| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Robust quantification of riverine land cover dynamics by high-resolution remote sensing |
| Autor/-in: | Milani, Gillian Volpi, Michele Tonolla, Diego Döring, Michael Robinson, Christopher T. Kneubühler, Mathias Schaepman, Michael |
| DOI: | 10.1016/j.rse.2018.08.035 |
| Erschienen in: | Remote Sensing of Environment |
| Band(Heft): | 217 |
| Seite(n): | 491 |
| Seiten bis: | 505 |
| Erscheinungsdatum: | 2018 |
| Verlag / Hrsg. Institution: | Elsevier |
| ISSN: | 0034-4257 |
| Sprache: | Englisch |
| Schlagwörter: | Rmote Sensing; Floodplain |
| Fachgebiet (DDC): | 333.7: Landflächen, Naturerholungsgebiete 577: Ökologie |
| Zusammenfassung: | Floodplain areas belong to the most diverse, dynamic and complex ecological habitats of the terrestrial portion of the Earth. Spatial and temporal quantification of floodplain dynamics is needed for assessing the impacts of hydromorphological controls on river ecosystems. However, estimation of land cover dynamics in a post-classification setting is hindered by a high contribution of classification errors. A possible solution relies on the selection of specific information of the change map, instead of increasing the overall classification accuracy. In this study, we analyze the capabilities of Unmanned Aerial Systems (UAS), the associated classification processes and their respective accuracies to extract a robust estimate of floodplain dynamics. We show that an estimation of dynamics should be built on specific land cover interfaces to be robust against classification errors and should include specific features depending on the season-sensor coupling. We use five different sets of features and determine the optimal combination to use information largely based on blue and infrared bands with the support of texture and point cloud metrics at leaf-off conditions. In this post-classification setting, the best observation of dynamics can be achieved by focusing on the gravel-water interface. The semi-supervised approach generated error of 10% of observed changes along highly dynamic reaches using these two land cover classes. The results show that a robust quantification of floodplain land cover dynamics can be achieved by high-resolution remote sensing. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/10531 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | Life Sciences und Facility Management |
| Organisationseinheit: | Institut für Umwelt und Natürliche Ressourcen (IUNR) |
| Enthalten in den Sammlungen: | Publikationen Life Sciences und Facility Management |
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Milani, G., Volpi, M., Tonolla, D., Döring, M., Robinson, C. T., Kneubühler, M., & Schaepman, M. (2018). Robust quantification of riverine land cover dynamics by high-resolution remote sensing. Remote Sensing of Environment, 217, 491–505. https://doi.org/10.1016/j.rse.2018.08.035
Milani, G. et al. (2018) ‘Robust quantification of riverine land cover dynamics by high-resolution remote sensing’, Remote Sensing of Environment, 217, pp. 491–505. Available at: https://doi.org/10.1016/j.rse.2018.08.035.
G. Milani et al., “Robust quantification of riverine land cover dynamics by high-resolution remote sensing,” Remote Sensing of Environment, vol. 217, pp. 491–505, 2018, doi: 10.1016/j.rse.2018.08.035.
MILANI, Gillian, Michele VOLPI, Diego TONOLLA, Michael DÖRING, Christopher T. ROBINSON, Mathias KNEUBÜHLER und Michael SCHAEPMAN, 2018. Robust quantification of riverine land cover dynamics by high-resolution remote sensing. Remote Sensing of Environment. 2018. Bd. 217, S. 491–505. DOI 10.1016/j.rse.2018.08.035
Milani, Gillian, Michele Volpi, Diego Tonolla, Michael Döring, Christopher T. Robinson, Mathias Kneubühler, and Michael Schaepman. 2018. “Robust Quantification of Riverine Land Cover Dynamics by High-Resolution Remote Sensing.” Remote Sensing of Environment 217: 491–505. https://doi.org/10.1016/j.rse.2018.08.035.
Milani, Gillian, et al. “Robust Quantification of Riverine Land Cover Dynamics by High-Resolution Remote Sensing.” Remote Sensing of Environment, vol. 217, 2018, pp. 491–505, https://doi.org/10.1016/j.rse.2018.08.035.
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