the results show the characteristic value of NDVI is the greatest, second largest PVI, MSAVI minimum. All kinds of yellow vegetation index of the maximum and minimum values are respectively for1and1, the average of the NDTI is biggest, followed by NDSVI, SACRI minimum.(3) Analyze applicability of regional vegetation coverage inversion method by vegetation index.Analyze the correlation between the green index and the Joe, shrub, grass each layer of observed vegetation communities coverage, and the correlation between yellow index and the observed sample data of the dead leave in field, the results show that the perpendicular vegetation index PVI is the optimal of green index and the normalized difference senescent vegetation index NDSVI is the optimal yellow index.Compare Jiangxi Red hilly area and the Northern Shaanxi Loess area of green vegetation and yellow index. It shows that PVI eliminate the influence of soil background which is the optimal vegetation index for different soil type areas of vegetation coverage inversion; Yellow index has regional differences, normalized difference tillage index is the optimal yellow index in Northern Shaanxi Loess area, normalized difference senescent vegetation index NDSVI is the optimal yellow index in southern red hilly area.