An advanced tool for real-time crop monitoring in China

This paper presents a series of methods that monitoring crop in China by remote sensing. First the paper describes the methodology used to integrate high resolution land cover data and 1km2-resolution SPOT-Vegetation 10-day images for the extraction of NDVI profiles. That can increase the information content of the time series of NDVI. It proved that information extracted this way is more close to crop behaviors than a simple mixed vegetation profile. Next for cloud masking, we use HANTS(harmonic analysis of time series)algorithm. This is because time series of NDVI data have period characteristic that describes the yearly cycle of the vegetation dynamics. HANTS can analyze the time signal for each individual pixel and use the series of harmonic sine and cosine waves to reconstructed waves fits into the total period. Results showed that cloud affected data are recognized and replaced successfully by reconstruction of seasonal NDVI profiles. The application and the result fit the objective of the crop monitoring system in china, which used along the cropping season to monitor crop growth and identify possible food shortages in real time.