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Spatial dynamics for relative contribution of cropping pattern analysis on environment by integrating remote sensing and GIS
Volume 8, Issue 1
, Winter 2014
, Page 1-17
PDF (967 K)
Document Type: Research Paper
Student, N. R. D. M. S., Kumaun University, S.S.J. Campus Almora, Uttrakhand, India.
Assistant Professor, Department of Remote Sensing, Banasthali University, Rajasthan, India.
Assistant Scientist, Haryana Space Applications Centre, Hisar (HARSAC), Haryana, India.
H.O.D., N. R. D. M. S., Kumaun University, S.S.J. Campus Almora, Uttrakhand, India.
Assistant Scientist, Haryana Space Applications Centre (HARSAC), Hisar, Haryana, India.
Chief Scientist, Haryana Space Applications Centre (HARSAC), Hisar, Haryana, India.
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.
Accuracy assessment; Cropping pattern; Crop rotation.
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