Study on the utility of IRS-P6 AWiFS SWIR band for crop discrimination and classification
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Photonirvachak
J. Indian Soc. Remote Sens. (June 2009) 37:325–333
SHORT NOTE
Study on the Utility of IRS-P6 AWiFS SWIR Band for Crop Discrimination and Classification Rabindra K. Panigrahy . S. S. Ray . S. Panigrahy
Received: 31 July 2006 / Accepted : 28 February 2009
Keywords AWiFS . SWIR band . Crop discrimination . Classification . Three-band ratio index
Abstract This present study was conducted to find out the usefulness of SWIR (Short Wave Infra Red) band data in AWiFS (Advanced Wide Field Sensor) sensor of Resourcesat 1, for the discrimination of different Rabi season crops (rabi rice, groundnut and vegetables) and other vegetations of the undivided Cuttack district of Orissa state. Four dates multispectral AWiFS data during the period from 10 December 2003 to 2 May 2004 were used. The analysis was carried out using various multivariate statistics and classification approaches. Principal Component Analysis (PCA) and separability mea-
R.K. Panigrahy1 . S.S. Ray ( ) . S. Panigrahy Agriculture, Forestry & Environment Group, RESA, Space Applications Centre, ISRO, Ahmedabad – 380 015, India 1 C-DAC, Pune – 411 007, India
email : [email protected]
sures were used for selection of best bands for crop discrimination. The analysis showed that, for discrimination of the crops in the study area, NIR was found to be the best band, followed by SWIR and Red. The results of the supervised MXL classification showed that inclusion of SWIR band increased the overall accuracy and kappa coefficient. The ‘Three Band Ratio’ index, which incorporated Red, NIR and SWIR bands, showed improved discrimination in the multi-date dataset classification, compared to other SWIR based indices.
Introduction Crop discrimination and classification is the foremost step in many agricultural applications such as crop acreage, yield and production estimation, cropping system analysis, crop stress physiology and precision agriculture. However, crop classification using remote sensing data has been a constant challenge, especially in the eastern Indian regions
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because of the small land holdings and the highly diversified cropping pattern. Czapleski (1992) has observed that estimates achieved by the remote sensing classification procedure are sensitive to various crops as well as sensor-related parameters. While reviewing the approaches of crop discrimination, Dadhwal et al. (2002) have high-lighted the need for a high spatial resolution multi-spectral sensor with large area coverage, keeping in view the limitations of WiFS (Wide Field Sensor) onboard IRS 1C/1D satellites. With 56 m spatial resolution, 10 bit radiometric resolution and 5 days revisit period, the AWiFS (Advanced Wide Field Sensor) onboard Resources at 1 (IRS-P6) provides a huge potential for agricultural applications. AWiFS operates in four multi-spectral bands such as green (0.52–0.59 m), red (0.62–0.68 m), near infrared (0.77–0.86 m) and short wave infrared (1.55–1.70 m). The SWIR (short wave infrared) band is particularly significant because of its strong re
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