An Analysis of crop rotation practice by the farmers of North-western Haryana: Using geospatial technology
DOI:
https://doi.org/10.36676/urr.v11.i4.1310Keywords:
supervised classification, crop rotation transpose, Remote sensing, GIS, Spatio-temporal analysisAbstract
Crop rotation studies that include comprehensive temporal and spatial data are essential for sustainable agricultural management, crop monitoring, and addressing food security concerns. Insufficient agricultural information is a significant barrier to effective policy-making and research aimed at ensuring food security. A study was carried out in northwestern Haryana to map crop rotation using satellite-based remote sensing data, combined with other spatial and non-spatial collateral data. The main data sources utilized were Landsat-5 and Sentinel-2, which were analyzed using digital image processing techniques in ERDAS Imagine and ArcGIS software. An interactive supervised classification method was applied to evaluate the data. Crop rotation maps were created for the periods 1990-1991 and 2021-2022. The findings indicated that the cotton-mustard cropping area comprised 19.85% of the total geographical area in 1990-1991, while the rice-wheat cropping area accounted for 31.46% in 2021-2022. This indicates that cotton-mustard was the predominant crop rotation in 1990-1991, whereas rice-wheat became the primary
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