GeoRange Consortium

The Department

The Remote Sensing Department of the University of Trier is part of the Faculty of Geography/Geosciences in which major emphasis is given to interdisciplinary research in geosciences and geomatics. Besides teaching within the fields of Applied Physical Geography and Environmental Sciences, the department has acquired a large expertise in remote sensing and GIS applications. The focus of research lies on land use/land cover mapping, environmental monitoring and modelling using earth observation and airborne remote sensing data. In this context, special emphasis is given to the development of new and standardised image processing techniques, spectrometry, reflectance modelling, integration of remote sensing data and GIS, and the quantitative integration of different sensors. The relevance and concrete applicability of these methodologies is supported by their integration into a number of completed and pending research projects, such as DeMon-1 and -2, Lucifer, Floodgen or the German Research Foundation (DFG)-funded SFB 522 "Environment and Region". The Department is equipped with a Unix-/NT-network, and disposes of a number of high-precision devices for field and laboratory assessments, such as two ASD Fieldspec II spectroradiometers, a Trimble Pathfinder Pro XRS differential GPS, a LICOR LAI measurement device and a CIMEL broadband spectroradiometer.

The Remote Sensing Department is co-ordinating the project. On the methodological side, it shares responsibility for the processing and analysis of satellite image time series acquired with earth observation satellites (EOS) with JRC-LUC. Besides conceptual and methodological developments for deriving vegetation-related parameters from reflective remote sensing data, the design and implementation of customised GIS environments and Internet Map Exchange facilities will be major contributions to the project. In particular the retrospective analysis of rangeland dynamics from remote sensing data will provide important base data to unravel the impact of past management strategies. Beside this, the focus will be set upon the development of methods to combine high spatial and spectral resolution satellite imagery for structural analysis, and the derivation of quantitative estimates of key variables (LAI, biomass, plant pigment and plant water concentrations) from the inversion of reflectance models.


	Georange Consortium - FEUT
	Remote Sensing Department, Faculty of Geography/Geosciences, Universität Trier, Germany (FEUT)	click to access web page
	The Department The Remote Sensing Department of the University of Trier is part of the Faculty of Geography/Geosciences in which major emphasis is given to interdisciplinary research in geosciences and geomatics. Besides teaching within the fields of Applied Physical Geography and Environmental Sciences, the department has acquired a large expertise in remote sensing and GIS applications. The focus of research lies on land use/land cover mapping, environmental monitoring and modelling using earth observation and airborne remote sensing data. In this context, special emphasis is given to the development of new and standardised image processing techniques, spectrometry, reflectance modelling, integration of remote sensing data and GIS, and the quantitative integration of different sensors. The relevance and concrete applicability of these methodologies is supported by their integration into a number of completed and pending research projects, such as DeMon-1 and -2, Lucifer, Floodgen or the German Research Foundation (DFG)-funded SFB 522 "Environment and Region". The Department is equipped with a Unix-/NT-network, and disposes of a number of high-precision devices for field and laboratory assessments, such as two ASD Fieldspec II spectroradiometers, a Trimble Pathfinder Pro XRS differential GPS, a LICOR LAI measurement device and a CIMEL broadband spectroradiometer. GeoRange The Remote Sensing Department is co-ordinating the project. On the methodological side, it shares responsibility for the processing and analysis of satellite image time series acquired with earth observation satellites (EOS) with JRC-LUC. Besides conceptual and methodological developments for deriving vegetation-related parameters from reflective remote sensing data, the design and implementation of customised GIS environments and Internet Map Exchange facilities will be major contributions to the project. In particular the retrospective analysis of rangeland dynamics from remote sensing data will provide important base data to unravel the impact of past management strategies. Beside this, the focus will be set upon the development of methods to combine high spatial and spectral resolution satellite imagery for structural analysis, and the derivation of quantitative estimates of key variables (LAI, biomass, plant pigment and plant water concentrations) from the inversion of reflectance models.


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