Spatial dynamics for relative contribution of cropping pattern analysis on environment by integrating remote sensing and GIS

Authors

  • J.S. Rawat H.O.D., N. R. D. M. S., Kumaun University, S.S.J. Campus Almora, Uttrakhand, India.
  • M. Yadav Assistant Scientist, Haryana Space Applications Centre, Hisar (HARSAC), Haryana, India.
  • M.P. Sharma Assistant Scientist, Haryana Space Applications Centre (HARSAC), Hisar, Haryana, India.
  • P. Bisht Student, N. R. D. M. S., Kumaun University, S.S.J. Campus Almora, Uttrakhand, India.
  • P. Kumar Assistant Professor, Department of Remote Sensing, Banasthali University, Rajasthan, India.
  • R.S. Hooda Chief Scientist, Haryana Space Applications Centre (HARSAC), Hisar, Haryana, India.
Abstract:

Agriculture resources reflected to be one of the most imperative renewable and dynamic natural resources. Agricultural sustainability has the premier priority in all countries, whether developed or developing. Cropping system analysis is indispensable for grinding the sustainability of agricultural science. Crop alternation is stated as growing one crop after another on the same piece of land in altered timings (seasons) without prejudicing the soil fertility. The study has been conducted for Fatehabad district of Haryana State of Indo-Gangetic plains in India. This paper generated cropping pattern and crop rotation maps of Fatehabad district. Multi-date IRS LISS-III digital data of different cropping seasons of 2007-08 have been used for this study. The present study relies on data from remote sensing combined with ground observations. Multi-date images of Rabi season images were geo-referenced using master images. Multi-date images of Kharif and single date image of summer seasons were geo-referenced with geo-referenced Rabi season image using image-to-image registrations and nearest neighborhood resampling method was applied. Multilayer stack were prepared for Kharif and Rabi cropping seasons. Stacked images of different seasons were classified using complete enumeration approach and unsupervised ISO-Data clustering classifier with district outside and non-agriculture mask based on some defined conditions such as the number of clusters, threshold, and number of iterations etc. A multiphased unsupervised ISODATA classification was used for seasonal cropping pattern mapping. The results showed that in the area, a monophonic crop pattern was found in summer and major part of the district is lying as fallow and major crops are fodder, dhaicha & sunflower, but in winter, areas under dissimilar crop pattern had changed melodramatically. Keywords: Accuracy assessment; Cropping pattern; Crop rotation.

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Journal title

volume 8  issue 1

pages  1- 17

publication date 2014-01-01

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