Showing papers by "Arijit Roy published in 2015"
University of Hyderabad1, Indian Space Research Organisation2, The Energy and Resources Institute3, Centre for Development of Advanced Computing4, Remote Sensing Center5, Indian Institute of Technology Kharagpur6, University of Illinois at Urbana–Champaign7, Banaras Hindu University8, CEPT University9, Anna University10, International Institute of Information Technology, Hyderabad11, Central University, India12, North Eastern Regional Institute of Science and Technology13
TL;DR: 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 to conclude that this dataset has captured the maximum cumulative patch diversity frequency, indicating the detailed representation that can be attributed to the on- screen visual interpretation technique.
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.
186 citations
University of Hyderabad1, Indian Institute of Technology Kharagpur2, International Centre for Integrated Mountain Development3, Indian Institute of Remote Sensing4, Remote Sensing Center5, TERI University6, Banaras Hindu University7, University of Twente8, International Water Management Institute9, Centre for Development of Advanced Computing10, International Center for Agricultural Research in the Dry Areas11, Wildlife Institute of India12, Annamalai University13, Berhampur University14, United Nations University15, Indian Institutes of Information Technology16, University of Agricultural Sciences, Dharwad17, World Agroforestry Centre18, University of Kashmir19, National Botanical Research Institute20, Assam University21, Kerala Forest Research Institute22, North Orissa University23, Botanical Survey of India24, University of Calcutta25, Lincoln University (Pennsylvania)26, Pondicherry University27, Mohanlal Sukhadia University28, University of Jammu29, Council of Scientific and Industrial Research30
TL;DR: This vegetation type map is the most comprehensive one developed for India so far and was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil.
140 citations
TL;DR: Fractal geometry has been used to quantitatively estimate the extent of irregularity in ecosystem changes as mentioned in this paper, however, in some cases it has been overly used giving misleading results, to avoid this, other metrics are also being used in studying changes in forest ecosystems.
Abstract: Changes in ecosystems are highly complex, heterogeneous and are extremely difficult to measure through single scale. Fractal geometry has been used to quantitatively estimate the extent of irregularity in ecosystem changes. However, in some cases it has been overly used giving misleading results. To avoid this, other metrics are also being used in studying changes in forest ecosystems. In this article, we review use of fractal geometry in measuring ecosystem components in a range of ecological conditions. Further, case studies from forest fragmentation and soil aggregates stability in different Indian tropical ecosystems with respect to management practices and environmental change have been described using fractal dimension. We have tried to point out some instances where fractals can more appropriately be used in assessing ecosystems properties and where it could not be successfully used. Characterization of ecological situations where fractals can effectively be used in general remains an important issue.
3 citations