Literature DB >> 30857091

Assessing deforestation susceptibility to forest ecosystem in Rudraprayag district, India using fragmentation approach and frequency ratio model.

Mehebub Sahana1, Haoyuan Hong2, Haroon Sajjad3, Junzhi Liu4, A-Xing Zhu4.   

Abstract

This study aimed to model deforestation susceptibility in forest ecosystem of Rudraprayag district, India. For this purpose, site-specific physical (slope angle, slope aspect, altitude, annual average rainfall, soil texture, soil depth), and anthropogenic (population distribution, distance from road, distance from settlement, proximity to agricultural land) deforestation conditioning factors were chosen. Landsat TM and OLI images for 1990 and 2015 were utilized to evaluate the changes in forest cover. The frequency ratio model was used for deforestation susceptibility mapping. The extent of deforestation was examined by overlaying forest fragmentation map and deforestation susceptibility map. The results showed that about 112.5km2 forest area has been deforested over the last 25years. Of the total existing forest, nearly 10% area falls under very high, 17% under high and 30% under moderate deforestation susceptibility categories. Patch, edge and perforated have influenced high (64%) and very high (81%) deforestation susceptibility zones. The integrated methodology involving frequency ratio model, fragmentation approach and remote sensing and GIS techniques has proved useful in analyzing deforestation susceptibility and identifying its causative factors. Thus, the methodology adopted in this study can best be utilized for effective planning and management of forest ecosystem.
Copyright © 2018 Elsevier B.V. All rights reserved.

Keywords:  Deforestation susceptibility; Forest fragmentation; Frequency ratio model; Remote sensing and GIS; Rudraprayag District

Mesh:

Year:  2018        PMID: 30857091     DOI: 10.1016/j.scitotenv.2018.01.290

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Modelling Agriculture, Forestry and Other Land Use (AFOLU) in response to climate change scenarios for the SAARC nations.

Authors:  Ram Kumar Singh; Vinay Shankar Prasad Sinha; Pawan Kumar Joshi; Manoj Kumar
Journal:  Environ Monit Assess       Date:  2020-03-14       Impact factor: 2.513

  1 in total

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