- Fusion of LiDAR and UAV borne multispectral data to assess physiographic diversity of post-mining sites (Czech Science Foundation; 2017 – 2019).
The land affected by mining is a global issue and occupies about 1% of the global land. For effective management of the landscape data at high spatial and thematic resolution are necessary. Laser altimetry, commonly referred to as LiDAR, and multispectral/hyperspectral imaging are remote sensing technologies that have enabled measurement of ecosystems 3D structure with high accuracy. In this project, we will scan several spoil heaps using both technologies. First, we will classify land cover and calculate vertical and horizontal structure and terrain structural variables (e.g. canopy height, terrain roughness). Second, the effects of structural variables on dragonflies, frogs and bird diversity and distribution will be investigated.
The main goal of the project is to understand physiographic diversity of spoil heaps and to investigate the general hypothesis that variables derived from LiDAR and multispectral/hyperspectral data are important predictors of species diversity and distribution.
- Comparison of vegetation height derived from TanDEM-X DEM with reference Airborne Laser Scanning data for a mountainous areas in Czechia (German Aerospace Center; 2017 – 2018).
The objectives of this project are two folded. First, the provided dataset will be validated by comparison with various products based on ALS for the territory of Czechia. Secondly, the potential of the TanDEM-X DEM for derivation of meaningful parameters describing forest vegetation will be explored. Method: The quality of the final TanDEM-X DEM depends on terrain and vegetation characteristics. The quality of TanDEM-X DEM will be tested over vegetated and non-vegetated bare-earth terrain. In addition, we will examine associations between TanDEM-X DEM elevation error along with land-cover classes and terrain’s aspect and slope.