The Remote Sensing Department (RSD) of the Faculty of Geography/Geosciences at the University of Trier has a long-standing experience in using optical remote sensing systems for environmental research, and has participated in and coordinated numerous national and international interdisciplinary initiatives.

One major focus of the group lies on environmental remote sensing applications in dryland environments. Starting from the development and improvement of atmospheric correction and sensor calibration concepts (derived from multi-temporal satellite imagery, c.f. Hill 1993; Hill and Aifadopoulou 1990; Hill and Mehl 2003; Hill et al. 1995b; Hill and Sturm 1991; Röder et al. 2005), the group has developed its expertise in applying empirical and statistical models for using optical remote sensing systems to analyse land use change and land degradation phenomena (Hill et al. 1998; Hill et al. 1995a; Mégier et al. 1991; Sommer et al. 1998). These studies provided the background for scientific review papers and books (Hill 2000; Hill et al. 2004; Hill and Röder 2006; Hostert et al. 2001; Röder and Hill 2009; Röder et al. 2003) but also opened new perspectives for improving ecosystem assessment and monitoring concepts applied so far. Subsequent studies used spectral decomposition techniques in the context of long-term retrospective monitoring studies on global (Stellmes et al. 2006; Udelhoven 2006; Udelhoven and Hill 2009) to regional/local scale levels (Hill et al. 2008; Hostert et al. 2003a; Hostert et al. 2003b; Kuemmerle et al. 2006; Röder et al. 2008a; Röder et al. 2008b) and their integration with concepts of environmental modelling (Del Barrio et al. 2009; Duguy et al. 2007; Hill et al. 2009; Hill and Schutt 2000; Röder et al. 2007) and economic valuation (Lorent et al.2008).

A second field of research is in developing remote sensing methods for forestry applications, such as mapping tree species/age, timber volume inventories, biophysical parameter retrieval, identification of water stress and change detection. In this context, major emphasis is given to the implementation of physically-based coupled leaf/canopy reflectance models (Schlerf and Atzberger 2006; Vohland and Jarmer 2008). These models support quantitative approaches to extract bio-physical information from optical remote sensing systems, particularly from hyperspectral and LiDAR imagers (Buddenbaum et al. 2005; Koetz et al. 2005; Schlerf et al. 2005), which can be coupled with ecosystem process models. Research in this field benefits from a strategic partnership with the State Forest Administration ("Landesforsten Rheinland-Pfalz"); within ForestClim1, a EU-funded research project addressing forests and climate change, RSD is developing a state-wide forest mapping and inventory programme based on multi-temporal SPOT-4/5 imagery. Since more than 15 years, RSD has been involved in experimental flight campaigns with hyperspectral remote sensing systems (EARSEC, MAC EUROPE 92, HYEUROPE 2003, 2005, CEFLES-2), is presently building up its own hyperspectral imaging facility (HySpex) and is in charge of developing forest-related research within the Core Science Team of the German EnMAP2 (Environmental Mapping and Analysis Program) Mission, a German hyperspectral satellite designed for providing high quality hyperspectral image data for investigating a wide range of ecosystem parameters from 2013 onwards.

Buddenbaum, H., Schlerf, M., & Hill, J. (2005). Classification of coniferous tree species and age classes using hyperspectral data and geostatistical methods. International Journal of Remote Sensing, 26, 5453-5465

Del Barrio, G., Puigdefabregas, J., Sanjuan, M.E., Stellmes, M., & Ruiz, A. (2009). Assessment and monitoring of land condition in the Iberian Peninsula over 1989-2000. Remote Sensing of Environment, in print

Duguy, B., Alloza, J.A., Röder, A., Vallejo, R., & Pastor, F. (2007). Modeling the effects of landscape fuel treatments on fire growth and behaviour in a Mediterranean landscape (eastern Spain). International Journal of Wildland Fire, 16, 619-632

Hill, J. (1993). High precision land cover mapping and inventory with multi-temporal earth observation satellite data. The Ardèche experiment. Luxembourg: Office for Official Publications of the European Communities

Hill, J. (2000). Assessment of semi-arid lands: monitoring dryland ecosystems through remote sensing. In R.A. Meyers (Ed.), Encyclopedia of Analytical Chemistry - Instrumentation and Applications (pp. 8769-8794). Chichester: John Wiley & Sons

Hill, J., & Aifadopoulou, D. (1990). Comparative analysis of Landsat-5 TM and SPOT HRV-1 for use in multiple sensor approaches. Remote Sensing of Environment, 34, 55-70

Hill, J., Hostert, P., & Röder, A. (2004). Long-term observation of Mediterranean ecosystems with satellite remote sensing. In S. Mazzoleni, G. di Pasquale, M. Mulligan, P. di Marti & F. Rego (Eds.), Recent Dynamics of the Mediterranean Vegetation and Landscape (pp. 32-44). London: Wiley & Sons

Hill, J., Hostert, P., Tsiourlis, G., Kasapidis, P., Udelhoven, T., & Diemer, C. (1998). Monitoring 20 years of increased grazing impact on the Greek island of Crete with earth observation satellites. Journal of Arid Environments, 39, 165-178

Hill, J., Mégier, J., & Mehl, W. (1995a). Land degradation, soil erosion and desertification monitoring in Mediterranean ecosystems. Remote Sensing Reviews, 12, 107-130

Hill, J., & Mehl, W. (2003). Geo- and radiometric pre-processing of multi- and hyperspectral data for the production of calibrated multi-annual time series. Photogrammetrie-Fernerkundung- Geoinformation (PFG), 7, 7-14

Hill, J., Mehl, W., & Radeloff, V. (1995b). Improved forest mapping by combining corrections of atmospheric and topographic effects. In J. Askne (Ed.) (pp. 143-151). Rotterdam, Brookfield: A.A. Balkema

Hill, J., & Röder, A. (2006). Remote sensing of Mediterranean land degradation. Geographische Rundschau International Edition, 2, 51-57

Hill, J., Röder, A., Mehl, W., & Tsiourlis, G.M. (2009). Retrieving rangeland vegteation characteristics through constrained inverse reflectance modelling of earth observation satellite imagery. In A.

Röder & J. Hill (Eds.), Recent advances in remote sensing and geoinformation processing for land degradation assessment (pp. 281-300). London: Taylor&Francis

Hill, J., & Schutt, B. (2000). Mapping complex patterns of erosion and stability in dry Mediterranean ecosystems. Remote Sensing of Environment, 74, 557-569

Hill, J., Stellmes, M., Udelhoven, T., Röder, A., & Sommer, S. (2008). Mediterranean desertification and land degradation mapping related land use change syndromes based on satellite observations. Global and Planetary Change, 64, 146-157.

Hill, J., & Sturm, B. (1991). Radiometric correction of multitemporal Thematic Mapper data for use in agricultural land-cover classification and vegetation monitoring. International Journal of Remote Sensing, 12, 1471-1491 University of Trier FB VI Geography/Geosciences Remote Sensing Department

Hostert, P., Roder, A., & Hill, J. (2003a). Coupling spectral unmixing and trend analysis for monitoring of long-term vegetation dynamics in Mediterranean rangelands. Remote Sensing of Environment, 87, 183-197

Hostert, P., Röder, A., Hill, J., Udelhoven, T., & Tsiourlis, G. (2003b). Retrospective studies of grazing- induced land degradation: a case study in central Crete, Greece. International Journal of Remote Sensing, 24, 4019-4034

Hostert, P., Röder, A., Jarmer, T., Udelhoven, T., & Hill, J. (2001). The potential of remote sensing and GIS for desertification monitoring. State of the art and future research. Annals of Arid Zone, 40, 103-140

Koetz, B., Baret, F., Poilve, H., & Hill, J. (2005). Use of coupled canopy structure dynamic and radiative transfer models to estimate biophysical canopy characteristics. Remote Sensing of Environment, 95, 115-124

Kuemmerle, T., Röder, A., & Hill, J. (2006). Separating grassland and shrub vegetation by multidate pixel-adaptive spectral mixture analysis. International Journal of Remote Sensing, 27, 3251-3271

Lorent, H., Evangelou, C., Stellmes, M., Hill, J., Papanastasis, V.P., Tsiourlis, G.M., Röder, A., & Lambin, E.F. (2008). Land degradation and economic conditions of agricultural households in a marginal region of Northern Greece. Global and Planetary Change, 64, 198-209

Mégier, J., Hill, J., & Kohl, H. (1991). Land use inventory and mapping in a mountainous area: the Ardèche experiment. International Journal of Remote Sensing, 12, 445-462

Röder, A., Duguy, B., Alloza, J.A., Vallejo, R., & Hill, J. (2008a). Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. Remote Sensing of Environment, 112, 259-273

Röder, A., & Hill, J. (2009). Recent Advances in Remote Sensing and Geoinformation Processing for Land Degradation Assessment. London: Taylor & Francis

Röder, A., Hill, J., Duguy, B., Alloza, J.A., & Vallejo, R. (2005). Mapping fire events and post fire succession using long time series of Landsat-TM and -MSS data. In J. De La Riva, F. Perez-Cabello & E. Chuvieco (Eds.), 5th International Workshop on Remote Sensing and GIS Applications to Forest Fire Management: Fire Effects Assessment (pp. 287-290). Zaragoza, Spain

Röder, A., Hill, J., & Hostert, P. (2003). Fernerkundung und Geodatenverarbeitung zum Monitoring fon Desertifikation und Degradation im Mediterranen Raum. Photogrammetrie - Fernerkundung - Geoinformation, 1, 15-25

Röder, A., Kuemmerle, T., Hill, J., Papanastasis, V.P., & Tsiourlis, G.M. (2007). Adaptation of a grazing gradient concept to heterogeneous Mediterranean rangelands using cost surface modelling. Ecological Modelling, 204, 387-398

Röder, A., Udelhoven, T., Hill, J., Del Barrio, G., & Tsiourlis, G.M. (2008b). Trend analysis of Landsat-TM and -ETM+ imagery to monitor grazing impact in a rangeland ecosystem in Northern Greece. Remote Sensing of Environment, 112, 2863-2875

Schlerf, M., & Atzberger, C. (2006). Inversion of a forest reflectance model to estimate structural canopy variables from hyperspectral remote sensing data. Remote Sensing of Environment, 100, 281- 294.

Schlerf, M., Atzberger, C., & Hill, J. (2005). Remote sensing of forest biophysical variables using HyMap imaging spectrometer data. Remote Sensing of Environment, 95, 177-194.

Sommer, S., Hill, J., & Mégier, J. (1998). The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions. Agriculture, Ecosystems and Environment, 67, 197- 209

Stellmes, M., Sommer, S., & Hill, J. (2006). Use of the NOAA AVHRR NDVI-Ts feature space to derive vegetation cover estimates from long term time series for determining regional vegetation cover trends in the Mediterranean. In A. Röder & J. Hill (Eds.), 1st Conference on Remote Sensing and Geoinformation Processing in the Assessment and Monitoring of Land Degradation and Desertification (pp. 231-238). Trier, Germany University of Trier FB VI Geography/Geosciences Remote Sensing Department

Udelhoven, T. (2006). TimeStats: a software tool for analyzing spatial-temporal raster data archives: In: 1st Conference on Remote Sensing and Geoinformation. In A. Röder & J. Hill (Eds.), Proceedings of the 1st International Conference on "Remote Sensing and Geoinformation Processing in the Assessment and Monitoring of Land Degradation and Desertification. In support of the UN Convention to Combat Desertification (pp. 247-255). Trier, Germany

Udelhoven, T., & Hill, J. (2009). Change detection in Syria's rangelands using long-term AVHRR data (1982-2004). In A. Röder & J. Hill (Eds.), Recent advances in remote sensing and geoinformation processing for land degradation assessment (pp. 117-132). London: Taylor&Francis

Vohland, M., & Jarmer, T. (2008). Estimating structural and biochemical parameters for grassland from spectroradiometer data by radiative transfer modelling (PROSPECT+SAIL). International Journal of Remote Sensing, 29, 191-209