Wu, SongjunTetzlaff, DoertheDaempfling, HaukeSoulsby, Chris2023-11-062023-11-062023-09-13Wu, S, Tetzlaff, D, Daempfling, H & Soulsby, C 2023, 'Improved understanding of vegetation dynamics and wetland ecohydrology via monthly UAV-based classification', Hydrological Processes, vol. 37, no. 9, e14988. https://doi.org/10.1002/hyp.149880885-6087https://hdl.handle.net/2164/22121Funding Information: Songjun Wu was funded by the Chinese Scholarship Council (CSC). Tetzlaff's contribution was partly funded through the Einstein Research Unit “Climate and Water under Change” from the Einstein Foundation Berlin and Berlin University Alliance (grant no. ERU‐2020‐609). Contributions from Soulsby were supported by the Leverhulme Trust through the ISO‐LAND project (grant no. RPG 2018 375). We also thank colleagues from the Finck Foundation ( www.finck-stiftung.org ) Benedict Boesel and Max Kuester for the trustful collaboration and for providing access to the study sites. Open Access funding enabled and organized by Projekt DEAL. Publisher Copyright: © 2023 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.167115622engecohydrologyremote sensed vegetation dynamicssoil moistureUAVunmanned aerial vehicleswetlandsTC Hydraulic engineering. Ocean engineeringGE Environmental SciencesWater Science and TechnologyTCGEJournal article10.1002/hyp.14988https://www.scopus.com/pages/publications/85170650239