About SemantiX
Long time series of essential climate variables (ECVs) derived from satellite data is an important contribution to climate research. They are a critical, independent source of information for comparison with climate model results, but they can also be used to directly detect and monitor changes in our environment. The Remote Sensing Research Group at the University of Bern’s Institute of Geography has compiled and archived the longest European time series (1981-2019) of AVHRR data that has been processed using physical methods and algorithms (e.g., lake surface temperature, snow cover, vegetation dynamics). In SemantiX, this time series will be complemented and expanded using Sentinel-3 A/B data and made accessible in a newly developed EO-midstream technology, a semantic EO data cube. This technology will be linked to a mobile citizen science application giving the public a new, direct and interactive access point to EO data and derived information products.
SemantiX will combine AVHRR and Sentinel-3 A/B data using new methods to create a unique, long time series that can be carried into the future through continued integration of newly acquired Copernicus Sentinel 3 data. Until now, AVHRR data have only been accessible via sequential access, requiring a significant time investment and expert knowledge to find relevant data for analysis. Interested scientists from other disciplines or the broader public currently do not have any access to these methods or data.
Earth observation (EO)-based information are unfortunately still nearly as remote from relevant target groups as EO satellites are from the Earth. Therefore, unlocking the potential of EO-data-derived information is crucial. It contributes to finding solutions to pressing global problems, such as how best to mitigate climate change. The SemantiX project is an approach to better facilitate access to EO data and derived information for scientists and the public, and promote active public participation, gaining additional information through citizen science. The project aims to simplify information production from EO data to variables relevant to climate change monitoring.
Progress in climatology has been very well documented by the Intergovernmental Panel on Climate Change (IPCC) in AR4 to AR5, which makes it particularly worthwhile to focus on remote sensing in this field. Satellite remote sensing has increasingly contributed to monitoring global conditions of particular importance to climate change studies. The increasing spatial, temporal, spectral and radiometric resolution of these data, simplified access, and lower to no costs to users have led to an increased likelihood of documenting changes driven or accelerated by human activities.
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