Zięba-Kulawik, KarolinaHawryło, PawełWężyk, PiotrMatczak, PiotrPrzewoźna, PatrycjaInglot, AdamMączka, Krzysztof2023-08-182023-08-182021-05Urban Forestry & Urban Greening 2021, Vol. 63; 127195.https://hdl.handle.net/10593/27345In this paper we propose a methodology for combining remotely sensed data with field measurements to assess selected tree parameters (diameter at breast height (DBH) and tree species) required by the i-Tree Eco model to estimate ecosystem services (ES) provided by urban trees. We determined values of ES provided by trees in 2017 in Racibórz (a city in South Poland) and estimated the loss of ES from January 1, 2017 to March 5, 2017, a period of changing legislation that temporarily allowed removal of trees on private property without any permission from city authorities. We applied Canopy Height Models (CHM; GSD 1.0 m) generated from two sets of ALS LiDAR point clouds (acquisitions on June 11, 2011 and March 5, 2017) and performed tree crown segmentations using the GEOBIA approach. Physical attributes were estimated for each tree using predictive models, developed based on field tree inventory . The reference areas for parameterizing the segmentation algorithm and assessing tree species composition were established in Racibórz, while reference data required for assessment of DBH were obtained from the MONIT-AIR project (from Municipality of Kraków). We found that in 2017, 988.79 ha of Racibórz (13.2 % of city area) was covered by the crowns of 264 471 trees, providing ES structural values worth over 384 mil €. The structural value of ES lost in the first months of 2017 (during which 5 075 trees were removed) was about 3.5 mil €. We concluded that in the face of information on tree crown cover that is often missing from city databases, tree inventories require application of a combination of multi-source and multi-resolution spatial analyses, including: administrative decisions for tree removal with exact location, predictive modelling of selected biometrical tree information, automatic crown segmentation on CHM and interpretation of regularly updated color infrared (CIR) aerial orthophotos.enecosystem servicesGEOBIAi-Tree EcoLiDARpredictive modelsurban forestsinfo:eu-repo/semantics/articlehttps://doi.org/10.1016/j.ufug.2021.127195