Abstract : 1B.7
Remote sensing monitoring of air pollution and climatic changes effects on Mountain forest systems
National Institute of R&D for Optoelectronics , Remote Sensing Dept.
The climate system responds in complex ways to changes in forcing that may be natural (e.g., variations in the magnitude of solar radiation reaching the top of the atmosphere) or human-induced (e.g., changing atmospheric concentrations of greenhouse gases).Climate-induced changes at the land surface (e.g., through more intense and higher frequency droughts) may in turn feed back on the climate itself, for example, through changes in soil moisture, vegetation, radiative characteristics, and surface-atmosphere exchanges of water vapor.
Thresholding based on biophysical variables derived from time trajectories of satellite data is a new approach to classifying forest land cover via remote sensing at coarse resolutions. This approach is attractive because it is much simpler than conventional alternatives. Further, it operates on biophysical variables and thus should be more robust than more data dependent techniques. The input data are composite values of the Normalized Difference Vegetation Index (NDVI). Associated with these values are radiances in three thermal bands that are used to estimate surface temperature. The classification algorithm, accepts mean growing-season NDVI, mean growing-season near-infrared radiance, NDVI amplitude and surface temperature as input parameters for the composite NDVI and surface temperature data. The units recognized are broad life-form vegetation classes, such as evergreen needle leaf forest, evergreen broadleaf forest, shrubs, etc. Classification accuracies are variable, depending on the class and the comparison method as well as function of season of the year. Our analysis indicates a potentially application of threshold techniques to land-cover classification and changes analysis due to climatic effects for Romanian Carpathian montane forest ecosystem . The climate of the Carpathians is moderately cool and humid, with both temperature and precipitation strongly correlated with elevation.Extreme climatic events and anthropogenic effects have a strong impact on forest ecosystem. Specific aim of this paper is to assess, forecast, and mitigate the risks of air pollution and climatic changes and extreme events on montane forest ecosystem in Prahova Valley, Romanian Carpathians test area and to provide early warning strategies on the basis of spectral information derived from MODIS satellite data as well as numerical simulations the regional climate model RegCM3.