HYECO - Hydro-ecological modelling supported by spectral directional imaging

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Context and objectives

The preservation of biodiversity is an increasingly important topic in European policy. Natural areas are constantly undergoing changes, mostly driven by socio-economic changes, and many of these changes lead to a reduction of the biodiversity. The following main research questions will be dealt with in this project:
  • Which variables should be considered to be retrieved from hyperspectral and multispectral remote sensing, taking into account accuracy requirements of the ecological models?
  • How is the uncertainty of remote sensing derived variables propagated into the ecological models?
  • To what extent can uncertainty in model output be reduced by replacing present model input data by remote sensing derived variables?
  • How can data derived from in situ (field) studies be extrapolated to scales that are relevant for ecological applications (regional, national and European scale)?
  • How do differences in RS supported energy balance model formulations (i.e. SEBS and SEBAL) effect estimates of evapotranspiration.
  • What is the dependence of the directionality of estimations of elements of the energy balance on different scales.
  • Project outcome

    Expected scientific results

    Eco- Hydrology: Identifying, developing and mapping of proxy for wetness conditions for valley areas.
    Flooding and vegetation management: Potential assessment of limnological water parameters using quantitative models to derive Chl a and b content, DOC and suspended matter in turbid and still waters.
    Spectral scaling, spectral libraries and spectral unmixing: Integration of field spectral samples into an object-relational data base for the further use in continuous classification and abundance map generation.
    Modelling and radiative transfer: Using leaf optical properties models linked with canopy models (e.g. PROSPECT, LEAFMOD and SAIL, GeoSAIL) to simulate the canopy HDRF.
    Habitat and vegetation mapping (spatial uncertainties): Land use and land cover classification using combined continuous and discrete classification approaches in combination with the development of spatial metrics to describe patterns of landscapes and to quantify the ecological impact of spatio-temporal dynamics of terrestrial ecosystems.
  • Species and diversity fragmentation: The use of hyperspectral data will enable an improved detection and identification of land use and land cover changes.
  • Product generation: Generation of second and third level products for the final end-user. Compilation of individual results. Communication of results to a larger audience. ecosystem scaling to spatially explicit areas.