Wheat Crop Acreage Estimation Based on Remote Sensing and GIS in Jabalpur (Madhya Pradesh, India)
Umakant Rawat *
Department of Soil and Water Engineering, College of Agricultural Engineering, JNKVV, Jabalpur, India.
Ankit Yadav
Department of Soil and Water Engineering, College of Agricultural Engineering, JNKVV, Jabalpur, India.
P.S. Pawar
Department of Soil and Water Engineering, College of Agricultural Engineering, JNKVV, Jabalpur, India.
Aniket Rajput
Department of Soil and Water Engineering, College of Agricultural Engineering, JNKVV, Jabalpur, India.
Devendra Vasht
Department of Soil and Water Engineering, College of Agricultural Engineering, JNKVV, Jabalpur, India.
S. Nema
Department of Soil and Water Engineering, College of Agricultural Engineering, JNKVV, Jabalpur, India.
*Author to whom correspondence should be addressed.
Abstract
Mapping and classification crop by using satellite images is a challenging task that can minimize the complexities of field visits. The recently launched Sentinel-2 satellite has thirteen spectral bands, short revisit time and determination at three different resolutions (10 m, 20 m and 60 m), besides that, the free availability of the images makes it a good choice for vegetation mapping. This study aims to classify crop, using single date Sentinel-2 imagery within the Jabalpur, state of Madhya Pradesh, India. The classification was performed by using Unsupervised Classification. In this study, four spectral bands, i.e., Near Infrared, Red, Green, and Blue of Sentinel-2 were stacked for the classification. The results show that the area of wheat crop corresponds to 83.07%; Gram/ Pulses, 14.64%; and other crop, 2.28%. The overall accuracy and overall Kappa Statistics of the classification using Sentinel-2 imagery are 85.71% and 0.819%, respectively. Therefore, this study has found that Sentinel-2 presented great potential in the mapping of the agriculture areas of Jabalpur by remote sensing.
Keywords: Sentinel-2, unsupervised classification, spectral bands, crop