SPATIOTEMPORAL CHANGE DETECTION IN FOREST COVER DYNAMICS ALONG LANDSLIDE SUSCEPTIBLE REGION OF KARAKORAM HIGHWAY, PAKISTAN
- 1National University of Sciences and Technology (NUST), Pakistan
- 2Head of Department, IGIS, National University of Sciences and Technology (NUST), Pakistan
Keywords: Deforestation, Supervised Image Classification, Geomatics, Change Detection, Kappa co-efficient
Abstract. Forest Cover dynamics and its understanding is essential for a country’s social, environmental, and political engagements. This research provides a methodical approach for the assessment of forest cover along Karakoram Highway. It has great ecological and economic significance because it’s a part of China-Pakistan Economic Corridor. Landsat 4, 5 TM, Landsat 7 ETM and Landsat 8 OLI imagery for the years 1990, 2000, 2010 and 2016 respectively were subjected to supervised classification in ArcMap 10.5 to identify forest change. The study area was categorized into five major land use land cover classes i.e., Forest, vegetation, urban, open land and snow cover. Results from post classification forest cover change maps illustrated notable decrease of almost 26 % forest cover over the time period of 26 years. The accuracy assessment revealed the kappa coefficients 083, 0.78, 0.77 and 0.85, respectively. Major reason for this change is an observed replacement of native forest cover with urban areas (12.5 %) and vegetation (18.6 %) However, there is no significant change in the reserved forests along the study area that contributes only 2.97 % of the total forest cover. The extensive forest degradation and risk prone topography of the region has increased the environmental risk of landslides. Hence, effective policies and forest management is needed to protect not only the environmental and aesthetic benefits of the forest cover but also to manage the disaster risks. Apart from the forest assessment, this research gives an insight of land cover dynamics, along with causes and consequences, thereby showing the forest degradation hotspots.