Remote Sensing and GIS Based Crop Acreage Estimation of the Rabi Season Growing Crop of the Middle Gujarat (India)

Abstract

Accurate and precise information about crop type, crop stage, and crop acreage is essential for sustainable utilization of available water resources. The present study is concerned with the estimation of Rabi season growing crops in the Panchmahal district of Gujarat state, India. In these study generation of spectral profiles and crop acreage estimation, Sentinel-2 satellite images were classified using unsupervised classification with ISODATA clustering classification techniques. The satellite image of the study area was classified into 52 classes and overlaid with a ground truth point shape file on the classified image. Total twelve date NDVI based signature derived from sentinel – 2 data during rabi season 2020 - 2021. NDVI based data set is used to classify the study area's major crops, which are maize, wheat, castor, chilli, cotton, pigeon pea, sorghum, and tobacco. The total research area's growing crops was estimated as 34472.59 ha, 16517.09 ha, 2186.92 ha, 250.59 ha, 8005.56 ha, 1130.93 ha, 1719.38 ha and 1468.52 ha for maize, wheat, castor, chilli, cotton, pigeon pea, sorghum and tobacco, respectively. The overall accuracy and kappa coefficient for crop acreage estimation were calculated to be 90.71% and 0.78%, respectively. The resulted acreage estimation will help to understand the cropping pattern and their interaction with spatial and temporal variability for present and future estimation of crop water requirement and proper resource availability in this selected region.