<p>A small area of county Ludwigsburg, Marbach, was visualized with 3D buildings and satellite map. The red area represents area with very long biomass density, either with buildings, roads or water bodies. Each polygon has homogeneous density over all area because a polygon is assumed to be covered by one type of crop. Except for red build-up area, road and river, the only vegetation cover land type is farming land in this map. Different colours represent different biomass potential brought by different crop types.</p>
<p>The detailed descripotion and findings of this workflow can be find in the following two open-sourced papers, which are funded by IN-Source project.</p>
<li>Bao, K.; Padsala, R.; Coors, V.; Thrän, D.; Schröter, B. A Method for Assessing Regional Bioenergy Potentials Based on GIS Data and a Dynamic Yield Simulation Model. Energies 2020, 13, 6488. DOI: https://doi.org/10.3390/en13246488 </li>
<li>Bao K, Padsala R, Coors V, Thrään D, Schröter B (2020): GIS-Based Assessment of Regional Biomass Potentials at the Example of Two Counties in Germany. In European Biomass Conference and Exhibition Proceedings, pp. 77–85. DOI: 10.5071/28thEUBCE2020-1CV.4.15.</li>
<li>Bao, K.; Padsala, R.; Coors, V.; Thrän, D.; Schröter, B. A Method for Assessing Regional Bioenergy Potentials Based on GIS Data and a Dynamic Yield Simulation Model. Energies 2020, 13, 6488. DOI: https://doi.org/10.3390/en13246488 </li>
<li>Bao K, Padsala R, Coors V, Thrän D, Schröter B (2020): GIS-Based Assessment of Regional Biomass Potentials at the Example of Two Counties in Germany. In European Biomass Conference and Exhibition Proceedings, pp. 77–85. DOI: 10.5071/28thEUBCE2020-1CV.4.15.</li>
