Monitoring of wet season rice crop at state and national level in India using multidate synthetic aperture radar data

Manab Chakraborty; Chakrapani Patnaik; Sushma Panigrahy; Jai Singh Parihar

doi:10.1117/12.693900

9 December 2006 Monitoring of wet season rice crop at state and national level in India using multidate synthetic aperture radar data

Manab Chakraborty, Chakrapani Patnaik, Sushma Panigrahy, Jai Singh Parihar

Author Affiliations +

Proceedings Volume 6411, Agriculture and Hydrology Applications of Remote Sensing; 641103 (2006) https://doi.org/10.1117/12.693900
Event: SPIE Asia-Pacific Remote Sensing, 2006, Goa, India

Abstract

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.

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Manab Chakraborty, Chakrapani Patnaik, Sushma Panigrahy, and Jai Singh Parihar "Monitoring of wet season rice crop at state and national level in India using multidate synthetic aperture radar data", Proc. SPIE 6411, Agriculture and Hydrology Applications of Remote Sensing, 641103 (9 December 2006); https://doi.org/10.1117/12.693900

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