INTRODUCTION

Natural hazards such as landslides involving small to large ground movements are mainly triggered due to unstable slopes with scanty green cover. Unstable sloped are induced due to the removal of vegetation cover, rock falls, deep failure of slopes, shallow debris flows, ground water pressure, erosion, soil nutrients, soil structure, etc. The actual landslide often requires a trigger before being released and in most cases, a change in land cover (LC) due to the loss of vegetation is a primary factor that builds up specific sub-surface conditions for landslide to occur. The loss in forest cover due to LC change has increased rapidly in recent times due to increasing mankind needs. Forest cover is reduced to almost half of the ecologically desired amount [1] and about 72 percent of India’s forests have lost their viability for regeneration, with forest grazing being one of the most important causes [2]. Forest fragmentation apart from affecting the biodiversity and ecology of the region has a significant influence in the movement of soil (silt) and debris in undulating terrains with high intensity rainfall. Forest fragmentation analysis spatially aids in visualising the regions that require immediate attention to minimise natural calamities such as landslides. Spatial fragmentation map depicts the type and extent of fragmentation derived from land use (LU) data which are obtained from multi-source, multi-sensor, multi-temporal, multi-frequency or multi-polarization remote sensing (RS) data. The objectives of this paper are

1. Classification of multi-temporal RS data using Maximum Likelihood classifier to obtain LU map.
2. Multi-temporal forest fragmentation analysis for five watersheds in Uttara Kannada to characterise the type and extent of fragmentation or loss of vegetation cover.
3. Visualising the consequences of fragmentation for landslide susceptibility.