{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:04:08Z","timestamp":1760144648210,"version":"build-2065373602"},"reference-count":61,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T00:00:00Z","timestamp":1715212800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Alexander von Humboldt Foundation"},{"name":"HIT-Umweltstiftung"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Water surface roughness (SR) is a highly relevant parameter governing data reliability in remote sensing applications, yet lacking appropriate methodology in riverine habitats. In order to assess thermal accuracy linked to SR of thermal imaging derived from an unmanned aerial vehicle (UAV), we developed the SR Measurement Device (SRMD). The SRMD uses the concept of in situ quantification of wave frequency and wave amplitude. Data of nine installed SRMDs in four different fluvial mesohabitat classes presented a range of 0 to 47 waves per 30 s and an amplitude range of 0 to 6 cm. Even subtle differences between mesohabitat classes run, riffle, and no-\/low-flow still and pool areas could be detected with the SRMD. However, SR revealed no significant influence on the accuracy of thermal infrared (TIR) imagery data in our study case. Overall, the presented device expands existing methods of riverine habitat assessments and has the potential to produce highly relevant data of SR for various ecological and technical applications, ranging from remote sensing of surface water and habitat quality characterizations to bank stability and erosion risk assessments.<\/jats:p>","DOI":"10.3390\/rs16101674","type":"journal-article","created":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T05:16:45Z","timestamp":1715231805000},"page":"1674","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Determining Riverine Surface Roughness at Fluvial Mesohabitat Level and Its Influence on UAV-Based Thermal Imaging Accuracy"],"prefix":"10.3390","volume":"16","author":[{"given":"Johannes","family":"Kuhn","sequence":"first","affiliation":[{"name":"Aquatic Systems Biology Unit, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8322-9374","authenticated-orcid":false,"given":"Joachim","family":"Pander","sequence":"additional","affiliation":[{"name":"Aquatic Systems Biology Unit, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1465-4888","authenticated-orcid":false,"given":"Luis","family":"Habersetzer","sequence":"additional","affiliation":[{"name":"Department of Fish Ecology and Evolution, Eawag (Swiss Federal Institute of Aquatic Science and Technology), 6047 Kastanienbaum, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7139-8859","authenticated-orcid":false,"given":"Roser","family":"Casas-Mulet","sequence":"additional","affiliation":[{"name":"Chair of Hydraulic Engineering, TUM School of Engineering and Design, Technical University of Munich, 80333 Munich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7698-3443","authenticated-orcid":false,"given":"Juergen","family":"Geist","sequence":"additional","affiliation":[{"name":"Aquatic Systems Biology Unit, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,9]]},"reference":[{"key":"ref_1","unstructured":"IPCC (2023). 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