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

Application of DSSAT crop model for wheat crop growth simulation in some wheat growing districts of northern India

Process based Crop growth simulation models are being used as a potential decision support tool for informed decision making by policy makers and researchers. Calibration and validation of a crop growth simulation model is the fundamental process before applying the model projections to a new location. CERES crop growth simulation model has been used by a number of researchers worldwide to simulate wheat growth. This study is undertaken to calibrate and validate CERES model on DSSAT (Decision Support System for Agro Technology Transfer) platform for six predominantly wheat growing districts of Northern India

Assessment of satellite and model derived long term solar radiation for spatial crop models: A case study using DSSAT in Andhra Pradesh

Crop Simulation models are mathematical representations of the soil plant-atmosphere system that calculate crop growth and yield, as well as the soil and plant water and nutrient balances, as a function of environmental conditions and crop management practices on daily time scale. Crop simulation models require meteorological data as inputs, but data availability and quality are often problematic particularly in spatialising the model for a regional studies. Among these weather variables, daily total solar radiation and air temperature (Tmax and Tmin) have the greatest influence on crop phenology and yield potential. The scarcity of good quality solar radiation data can be a major limitation to the use of crop models. Satellite-sensed weather data have been proposed as an alternative when weather station data are not available. These satellite and modeled based products are global and, in general, contiguous in time and also been shown to be accurate enough to provide reliable solar and meteorological resource data over large regions where surface measurements are sparse or nonexistent. In the present study, an attempt was made to evaluate the satellite and model derived daily solar radiation for simulating groundnut crop growth in the rainfed distrcits of Andhra Pradesh. From our preliminary investigation, we propose that satellite derived daily solar radiation data could be used along with ground observed temperature and rainfall data for regional crop simulation studies where the information on ground observed solar radiation is missing or not available