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Vegetation responses to changing climate patterns need to be understood to devise adaptation strategy for a sustainable development,especially in the light of increasing climate related vulnerability. Dynamic Global Vegetation Models(DGVM) have the capacity andscope to develop understanding in this regard, due to their ability in simulating plant-vegetation-climate processes incorporatingbioclimatic variables. However, prior to take up modelling using a spatially explicit DGVM, it may be imminent to prioritize the area forvulnerable contexts, so as to calibrate and validate the model optimally. Spatially explicit DGVMs require site level observations atcanopy and leaf level/soil strata level for parametrization and implementation. Satellite data in VNIR and thermal regimes provide scopeto understand the responses of various vegetation categories and enable to set up baseline addressing the foci of change as regions ofvulnerability. Study carried out Western Himalayan transect using MODIS enhanced vegetation index and land surface temperatureillustrates potential to differentiate areas that can be vulnerable due to warming trends disturbing cold to warm season energy leveltransition. Relations of these indices were studied in different vegetation categories and modelled spatially to derive potential vulnerablezones. Many sites showed high vulnerability while some sites showed distinct resilient behaviour by showing increase in EVI duringwarming periods. Potential zones were studied further using a spatially explicit Dynamic Global Vegetation Model for site levelunderstanding. DGVM results in terms of biomass and carbon were studied to understand the trends in the vulnerable and resilient sites.Detailed characterisation of DGVM based modelling is underway to further diagnose the vulnerability contexts

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

VULNERABILITY OF VEGETATION IN PARTS OF HIMALAYAS AND DYNAMIC GLOBAL VEGETATION MODELLING (DGVM) – STUDY USING VNIR AND THERMAL RESPONSES OF MODIS TIME SERIES DATA