RS-based regional crop identification and mapping: A case study of Barwala sub-branch of Western Yamuna Canal in Haryana (India)

-, Arvind ; Hooda, R S; Sheoran, Hardeep Singh; Kumar, Devendra ; -, Satyawan ; -, Abhilash ; Bhardwaj, Sushant


Information on spatial land use is the main input in strategic and tactical plan-making by all agricultural participants in countries like India with agriculture at the mainstay of the economy. In addition, accurately evaluation of the management of crops in a spatio-temporal context, information on cropping systems is also required, but such information on a regional scale are scarcely available. The spectrum of multiannual patterns of land use on cultivable land, however, remains unknown. The paper thus focuses on the mapping of the cropping systems that are actually practiced in Hisar District of Haryana (India). The objective of this research was to use satellite data and Remote Sensing (RS) techniques to identify the cropping pattern of Barwala sub-branch of Sirsa branch of the Western Yamuna Canal in Haryana. To identify classes of interest, handheld GPS was used to collect ground-truth information. Mask of mixed classes was developed to reclassify an image under the mask. Moreover, appropriate classification of images and application of logical combinations helped in generating cropping pattern maps and statistics. Results revealed that major crops identified in the study area were cotton, rice and pearl-millet in Kharif season, which accounts for about 70% of total cultivated area. In the case of Rabi season, wheat and mustard were observed as the major crops covering approximately 57% of total area. RS technology is currently capable of providing cropping pattern with 90% accuracy. The results of the current study could be useful in the land use and efficient water management in the canal command areas in the water-scarce southern Haryana, India. Some crops like guar, pearl-millet, horticultural crops, etc. were also identified during this period but the major crops that were identified during Kharif season were Rice and Cotton.


Classification; Cropping pattern; Landsat 8; ISODATA; Remote sensing

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