Crop classification and cropping intensity estimation using geospatial technology in the upper Gangetic plains of Uttarakhand.

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. 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 Artificial Neural Network. 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 6227 ha from December 7, 2021 image. Using March 6, 2022 image, wheat and mustard crop areas were estimated as 105,334 ha and 2018 ha, respectively. The estimated area of each major crop was further utilized to calculate Multiple Cropping Index which was found to be 174.4 %.