Mapping potential, existing and efficient wetlands using free remote sensing data
| Autor: | Cendrine Mony, Elodie Fabre, Simon Dufour, Sébastien Rapinel, Damien Arvor, Laurence Hubert-Moy |
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| Přispěvatelé: | Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Littoral, Environnement, Télédétection, Géomatique (LETG - Rennes), Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université d'Angers (UA)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Brest (UBO)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Nantes (UN)-Université de Nantes (UN)-Université de Caen Normandie (UNICAEN), Université de Nantes (UN)-Université de Nantes (UN), Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES), Neurosurgery Research and Education Foundation, National Geographic Society Education Foundation, 2101606295, French Ministry of Ecology, Lucie Lecoq, Romain Georges, Bernard Clément, Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Normandie Université (NU)-Normandie Université (NU)-Université d'Angers (UA)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Brest (UBO)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN) |
| Rok vydání: | 2018 |
| Předmět: |
Environmental Engineering
Watershed Watershed area Climate Change 0208 environmental biotechnology Climate change Wetland 02 engineering and technology Land cover 010501 environmental sciences Management Monitoring Policy and Law 01 natural sciences Soil Wetland functions Humans Digital elevation model Sentinel Waste Management and Disposal ComputingMilieux_MISCELLANEOUS 0105 earth and related environmental sciences Remote sensing geography Lidar geography.geographical_feature_category General Medicine Vegetation [SHS.GEO]Humanities and Social Sciences/Geography 15. Life on land 020801 environmental engineering MODIS 13. Climate action Remote sensing (archaeology) Wetlands Remote Sensing Technology Environmental science Natural vegetations France Random forest Environmental Monitoring |
| Zdroj: | Journal of Environmental Management Journal of Environmental Management, Elsevier, 2019, 247, pp.829-839. ⟨10.1016/j.jenvman.2019.06.098⟩ Journal of Environmental Management, 2019, 247, pp.829-839. ⟨10.1016/j.jenvman.2019.06.098⟩ |
| ISSN: | 1095-8630 0301-4797 |
| DOI: | 10.1016/j.jenvman.2019.06.098⟩ |
| Popis: | Although wetlands remain threatened by human pressures and climate change, monitoring and managing them are challenging due to their high spatial and temporal dynamics within a fine-grained pattern. New satellite time-series at high temporal and spatial resolutions provide a promising opportunity to map and monitor wetlands. The objective of this study was to develop an operational method for managing valley bottom wetlands based on available free remote sensing data. The Potential, Existing, Efficient Wetlands (PEEW) approach was adapted to remote sensing data to delineate three wetland components: (1) potential wetlands, mapped from a digital terrain model derived from LiDAR data; (2) existing wetlands, delineated from land cover maps derived from Sentinel-1/2 time-series; and (3) efficient wetlands, identified from functional indicators (i.e. annual primary production, vegetation phenology, seasonality of carbon flux) derived from MODIS annual time-series. Soil and vegetation samples were collected in the field to calibrate and validate classification of remote sensing data. The method was applied to a 113 000 ha watershed in northwestern France. Results show that potential wetlands were successfully delineated (82% overall accuracy) and covered 21% of the watershed area, while 44% of existing wetlands had been lost. Small wetlands along headwater channels, which are considered as ordinary, cover 56% of wetland area in the watershed. Efficient wetlands were identified as contiguous pixels with a similar temporal functional trajectory. This method, based on free remote sensing data, provides a new perspective for wetland management. The method can identify sites where restoration measures should be prioritized and enables better understanding and monitoring of the influence of management practices and climate on wetland functions. |
| Databáze: | OpenAIRE |
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