Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.3390/w15081532
Lizenz creative commons licence
Titel (primär) Mapping specific constituents of an ochre-coloured watercourse based on in situ and airborne hyperspectral remote sensing data
Autor Ulrich, C.; Hupfer, M.; Schwefel, R.; Bannehr, L.; Lausch, A.
Quelle Water
Erscheinungsjahr 2023
Department CLE
Band/Volume 15
Heft 8
Seite von art. 1532
Sprache englisch
Topic T5 Future Landscapes
Keywords remote sensing; hyperspectral data; RGB; in situ; ochre-coloured rivers; pyrite weathering; water constituents; water quality
Abstract It is a well-known fact that water bodies are crucial for human life, ecosystems and biodiversity. Therefore, they are subject to regulatory monitoring in terms of water quality. However, land-use intensification, such as open-cast mining activities, can have a direct impact on water quality. Unfortunately, in situ measurements of water quality parameters are spatially limited, costly and time-consuming, which is why we proposed a combination of hyperspectral data, in situ data and simple regression models in this study to estimate and thus monitor various water quality parameters. We focused on the variables of total iron, ferrous iron, ferric iron, sulphate and chlorophyll-a. Unlike other studies, we used a combination of airborne hyperspectral and RGB data to ensure a very high spatial resolution of the data. To investigate the potential of our approach, we conducted simultaneous in situ measurements and airborne hyperspectral/RGB aircraft campaigns at different sites of the Spree River in Germany to monitor the impact of pyrite weathering on water bodies after open-cast mining activities. Appropriate regression models were developed to estimate the five variables mentioned above. The model with the best performance for each variable gave a coefficient of determination R2 of 64% to 79%. This clearly shows the potential of airborne hyperspectral/RGB data for water quality monitoring. In further investigations, we focused on the use of machine learning techniques, as well as transferability to other water bodies. The approach presented here has great potential for the development of a monitoring method for the continuous monitoring of still waters and large watercourses, especially given the freely available space-based hyperspectral missions via EnMAP.
dauerhafte UFZ-Verlinkung
Ulrich, C., Hupfer, M., Schwefel, R., Bannehr, L., Lausch, A. (2023):
Mapping specific constituents of an ochre-coloured watercourse based on in situ and airborne hyperspectral remote sensing data
Water 15 (8), art. 1532 10.3390/w15081532