Analysis of Temporal and Spatial Changes in the Vegetation Density of Similipal Biosphere Reserve in Odisha (India) Using Multitemporal Satellite Imagery
National parks and protected areas require periodic monitoring because of changing land cover types and variability of landscape contexts within and adjacent to their boundaries. In this study, remote sensing and GIS techniques were used to analyse the changes in the vegetation density particularly in the zones of higher anthropogenic pressure in the Similipal Biosphere Reserve (SBR) of Odisha (India), using Landsat imagery from 1975 to 2005. A technique for the detection of postclassification changes was followed and the change in vegetation density as expressed by normalized difference vegetation index was computed. Results indicate that high dense forest in the core zone has been conserved and the highest reforestation has also occurred in this zone of SBR. The results also reveal that anthropological interventions are more in the less dense forest areas and along the roads, whereas high dense forest areas have remained undisturbed and rejuvenated. This study provides baseline data demonstrating alteration in land cover over the past three decades and also serves as a foundation for monitoring future changes in the national parks and protected areas. 1. Introduction Promoting and facilitating the use of remotely sensed images for the monitoring and management of national parks and other protected areas have been the focus of many research and governmental agencies. Monitoring landscape dynamics can answer questions of what the spatial extent of land cover types within and adjacent to the parks and the protected areas and is how they have changed over time. Vegetation mapping is a very important application of remotely sensed data. Spectral profiles of vegetation clearly show that the peak reflectance can be found in the near-infrared wavelengths mainly because of the internal structure of “green” leaves, and the greatest absorption is in the red wavelengths because of the presence of chlorophyll pigments. The normalized difference vegetation index (NDVI) is one of the most successfully used vegetation indices for land cover classification [1–4]. It is also used as an environmental indicator to monitor temporal and spatial variation in vegetation density as well as the health and viability of plant cover over time [5–8] for the derivation of biophysical properties [9–11] and for estimation of net primary production [12–14]. The NDVI is correlated with many biophysical parameters of the vegetation canopy such as leaf area index (LAI), fractional vegetation cover, vegetation condition, and biomass. The NDVI values increase as green cover density
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