Crop Classification and Crop Acreage Estimation Using Geospatial Technology in the Upper Gangetic Plains of Uttarakhand, India

Abstract

Timely and accurate crop mapping plays an important role in food security, economic and environmental policies. Crop maps are also utilized for agro-environmental assessments and crop water usage monitoring. As a result, accurate and timely crop classification is essential for agricultural management and monitoring. Because it provides periodic large-scale observations of ground objects, satellite remote sensing has been regarded as an advanced tool to characterize crop types and their distributions on a regional scale. High-resolution, multispectral images of October 13, 2021, December 7, 2021 and March 6, 2022 of sentinel-2 satellite released by the European Space Agency (ESA) have been used for classification. Ground truth points have been collected manually with the android app ‘Mapmarker’ and Google Earth. Further, pre-processing of satellite imageries such as resampling, mosaicking and sub-setting have been done with the Sentinel Application Platform (SNAP) software. Crop classification and acreage estimation was conducted using Maximum Likelihood approach. It is the first time an attempt was made to estimate cropping intensity using geospatial technology in the upper Gangetic plains of Uttarakhand state. Rice and sugarcane areas of 108,884 ha and 11,479 ha, respectively, were estimated from the October 13, 2021 image. Pea crop area was estimated as 6,227 ha from December 7, 2021 image. Using March 6, 2022 image, wheat and mustard crop areas were estimated as 105,334 ha and 2,018 ha, respectively.