Downloading: Cropping System Analysis Using Geospatial Approach: A Case Study of Sirsa District in Haryana, India
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR) | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

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Cropping System Analysis Using Geospatial Approach: A Case Study of Sirsa District in Haryana, India

Satyawan, Manoj Yadav, R S Hooda

Abstract: Agriculture plays a crucial role in the economy of developing countries, and provides the main source of food, income and employment to their rural populations. With increasing population pressure throughout the nation and the concomitant need for increased agricultural production. A cropping system is defined as the cropping pattern and its management to derive benefits from a given resource base under a specific environmental condition. Crop rotation means the successive cultivation of different crops in a specified order on the same fields, in contrast to a one-crop system or to haphazard crop successions. The paper describes methodology and results of cropping system analysis for Sirsa district of Haryana, India climatologically characterized by hot summer, cold winter and dry air except during rainy season. Multi-date & multi-season IRS LISS-III digital satellite data of 2007-2008 was geo-referenced with the already geo-referenced master images by collecting GCPs using second polynomial order and Nearest Neighborhood resembling approach. District boundary was overplayed on the image and all the data elements (pixels) within this were extracted for further analysis. Multi-layer stacks were prepared for Monsoon, Winter and Summer seasons using multi-date images of each season. Multiphase unsupervised classification approach Iterative Self-organizing Data Analysis Technique (ISODATA) Clustering classifier was used and class of interest were identified using ground truth information collected using hand held GPS. Mask of mixed classes was prepared and image under the mask was reclassified. The reclassification process was continued till the classes of interest were segregated. To improve the accuracy Normalized Difference Vegetation Index (NDVI) of each date and mask of non-agricultural classes such as urban, forest, water bodies and wastelands was prepared and used at the time of classification. The Monsoon, Winter and Summer seasons cropping pattern maps and statistics were generated using classified images and applying logical combinations. During Monsoon season cotton (Gossypium) is the major crop which occupies 179.29 (000 ha.) areas and in the Winter season wheat is major crop occupying 276.9 (000 ha.) areas. In the summer season most of the area is lying vacant as fallow and major crops are mung, fodder, vegetables etc. Horticulture fruit crops are long duration crops and available in all three cropping seasons. Some minor crops are unable to separate out due to less area scattered distribution and hence here termed as Other Crops. Paddy-Wheat-Other Crops, Cotton (Gossypium) -Wheat-Mung/Fallow/Other Crops are the major crop rotations identified in the district. Multi-date and multi-season IRS LISS-III data is found to be useful for the cropping system analysis at the state level.

Keywords: Cropping system, Remote Sensing, IRS-P6 satellite, LISS-III, Winter, Monsoon & Summer