Earth Observation and Climate Processes (EOCP) – Evaluating the Feasibility of Sentinel-2 Data for Drought Stress Detection in Urban Trees Max Gerhards1*, Henning Buddenbaum1, Jessica Friedrichs1, Christian Lindner2 and Frank Knospe2 1 Earth Observation and Climate Processes, Trier University, 54286 Germany 2 Stadt Essen, Amt für Geoinformation, Vermessung und Kataster, Lindenallee 10, 45127 Essen, Germany ‚TreeCop‘: a Pilot Project Urban areas are highly vulnerable to heatwaves, which have direct negative effects on human health and well-being. Urban green and in particular urban trees provide crucial ecosystem services (i.e., shade and cooling, etc.). These services mitigate the negative effects associated with climate change, and thus contribute to the quality of life in our cities and comply with several sustainable development goals (e.g., SDG 3 – good health and well-being, SDG 6 – clean water, SDG 11 – sustainable cities and communities). However, urban trees are also exposed to climate change- related increases in drought stress and tree dieback as a result of heatwaves, leading to a reduction in their ability to provide ecosystem services. Therefore, early detection of drought-stressed trees, in the context of a healthy urban climate and increased climate resilience of cities, is particularly important to ensure the preservation and function of urban greenery through targeted irrigation of stressed trees while conserving drinking water resources. ‘TreeCop’, as a pilot project, evaluates the potential Sentinel-2 imagery for drought monitoring in the city of Essen. Over 40 (rising) in-situ sensors (Fig. 3, left) measuring soil moisture provide a unique validation basis. Examinations on the interactions between Sentinel-2 imagery and in-situ sensors forms a solid base for the development of an optimized small- scale irrigation management system (Fig. 2). First results are very promising: Sentinel-2 data were processed with FORCE on CODE-DE (Fig. 1), areas of potential drought stress could be revealed (Fig. 3, right) and a dashboard containing all in-situ meas. was implemented (Fig. 4). However, various difficulties have been identified that need to be addressed. For example, only mild stress symptoms were observed remotely, since urban trees are well adapted to their habitat and no drought stress occurred in 2021. Luckily ‘TreeCop’ was extended until end of 2022 to study another vegetation period with more and new sensors at non-disturbed locations (i.e., forests) to better understand the correlations between Sentinel-2 imagery and in-situ sensors. References Frantz, D. 2019. Remote Sensing 11 (9): 1124. https://doi.org/10.3390/rs11091124. Funding: Deutsches Zentrum für Luft- und Raumfahrt (DLR), Raumfahrtmanagement mit Mitteln des Bundesministeriums für Verkehr und digitale Infrastruktur (BMVI), FKZ: 50EW2010 A & 50EW2010 B Contact: gerhardsm@uni-trier.de, https://www.uni-trier.de/?id=74823 Figure 4: Dashboard containing all in-situ soil moisture measurements and showing their temporal course. 2020-09-19 2020-09-19 Figure 3: ARD Sentinel-2 image Essen with locations of in-situ sensors (left), MSI-difference image (right) – the darker the larger the difference to a non-stressed reference date. Brownish areas indicate potential drought stress. Blue areas are not threatened. Non-vegetated areas are displayed in RGB. in-situ sensors CODE-DE: Analysis Ready Data We utilized FORCE (Framework for Operational Radiometric Correction for Environmental monitoring: Frantz 2019) - an in-house software package designed for mass-processing satellite image archives such as the Sentinel- 2 data stream from the European Copernicus Program as it is available in CODE-DE. A data cube of analysis-ready data (ARD) was created (Fig. 1), holding atmospherically and topographically corrected surface reflectance datasets as nadir BRDF-adjusted bottom-of-atmosphere reflectance (BOA). The reflectance data are accompanied by per-pixel quality inform