Determining Wheat Crop Acreage Based on Remote Sensing and GIS Technique in Jabalpur, India

Authors

  • 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.

DOI:

https://doi.org/10.9734/bpi/ctas/v3/2662E

Keywords:

Sentinel-2, unsupervised classification, spectral bands, crop

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. The study clearly demonstrated that district-level wheat acreage could be reliably estimated using multi-date vegetative growth stage Sentinel data and digital unsupervised classification.

Published

2021-10-30

How to Cite

Umakant Rawat, Ankit Yadav, P. S. Pawar, Aniket Rajput, Devendra Vasht, & S. Nema. (2021). Determining Wheat Crop Acreage Based on Remote Sensing and GIS Technique in Jabalpur, India. Current Topics in Agricultural Sciences Vol. 3, 63–69. https://doi.org/10.9734/bpi/ctas/v3/2662E