Land-use and land-cover change in Western Ghats of India

被引:0
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作者
Manish P. Kale
Manoj Chavan
Satish Pardeshi
Chitiz Joshi
Prabhakar A. Verma
P. S. Roy
S. K. Srivastav
V. K. Srivastava
A. K. Jha
Swapnil Chaudhari
Yogesh Giri
Y. V. N. Krishna Murthy
机构
[1] A Scientific Society of Ministry of Communication and IT,Centre for Development of Advanced Computing (C
[2] Govt. of India,DAC)
[3] Indian Institute of Remote Sensing,undefined
[4] Indian Space Research Organisation (ISRO),undefined
[5] Center for Earth & Space Sciences University of Hyderabad P.O. Central University,undefined
[6] National Remote Sensing Centre (NRSC),undefined
[7] Indian Space Research Organisation (ISRO),undefined
[8] Headquarters,undefined
[9] Antariksha Bhavan,undefined
来源
关键词
Western Ghats; Forest; Land-use land-cover; Simulation; R;
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摘要
The Western Ghats (WG) of India, one of the hottest biodiversity hotspots in the world, has witnessed major land-use and land-cover (LULC) change in recent times. The present research was aimed at studying the patterns of LULC change in WG during 1985–1995–2005, understanding the major drivers that caused such change, and projecting the future (2025) spatial distribution of forest using coupled logistic regression and Markov model. The International Geosphere Biosphere Program (IGBP) classification scheme was mainly followed in LULC characterization and change analysis. The single-step Markov model was used to project the forest demand. The spatial allocation of such forest demand was based on the predicted probabilities derived through logistic regression model. The R statistical package was used to set the allocation rules. The projection model was selected based on Akaike information criterion (AIC) and area under receiver operating characteristic (ROC) curve. The actual and projected areas of forest in 2005 were compared before making projection for 2025. It was observed that forest degradation has reduced from 1985–1995 to 1995–2005. The study obtained important insights about the drivers and their impacts on LULC simulations. To the best of our knowledge, this is the first attempt where projection of future state of forest in entire WG is made based on decadal LULC and socio-economic datasets at the Taluka (sub-district) level.
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