Müller, SönkeSteensen, TorgeBüscher, OlafJandewerth, MichaelGómez, Jorge MarxSonnenschein, MichaelVogel, UteWinter, AndreasRapp, BarbaraGiesen, Nils2019-09-162019-09-162014https://dl.gi.de/handle/20.500.12116/25788Achieving a fossil-resources-free power supply requires an exploration of alternative, renewable energy sources. Over the last years, biomass has become an important component of this endeavour and its consumption is rising steadily. Common sources of biomass are agricultural production and forestry but the production of these sources is stagnating due to limited space. To explore new sources of biomass, for example in the field of landscape conservation, the location and available amount of biomass must be obtained. Normally, there are no reliable data sources that give information about the objects of interest like hedges and vegetation along streets, railways, rivers and field margins. There is a great demand for an inventory of these biomass sources which could be answered by applying remote sensing technology. To generate that kind of spatial information, satellite imagery is used in combination with areawide available GIS and elevation data. The multispectral satellite images are assumed to have a low spatial resolution of 10-20 m and spectral bands corresponding to the Sentinel-2 spatial and spectral configurations. For GIS data, the German Digital Landscape Model (ATKIS Base-DLM), containing roads, field boundaries and waterways, supports the mapping allowing for deduction of potential biomass objects located beside GIS objects. To allow a quantitative estimation of the biomass volume, a digital surface model (DSM), produced from raw LIDAR data, is utilized.Text/Conference Paper