Beyond public inventories: Remote sensing–based assessment of urban tree ecosystem services

Abstract

Urban trees provide important ecosystem services (ESS), but their contributions are often undervalued and less acknowledged due to the complexity of quantifying them. Therefore, ESS assessment for urban trees at the individual tree level using ESS models is crucial for a more knowledge-based management of urban green spaces. In this study, we used very high-resolution aerial and satellite-based remote sensing imagery to derive the geospatial input for the CityTree model to estimate regulating ESS from over 160,000 individual trees in Munich, Germany. Our assessment includes both, trees on public and private land and enables fine-scale spatial modeling of eight ESS (carbon storage, carbon sequestration, CO2 sequestration, evapotranspiration of trees, runoff under the tree, transpiration, cooling by transpiration and shading). We found that public trees, especially those in recreational areas such as parks and woodlands, contribute largely to ESS provision. Private trees also play a meaningful role by contributing around one third of the total ESS. A statistical comparison with the tree inventory data revealed good agreement between the two datasets. However, we also found systematic measurement differences, possibly due to rounding in field measurements and limitations in remote sensing datasets. However, the size effect of these differences is small in practical terms, indicating that both data sources are comparable and complementary. Our findings support the use of remote sensing as a scalable, area-wide, consistent, and resource-efficient approach for urban ESS estimations.