Retrieval of Land Surface Parameters for Vegetation Degradation Monitoring in Arid and Semi-arid regions

摘要

Land surface characterisation is gaining importance due to swift transformations occurring at earth-atmosphere interface. The far-reaching changes brought in the course of the exchange of radiant energy between earth surface and the atmosphere due to rapid urbanisation, deforestation, land degradation and desertification has ultimately resulted in substantial changes in land surface parameters at local, regional and global level. Owing to the significant role arid and semi-arid ecosystems play in determining the intricacies of earth-atmosphere interactions and ultimately affecting the global climatic mechanisms, land surface studies have thus become imperative to assess the potential impact of the environmental changes taking place at the boundary of earth's surface and the atmosphere. The vegetation in arid and semi-arid regions experiences a phenomenal change in its growth pattern and is highly dynamic. The change in vegetation canopy density with the change of season has great impact on the land surface properties and their interactions. It is thus very important to assess and monitor the vegetation status and seasonal growth characteristics in association plant diversity in these regions. Vegetation degradation monitoring in arid and semi-arid regions requires longterm observations of vegetation extent and involves the use of a number of parameters (NDVI, Evapotranspiration, PAR, LAI etc.,)to substantiate its impact on these marginal ecosystems. The land surface parameters that have gained recognition for deriving real-time estimates of vegetation condition in these regions are GLAI (green leaf area index), gfc (green fractional cover), albedo, surface temperature, and surface emissivity to name a few. Of these the green leaf area index and green fractional cover have a unique importance owing to their characteristics and their capability to be linked with seasonal changes in vegetation condition. This paper will present an operational methodology developed through retrieval of land surface parameters for arid and semiarid regions of Rajasthan using multi temporal and multi-scale satellite data. The satellite data used in this study are S-1 and S-10 data from SPOT Vegetation (4&5), IRS-WiFS and IRS-LISS-Ⅲ data. Satellite data from these sensors gives fairly reasonable estimates of vegetation amount and condition when linked with surface biophysical parameters. The biophysical variables like GLAI and gfc, calculated over a period of time gives real-time spatial description of changes in land use and land cover and can be incorporated into models to make more realistic assessments of linkages between changes in surface properties and biogeochemical processes. The phenological information coupled with the land surface parameters provide valuable inputs to describe the interactions occurring at the atmosphere-geosphere interface. The seasonality captured through these multitemporal datasets gives an insight into the various processes of energy exchange phenomenon taking place at land surface. It is of significance to regional climate change studies and large scale monitoring of land use and land cover changes. The surface parameters derived from satellite data for the entire study area will serve as a baseline datum to further the studies related to vegetation degradation monitoring and climate change modelling.