Remote sensing based season calendar for Indian districts using MODIS data

Seasonal characteristics and crop growth information is of great utility for crop management. The primary occupation in India being agriculture, it is important to devise quick and reliable methods that will help in making decisions affecting agricultural practices at a macro level more efficiently. In this paper, the authors have devised an algorithm to derive a seasonal calendar from the time series data of a moderate resolution satellite, MODIS which is one step short of producing a crop calendar. The method proposed involves filtering time series data using Local Maximum Fitting, finding maximum and minimum points on the time series profile, calculating phenological parameters namely start of season, mid of season, end of season and seasonal amplitude and finally clustering these phenological parameters to obtain a cluster center which is representative of a particular season/cropping practice. The initial results are promising as they are similar to the information available in the form of handouts of the regions under study. A full scale validation involving field visits and comparison with statistical data from government sources will prove the utility of this product. Nevertheless, this work demonstrates the utility of time series MODIS data for obtaining phenological parameters.