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28 October 2015 An assessment of the impact of climate change effects on forest land cover based on satellite data
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Climate change affects forest both directly and indirectly through disturbances, that are a natural and integral part of forest ecosystems, and climate change can alter these natural interactions. Forest vegetation characteristics, including land cover and phenology, affect processes such as water cycle, absorption and re-emission of solar radiation, momentum transfer, carbon cycle, and latent and sensible heat fluxes. The climate system responds in complex ways to changes in forcing that may be natural or human-induced. Drastic climate change over the last decades has greatly increased the importance of forest land cover changes monitoring through time-series satellite data. Satellite based derived biophysical parameters for assessment of climate impacts on forest vegetation have to meet particularly high quality requirements. Forest vegetation and climate interact through a series of complex feedbacks, which are not very well understood. Satellite remote sensing is suited tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and GPP (Gross Primary Production), which are key biophysical variables for studying land surface processes and surface-atmosphere interactions for forested areas. The aim of this paper was to investigate their pattern dynamics due to the impact of climate variations on a periurban forest Branesti-Cernica, placed to the North-Eastern part of Bucharest city, Romania. The forest vegetation analysis was based on derived biogeophysical parameters from time-series satellite remote sensing MODIS Terra/Aqua and NOAA AVHRR data and in-situ monitoring ground data (as air temperature, aerosols distribution, relative humidity, etc.) over 2002–2014 period.
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Maria A. Zoran and Adrian I. Dida "An assessment of the impact of climate change effects on forest land cover based on satellite data", Proc. SPIE 9637, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII, 96372P (28 October 2015);

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