Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

Author： Roy Parth S. Roy Arijit Joshi Pawan K. Kale Manish P. Srivastava Vijay K. Srivastava Sushil K. Dwevidi Ravi S. Joshi Chitiz Behera Mukunda D. Meiyappan Prasanth Sharma Yeshu Jain Atul K. Singh Jamuna S. Palchowdhuri Yajnaseni Ramachandran Reshma. M. Pinjarla Bhavani Chakravarthi V. Babu Nani Gowsalya Mahalakshmi S. Thiruvengadam Praveen Kotteeswaran Mrinalni Priya Vishnu Yelishetty Krishna Murthy V. N. Maithani Sandeep Talukdar Gautam Mondal Indranil Rajan Krishnan S. Narendra Prasad S. Biswal Sushmita Chakraborty Anusheema Padalia Hitendra Chavan Manoj Pardeshi Satish N. Chaudhari Swapnil A. Anand Arur Vyas Anjana Reddy Mruthyunjaya K. Ramalingam M. Manonmani R. Behera Pritiranjan Das Pulakesh Tripathi Poonam Matin Shafique Khan Mohammed L. Tripathi Om P. Deka Jyotihman Kumar Prasanna Kushwaha Deepak

Publisher： MDPI

E-ISSN： 2072-4292|7|3|2401-2430

ISSN： 2072-4292

Source： Remote Sensing, Vol.7, Iss.3, 2015-02, pp. : 2401-2430

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Abstract

India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.