Deriving cropping system performance indices using remote sensing data and GIS

The cropping system approach is a holistic management of variant and invariant resources to optimize the food production. Various indices are used to assess and evaluate the efficiency and sustainability of the systems. These indices are generally computed from the data collected by traditional survey methods that are time consuming and non-spatial. An attempt has been made to derive such indices using satellite remote sensing data for the state of West Bengal, India. Three indices-Multiple Cropping Index (MCI), Area Diversity Index (ADI) and Cultivated Land Utilization Index (CLUI)-were attempted. Multi-date, multisensor data from Indian Remote Sensing Satellite (IRS) and Radarsat Synthetic Aperture Radar (SAR) were used to derive cropping pattern, crop rotation, and crop calendar. Crop type, acreage, rotation and crop duration were used as inputs to compute the indices at district and state level. The indices were categorized as high, medium and low to evaluate the performance of each of the 16 districts. The average MCI of the state derived was 140. At district level it varied from 104 to 177. The average ADI of state was 2.5 and varied from 1.5 to 5.0.