Efficient geomorphological mapping based on geographic information systems and remote sensing data: an example from Jena, Germany

Abstract

We present a detailed geomorphological map (1:5000-scale) of a middle mountainous area in Jena, Germany. To overcome limitations and to extend the possibility of manually digital mapping in a structural way, we propose an approach using geographic information systems (GIS) and high-resolution digital data. The geomorphological map features were extracted by manually interpreting and analyzing the combination of different data sources using light detection and ranging (LiDAR) data. A combination of topographic and geological maps, digital orthophotos (DOPs), Google Earth images, field investigations, and derivatives from digital terrain models (DTMs) revealed that it is possible to generate the geomorphologic features involved in classical mapping approaches. LiDAR-DTM and land surface parameters (LSPs) can provide better results when incorporating the visual interpretation of multidirectional hillshade and LSP composite maps.Findings enabled us to systematically delineate landforms and geomorphological process domains. We suggest that further use of digital data should be undertaken to support analysis and applications.