Estimating ecosystem services of urban trees based on remote sensing and in-situ measurements: A comparative study in Munich, Germany

Urban trees have proven an effective adaptation and mitigation strategy to attenuate the negative consequences of ongoing urbanization and climate change. However, area-wide data on trees in cities is still largely missing. Furthermore, ecosystem services of urban trees have only been quantified at the individual tree level for few selected trees within the urban forest to date. This study presents an integrative approach based on remote sensing for detection and characterization of urban trees, which serves as input for the modeling of ecosystem services using the process-based tree growth model "CityTree". In addition, the remote sensing-based parameter setting is compared to in-situ measurements to assess the plausibility of the ecosystem services estimation. The results show that tree dimensions from remote sensing generally agree well with in-situ measurements. Furthermore, the classification of tree genera based on multi-temporal very-high resolution (VHR) satellite data achieved good accuracies around 70%. Finally, this study demonstrates the effectiveness of remote sensing-based individual tree parameters for the estimation of ecosystem services, while the comparison with in-situ parameters confirmed the plausibility of the results.