Land cover classification and change detection analysis using LandSat series and geospatial datasets in Nepal from 1980 to 2010

Nepal was ranked as one of the most climate vulnerable country in the world and a better understanding of vegetation patterns and their transformations is critically needed for environmental studies. Studies have shown that monitoring land use and land cover changes with conventional ground survey methods are time consuming and labor intensive. Remote sensing and GIS techniques have been widely employed by researchers due to its cost effective, time efficient and product consistency. This paper illustrates the method to develop land cover maps in Nepal in 1980s, 1990s, 2000s, and 2010s using LandSat series with the support of ancillary spatial datasets. The support vector machine (SVM) supervised classification techniques was used to develop land cover products of each decade. The spatial analysis of time series land cover products over time was employed to examine the changes. The accuracy of different land cover types ranged from 46% to 94% and the overall accuracy of land cover maps in 2010 is around 83% based on the ground truth data collected by the local collaborators. The results show a decrease trend of forest coverage although the rate of deforestation was declining over time. Meanwhile, the results also indicated an expansion of agriculture land in order to sustain the growing population. Similarly, the urban extent have been sprawling over time. The study provide accurate means of measuring the spatial distribution of major land cover types in Nepal over the last four decades that forms valuable resources for devise sustainable land use and environmental research.