Topography data harmonisation and uncertainties applying SRTM, laser scanner and cartographic elevation models

Advances in Geosciences, 5, 65–73, 2005 SRef-ID: 1680-7359/adgeo/2005-5-65 European Geosciences Union © 2005 Author(s). This work is licensed under a Creative Commons License. Advances in Geosciences Topography data harmonisation and uncertainties applying SRTM, laser scanner and cartographic elevation models D. Haase1 and K. Frotscher2 1 UFZ – Centre for Environmental Research, Dept. of Applied Landscape Ecology, Permoserstr. 15, 04318 Leipzig, Germany 2 Friedrich-Schiller-University Jena, Department of Geography, Löbdergraben 10, 07743 Jena, Germany Received: 7 January 2005 – Revised: 1 August 2005 – Accepted: 1 September 2005 – Published: 16 December 2005 Abstract. Only a few studies have attempted to quantify topography-depending water fluxes, to evaluate retention and reservoir capacities and surface run-off paths within large river basins because data availability and data quality are critical issues to face this objective. It becomes most relevant if water balance has to be calculated in large or transboundary river basins. The advance of space based earth observation data offers a solution to this information problem. Therefore, this paper mainly focuses on weaknesses and strengths analyzing topography with SRTM (Shuttle Radar Topography Mission) digital height data and thus provides techniques for their improved application in river network derivation, floodplain analysis, watershed hydrology in large as well as in large river basins (>1000 km2 ). In the analysis different types of digital elevation models (DEM), terrain models (DTM) and land cover classification data (biotope map, Corine Land Cover 1994) have been used. The DHMs are generated from Airborne Laser Scanning (0.5 m), topographic maps (10.0/50.0 m) and SRTM at 30.0 m and 90.0 m spatial resolution. SRTM digital height models are generated by Synthetic Aperture Radar (SAR) and show a high spatial variance in urban areas, regions of dense vegetation canopy, floodplains and water bodies. As study area serve the Elbe basin (Czech Republic, Germany) with its sub-basins and the Saale river basin (Germany, different federal countries Saxony-Anhalt, Saxony and Thuringia). 1 Introduction One of the major challenges for an integrative European environmental development is the integrated management of transboundary (water) resources and large river basins in order to secure a sufficient availability of clean water (EuroCorrespondence to: D. Haase () pean Union 2003, EC 2002a, b, Gleick 2003, GWP-TAC 2000). Thus, for integrated water management methodical designs are necessary which refer to the complexity of the river basins to be managed and the difficulty to predict the factors or driving forces influencing them (economic development, demographic change, migration, Lutz, 2001). As a severe problem regular flood events in the plains resulting enormous financial losses of >10 Millions of Euro have to be considered. Increasing demands on land utilization (settlements, trade) within the floodplains are the main reason therefore (Gleick, 2003). Despite the above mentioned necessity only a few studies, however, have attempted to quantify water flows or to evaluate topography-related retention and reservoir capacities within large (transboundary) river basins because data availability and data quality are critical issues to face this objective. It is a methodical challenge to derive sound parameter sets of terrain and there from derived hydrological data required for the implementation of the Water Framework Directive (WFD) in such large river basins or, at least across national and administrative boundaries (Pahl-Wostl et al., 20051 ; Lammersen et al., 2002). Most of the higher resoluted elevation or terrain data are available often only for local sites, at the regional level for districts or federal states and, at most the national level. These data sets are not readily compatible at borderlines (Mysiak et al., 2004). Moreover, many higher resoluted terrain data (spatial resolution <50 m) are collected or compiled for specific purposes, projects or local/regional requirements and thus not available for larger areas/river basins. Because of their ecological importance, spatial and topographic heterogeneity it is still a challenge to analyse and to evaluate wetlands of large river basins, at regional, national and at transboundary level. Due to the ongoing exploitation 1 Pahl-Wostl, C., Downing, T., Kabat, P., Magnuszewski, P., Meigh, J., Schlueter, M., Sendzimir, J., and Werners, S.: Transitions to Adaptive Water Management: The Newater Project, Water Policy, submitted, 2005. 66 D. Haase and K. Frotscher: Topography data harmonisation and uncertainties Table 1. Properties of the Digital Elevation Model data set. SRTM-3 SRTM-1 DTM10/50 Laser Scanner (LSM) type of data surface model surface model terrain model surface model resolution horizontal vertical accuracy Actuality data source 300 ×300 Lat & Long 100 ×100 Lat & Long 90×90 m from 30×30 m ±6 m Feb 2000 Synthetic Aperture Radar (C-Band-SAR) 30×30 m ±6 m Feb 2000 Synthetic Aperture Radar (X-Band-SAR) 0.5×0.5 m ±0.15 m cross-border, worldwide equivalent quality (80% of land surface) free of charge, web-based, ftp-pull, available in blocks of 1◦ Lat×1◦ Lon cross-border, worldwide equivalent quality (<80% of land surface) not free, available in blocks of 150 Lat×150 Lon per 400 EU different, e.g. 10×10 m ±0.5 m different topographic data, e.g. isolines of topographic map 1:25 000 depending on national, regional borders, inconsistent mostly not free of charge, distributed by national/regional agencies, different quality and data recording Referring to borders Data availability of wetland reservoirs across Europe a successful protection and restoration of wetland functioning is extremely important and at a high level of the political agenda of the European environmental policy. Herewith related issues are a still missing sound wetland classification and topographic inventory completed for most of the larger European catchments to carry out further hydrological and ecological assessment and to derive management options. Earth observation (EO) platforms are the primary data source from which landscape patterns can be assessed (Herzog et al., 2001; Blaschke et al., 2001). Without a priori information about these patterns, observations provided by remote sensing sensors data supply an independent and unbiased framework to analyse the land cover at multiple scales (Hay et al., 2002). Two important scale-specific characteristics need to be considered: first the spatial, spectral and temporal resolution of each image pixel and secondly the image characteristics themselves, i.e. geographical area, combined band-widths and temporal duration. Within these data sets, only objects with “real-world relevance” may serve as suggested units over a range of scales. Recent studies describe how “image-objects”, nested in a hierarchical system of a mult (...truncated)