Assessing deforestation susceptibility to forest ecosystem in Rudraprayag district, India using fragmentation approach and frequency ratio model
Science of The Total Environment, ISSN: 0048-9697, Vol: 627, Page: 1264-1275
2018
- 45Citations
- 103Captures
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Metrics Details
- Citations45
- Citation Indexes44
- 44
- CrossRef38
- Policy Citations1
- Policy Citation1
- Captures103
- Readers103
- 103
Article Description
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 km 2 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.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0048969718303292; http://dx.doi.org/10.1016/j.scitotenv.2018.01.290; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85041490114&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/30857091; https://linkinghub.elsevier.com/retrieve/pii/S0048969718303292; https://dx.doi.org/10.1016/j.scitotenv.2018.01.290
Elsevier BV
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