Modelling Spatial and Temporal Forest Cover Change Patterns (1973-2020): A Case Study from South Western Ghats (India)

• Published in: Sensors (Basel, Switzerland) Vol. 8; no. 10; pp. 6132 - 6153
• Main Authors: Giriraj, Amarnath, Irfan-Ullah, Mohammed, Murthy, Manchi Sri Ramachandra, Beierkuhnlein, Carl
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.10.2008; Molecular Diversity Preservation International (MDPI)
• Subjects: Biodiversity; Biogeography; Case studies; Deforestation; Ecology; Endangered & extinct species; Flowers & plants; Forest cover change; Forestry; Geographic information systems; GEOMOD; monitoring; Remote sensing; Sensors; tropical forest; Western Ghats; Western Ghats; Tamil Nadu India; India; Forest cover change; GEOMOD; Western Ghats; tropical forest; monitoring
• DOI: 10.3390/s8106132
• ISSN: 1424-8220

This study used time series remote sensing data from 1973, 1990 and 2004 to assess spatial forest cover change patterns in the Kalakad-Mundanthurai Tiger Reserve (KMTR), South Western Ghats (India). Analysis of forest cover changes and its causes are the most challenging areas of landscape ecology, especially due to the absence of temporal ground data and comparable space platform based data. Comparing remotely sensed data from three different sources with sensors having different spatial and spectral resolution presented a technical challenge. Quantitative change analysis over a long period provided a valuable insight into forest cover dynamics in this area. Time-series maps were combined within a geographical information system (GIS) with biotic and abiotic factors for modelling its future change. The land-cover change has been modelled using GEOMOD and predicted for year 2020 using the current disturbance scenario. Comparison of the forest change maps over the 31-year period shows that evergreen forest being degraded (16%) primarily in the form of selective logging and clear felling to raise plantations of coffee, tea and cardamom. The natural disturbances such as forest fire, wildlife grazing, invasions after clearance and soil erosion induced by anthropogenic pressure over the decades are the reasons of forest cover change in KMTR. The study demonstrates the role of remote sensing and GIS in monitoring of large-coverage of forest area continuously for a given region over time more precisely and in cost-effective manner which will be ideal for conservation planning and prioritization.