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

Document Type: Research Paper

Authors

1 Student, N. R. D. M. S., Kumaun University, S.S.J. Campus Almora, Uttrakhand, India.

2 Assistant Professor, Department of Remote Sensing, Banasthali University, Rajasthan, India.

3 Assistant Scientist, Haryana Space Applications Centre, Hisar (HARSAC), Haryana, India.

4 H.O.D., N. R. D. M. S., Kumaun University, S.S.J. Campus Almora, Uttrakhand, India.

5 Assistant Scientist, Haryana Space Applications Centre (HARSAC), Hisar, Haryana, India.

6 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.