Assessing deforestation susceptibility to forest ecosystem in Rudraprayag district, India using fragmentation approach and frequency ratio model Mehebub Sahana a , Haoyuan Hong b,c,d, ⁎, Haroon Sajjad a, ⁎⁎, Junzhi Liu b,c,d , A-Xing Zhu b,c,d a Department of Geography, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India b Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing, 210023, China c State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China d Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing, Jiangsu 210023, China HIGHLIGHTS • Deforestation susceptibility was assessed using frequency ratio model. • Influence of forest fragmentation on de- forestation susceptibility was analyzed. • Influence of natural and anthropogenic drivers on deforestation susceptibility • The methodology of the study proved useful for deforestation susceptibility assessment. GRAPHICAL ABSTRACT abstract article info Article history: Received 30 November 2017 Received in revised form 28 January 2018 Accepted 28 January 2018 Available online xxxx Editor: Elena PAOLETTI 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 agricul- tural 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 susceptibil- ity mapping. The extent of deforestation was examined by overlaying forest fragmentation map and deforesta- tion 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 mod- erate 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, frag- mentation approach and remote sensing and GIS techniques has proved useful in analyzing deforestation suscep- tibility and identifying its causative factors. Thus, the methodology adopted in this study can best be utilized for effective planning and management of forest ecosystem. © 2018 Elsevier B.V. All rights reserved. Keywords: Deforestation susceptibility Frequency ratio model Forest fragmentation Remote sensing and GIS Rudraprayag District Science of the Total Environment 627 (2018) 1264–1275 ⁎ Correspondence to: H. Hong, Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China. ⁎⁎ Corresponding author. E-mail addresses: hong_haoyuan@outlook.com (H. Hong), haroon.geog@gmail.com (H. Sajjad). https://doi.org/10.1016/j.scitotenv.2018.01.290 0048-9697/© 2018 Elsevier B.V. All rights reserved. Contents lists available at ScienceDirect Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv