Detecting Forest Degradation in the Three-North Forest Shelterbelt in China from Multi-Scale Satellite Images

Detecting forest degradation from satellite observation data is of great significance in revealing the process decreasing quality and giving a better understanding regional or global carbon emissions their feedbacks with climate changes. In this paper, quick applicable approach was developed for monitoring Three-North Forest Shelterbelt China multi-scale remote sensing data. Firstly, Normalized Difference Vegetation Index (NDVI), Enhanced (EVI), Ratio (RVI), Leaf Area (LAI), Fraction Photosynthetically Active Radiation (FPAR) Net Primary Production (NPP) were selected as indicators to describe degradation. Then maps obtained by adopting new classification method using time series MODerate Resolution Imaging Spectroradiometer (MODIS) Landsat Thematic Mapper Plus (ETM+) images, validated ground survey At last, criteria discussed, uncertainly analyzed. Results paper indicated that have potential detecting