Abstract
Crop rotation is the sequential growth of crops in a year. The feasibility of deriving this information from multi-temporal satellite digital data acquired during different crop seasons in a year is reported herein. Red and NIR bands of the Indian Remote Sensing Satellite (IRS) LISS-I multidate data acquired in different crop seasons resulted in more than 95 percent accuracy of training site pixels. Similar result was also obtained using principal components of multidate data. Inclusion of data acquired during the transitional phase of crop seasons was found to improve classification accuracy. Four-date data acquired between October and March were found to be optimum for deriving such information for West Bengal. The results showed that a rice based single cropping system is the dominant rotation class of the district, while in the irrigation command area of Damodar river, a double cropping system of rice followed by rice and rice followed by potato were the major rotation classes.
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