Study on operational applications in crop growth and drought monitoring using multiple satellite data: Case study in Xinjiang, China

The high spatial and high temporal satellite data is necessary in the operational agricultural applications of remote sensing. But till now the advantages of high spatial and high temporal resolution still can not be realized in single sensor. The PSP method (Patch Spectral Purification Method) is capable of retrieving field patch average information from high temporal but moderate spatial resolution satellite data, which meets the requirement of high spatial and high temporal resolution information in the real monitoring applications. In this paper a PSP-based methodology is proposed to retrieve the high spatial and high temporal resolution information for the growth and drought monitoring using multiple satellite data. An application demonstration was made in Xinjiang, China to monitor the cotton growth and drought with MODIS and Landsat/TM data. And the processing software-AgRsis (Agricultural Remote Sensing Inversion System) was realized to generate the daily crop parameters standard maps(e.g. NDVI, TVDI) for the crop growth and drought monitoring.