Assessing deforestation susceptibility to forest ecosystem in Rudraprayag district, India using fragmentation approach and frequency ratio model
Creators
- 1. Department of Geography, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi (India)
- 2. Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing, Jiangsu 210023 (China)
- 3. State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023 (China)
- 4. Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing, 210023 (China)
Description
Highlights: • Deforestation susceptibility was assessed using frequency ratio model. • Influence of forest fragmentation on deforestation susceptibility was analyzed. • Influence of natural and anthropogenic drivers on deforestation susceptibility • The methodology of the study proved useful for deforestation susceptibility assessment. 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 112.5 km2 forest area has been deforested over the last 25 years. 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.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.scitotenv.2018.01.290Additional details
Identifiers
- DOI
- 10.1016/j.scitotenv.2018.01.290;
- PII
- S0048969718303292;
Publishing Information
- Journal Title
- Science of the Total Environment
- Journal Volume
- 627
- Journal Page Range
- p. 1264-1275
- ISSN
- 0048-9697
- CODEN
- STENDL
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 53044011
- Subject category
- S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- ALTITUDE; DEFORESTATION; DISTANCE; ECOSYSTEMS; FORESTS; FRAGMENTATION; GEOGRAPHIC INFORMATION SYSTEMS; IMAGES; INDIA; POPULATIONS; REMOTE SENSING; ROADS; SOILS
- Descriptors DEC
- ASIA; DEVELOPING COUNTRIES; INFORMATION SYSTEMS
Optional Information
- Copyright
- Copyright (c) 2018 Elsevier B.V. All rights reserved.