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International Journal of Geophysics
Volume 2018, Article ID 2847504, 7 pages
Research Article

Integration of Earth Observation Data and Spatial Approach to Delineate and Manage Aeolian Sand-Affected Wasteland in Highly Productive Lands of Haryana, India

1Centre for Remote Sensing and Geoinformatics, Sathyabama Institute of Science and Technology, Chennai 600119, India
2Division of Environmental Sciences, Indian Agricultural Research Institute, New Delhi 110012, India
3K. Banerjee Centre of Atmospheric and Ocean Studies, IIDS, Nehru Science Centre, University of Allahabad, Allahabad, India

Correspondence should be addressed to Kishan Singh Rawat; moc.liamg@nahsik.rsk

Received 29 August 2017; Revised 30 January 2018; Accepted 20 February 2018; Published 27 March 2018

Academic Editor: Akhilesh Mishra

Copyright © 2018 Kishan Singh Rawat et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The western part of the country India is surrounded by Thar desert. Due to climate change, many regions in the world are facing different challenges. The objective of the study was to quantify the aeolian sand-affected land through integrated approach. The LANDSAT-ETM+ satellite image of 2009 has been used to distinguish recently affected areas by aeolian sand. A combined approach of digital classification backed with visual interpretation and ground verification was adopted. In addition to classification accuracy assessment was performed using field observations. Evidence based results of aeolian sand-affected areas have suggested that wasteland area has increased up to 4,427.55 ha (6.79%) of total geographical area. Two types of aeolian sands areas have been detected, namely, moderately affected (3,881.77 ha) and severely affected (545.79 ha). Moderately and severely affected aeolian soil lands have been more accurately mapped with reasonably good accuracy whereas smaller aeolian affected areas within croplands are mapped with low accuracy. The present study provides easy methodology for delineation, classification, and characterization of aeolian affected sands.