Ranjan, RajeevHegde, Arjun Shreepad2022-10-092022-10-092022-08https://krishikosh.egranth.ac.in/handle/1/5810188706Timely and accurate crop mapping plays an important role in food security, political, economic and environmental proposition. Crop maps, in particular, provide baseline information for efficient resource management and monitoring of agricultural production. 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. The number of crops grown by a farmer on the same field in an agricultural year constitutes the cropping intensity. It provides a measure of cropland usage with significant implications for agricultural intensification and bridging the food production gap. It estimates the intensification of production from the same piece of land. With these perspectives, a study has been conducted on crop classification and cropping intensity estimation using high-resolution multispectral satellite imageries in Udham Singh Nagar district of Uttarakhand. For this study high resolution, multispectral data of sentinel-2 satellite released by the European Space Agency (ESA) has been used. Cloud-free image of October 13, 2021, December 7, 2021 and March 6, 2022, has been acquired through the official website of the European Space Agency, Copernicus open access hub (https://scihub.copernicus.eu/) for more accurate differentiation of the feature classes. Ground truth points have been collected manually by using an android app named ‘Mapmarker’ and also by means of Google Earth. Further, pre-processing of satellite imageries like resampling, mosaicking and sub-setting are done using Sentinel Application Platform (SNAP) software. Then ENVI 4.7 software is used for crop classification and acreage estimation. The entire Udham Singh Nagar district has been classified based on crop seasons with the help of three different images for different major crop differentiation based on their respective maximum vegetative stage. Rice and Sugarcane are classified with help of the October 13, 2021 image with respective areas of 108884 ha and 11479 ha. The pea crop is classified from December 7, 2021 image and the pea crop area was estimated as 6227 ha. Using March 6, 2022, Sentinal-2 image, the other two major crops (wheat and mustard) are classified. Wheat crop area is estimated as 105334 ha whereas mustard crop occupied 2018 ha area according to estimation. A comparative study was done between three different classifiers namely, Artificial Neural Network (ANN), Maximum Likelihood (MXL) and Minimum distance to mean (Md) which yielded better results in the case of ANN with an R2 value of 0.999 and % RMSE of 3.20. The area occupied by major crops (rice, sugarcane, wheat, pea and mustard) is estimated in their respective seasons by taking their maximum vegetative stage into account. The estimated area of each major crop is further utilized to calculate three indices namely, Multiple Cropping Index (MCI), Area Diversity Index (ADI) and Cultivated Land Utilization Index (CLUI) which measures the cropping intensity as well as efficiency of the cropping system followed in the study area. High cropping intensity with an MCI value of 174.4%, Medium ADI of 2.4 and High CLUI of 0.7 is reported in the study area. Based on the calculated value of MCI, ADI and CLUI a recommendation was given to go for diversification with short-duration crops.EnglishThesis