Systematic Approach for Remote Sensing of Historical Conflict Landscapes with UAV-Based Laserscanning

In order to locate historical traces, drone-based Laserscanning has become increasingly popular in archaeological prospection and historical conflict landscapes research. The low resolution of aircraft-based Laserscanning is not suitable for small-scale detailed analysis so that high-resolution UAV-based LiDAR data are required. However, many of the existing studies lack a systematic approach to UAV-LiDAR data acquisition and point cloud filtering. We use this methodology to detect anthropogenic terrain anomalies. In this study, we systematically investigated different influencing factors on UAV-LiDAR data acquisition. The flight parameters speed and altitude above ground were systematically varied. In addition, different vegetation cover and seasonal acquisition times were compared, and we evaluated three different types of filter algorithms to separate ground from non-ground. It could be seen from our experiments that for the detection of subsurface anomalies in treeless open terrain, higher flight speeds like 6m/s were feasible. Regarding the flight altitude, we recommend an altitude of 50–75m above ground. At higher flight altitudes of 100–120m above ground, there is the risk that terrain characteristics smaller than 50cm will be missed. Areas covered with deciduous forest should only be surveyed during leaf-off season. In the presence of low-level vegetation (small bushes and shrubs with a height of up to 2m), it turned out that the morphological filter was the most suitable. In tree-covered areas with total absence of near ground vegetation, however, the choice of filter algorithm plays only a subordinate role, especially during winter where the resulting ground point densities have a percentage deviation of less than 6% from each other.

Reclaimed Mine Sites: Forests and Plant Diversity

The relationship between vegetation and selected soil characteristics in different monoculture forest types was investigated as part of a landscape restoration project after brown coal mining. Six forest types were selected: alder (Alnus sp.), spruce (Picea sp.), pine (Pinus sp.), larch (Larix sp.), long-term deciduous forest (Quercus robur, Tilia sp.), and forest created by spontaneous succession. These stands were classified into two age categories (younger and older). The soil attributes, C/N, TC, TN, pH, and A horizon depth were assessed. The observed species were categorized into functional groups by life history, life forms according to Raunkiær, and affinity to the forest environment. C/N ratio, humus thickness, and canopy cover were the main soil parameters affecting plant communities. The highest C/N values were recorded in Pinus and Larix stands, which were significantly different from deciduous and succession stands. The highest diversity index was noted in younger stands of Alnus and the lowest in younger stands of Picea. Intermediate values of the diversity index were achieved in successional stands at both age levels and in Larix and Alnus stands. The species belonging to a functional group was not an important factor in these habitat types. The species composition and vegetation change over time in the Alnus, long-life deciduous, and Larix stands show that these species are more suitable for forestry reclamation than spruce or pine. The study also emphasizes the great value of spontaneous succession areas as full-fledged alternatives to forestry reclamation.