Hyperspectral vegetation indices, NDVI,MTVI2 and MCARI/OSAV, are used as input variables in this model for the purpose of enhancing weak information of crop heavy metal pollution stress.

Application of five atmospheric correction models for Landsat TM data in vegetation remote sensing.;

Analysis for vegetation index in spring utilizing satellite remote sensing date in shandong province;

Study on plant extraction with Beijing-1 small satellite using vegetation index;

Study on Desertification Monitoring Model for Grassland in Xilinguole based on MODIS Vegetation Index;

Relationship Between Urban Thermal Distribution and NDVI of Shanghai City;

An analysis on eco-environmental effect of urban land use based on remote sensing images:a case study of urban thermal environment and NDVI;

Study on the Model of Crop Yield Estimating Based on NDVI and Temperature;

Normalized difference vegetation index (NDVI) is calculated from reflectance measurements in the red-NIR ofthe spectrum: ND VI=(NIR-R)/(NIR+R).

On the basis of research on sample strips and typical area, the factors of precipitation, temperature and types of land vegetation cover which effect the changes of the normalized difference vegetation index (NDVI) were analyzed by correlation analysis method.