Mapping Trees Outside Forests Using Semantic Segmentation

Trees Outside Forests (TOF) are an important part of landscapes and agroforestry systems, since they provide a variety of ecosystem services. They contribute to biomass and carbon stocks, support biodiversity conservation and enrich soil. This study investigates the potential of semantic segmentation to distinguish between Forest and the TOF classes Patch, Linear and Tree in aerial images. Information about these classes is crucial in order to understand their distribution and influence on the environment. An automated labeling approach with manual refinement is implemented for generating training and validation data. To map TOFs an adapted Pyramid Attention Network is trained. As this classification task is dependent on contextual information a spatial context postprocessing method is applied. The approach shows reliable results on independent validation data.