Application of Normalized Difference Vegetation Index (NDVI) for the Detection of Extreme Precipitation Change

Remote sensing has frequently been employed to monitor extreme climatic events, especially droughts, by identifying the anomalies of vegetation activity from regional global scale. However, limited research addressed performance remote on detecting precipitation events. By using Middle and Lower Reaches Yangtze River (MLR-YR) in China as an example, this paper examines application satellite-derived normalized difference index (NDVI) for change events 1982 2012. The performances three NDVI-based indices, including minimum, mean, maximum NDVIs, were examined capture sensibility changes results show not only common enhanced trends, but also obvious spatial discrepancies between intensity frequency MLR-YR. As its terrestrial vegetation, coincided with that activity, which was represented minimum NDVI. In addition, similar patterns found standard deviation NDVI trend intensity. Furthermore, correlation coefficients relatively greater than Our support hypothesis is more suited response MLR-YR region, comparison other two indices.