The repetitive cultivation of an ordered succession of crops (or crop and fallow) on the same land defined as crop
rotation has a significant role on sustainability of agricultural practice. This paper highlights the methodology used to
map seasonal cropping pattern and crop rotation of West Bengal state in India. Multi-date, remote sensing data of IRS
WiFS and Radarsat SAR were used to map seasonal cropping patterns, which were combined to derive the crop rotation
map. Three distinct crop-growing seasons could be identified. The main one coinciding with monsoon from June-
October, followed by winter crop season from November- February and the summer one March-June. It was feasible to
classify seven major crops using the SAR and WiFS data sets. Rice is the dominant crop in wet season occupying more
than 75 per cent of net sown area. Mustard, potato, wheat, gram, rice are the major dry season crops. Rice-rice, ricepotato,
rice-wheat, rice-mustard, rice-gram, and jute-rice were the major two crop rotations. Rice-fallow was the
dominant practice accounting for 55 per cent of area.
Rice crop grown during the monsoon (wet) season is the most important food grain in India. The crop is grown under
varied cultural and management practices. The present paper highlights the results of rice monitoring being carried out
for the past five years (2001-02 to 2005-06) using multi-date RADARSAT ScanSAR Narrow-B data. 30 ScanSAR
scenes covering thirteen states account for 95 percent of national crop area. 90 scenes are analysed to assess the national
wet season rice crop. A stratified sampling plan is used to analyse 5*5 km segments accounting for 15 per cent of the
crop area in each of the study states. A decision-rule classifier has been developed based on a Radiative Transfer (RT)
model developed and calibrated using large number of rice sites in India and controlled field experiments. This
procedure accounts for change in backscatter as a result of transplanting of rice and crop growth in multi-date data to
classify rice areas. Results indicate more than 93 per cent accuracy of area estimation at state level and 97 per cent at
national level. It is feasible to assess deviations in crop planting operation (late or early) for a given area.
Conference Committee Involvement (1)
Agriculture and Hydrology Applications of Remote Sensing
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.