Remote sensing in ecology and conservation / Zoological Society of London (Royaume-Uni) . vol 7 n° 2Paru le : 01/06/2021 |
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Ajouter le résultat dans votre panierDiscovery of new colonies by Sentinel2 reveals good and bad news for emperor penguins / Peter T. Fretwell in Remote sensing in ecology and conservation, vol 7 n° 2 (June 2021)
[article]
Titre : Discovery of new colonies by Sentinel2 reveals good and bad news for emperor penguins Type de document : Article/Communication Auteurs : Peter T. Fretwell, Auteur ; Philip N. Trathan, Auteur Année de publication : 2021 Article en page(s) : pp 139 - 153 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Antarctique
[Termes IGN] Aves
[Termes IGN] image Sentinel-MSIMots-clés libres : manchot empereur Aptenodytes forsteri Résumé : (auteur) The distribution of emperor penguins is circumpolar, with 54 colony locations currently reported of which 50 are currently extant as of 2019. Here we report on eight newly discovered colonies and confirm the rediscovery of three breeding sites, only previously reported in the era before Very High Resolution satellite imagery was available, making a total of 61 breeding locations. This represents an increase of ~20% in the number of breeding sites, but, as most of the colonies appear to be small, they may only increase the total population by around 5–10%. The discoveries have been facilitated by the use of Sentinel2 satellite imagery, which has a higher resolution and more efficient search mechanism than the Landsat data previously used to search for colonies. The small size of these new colonies indicates that considerations of reproductive output in relation to metabolic rate during huddling is likely to be of interest. Some of the colonies exist in offshore habitats, something not previously reported for emperor penguins. Comparison with recent modelling results show that the geographic locations of all the newly found colonies are in areas likely to be highly vulnerable under business-as-usual greenhouse gas emissions scenarios, suggesting that population decreases for the species will be greater than previously thought. Numéro de notice : A2021-732 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1002/rse2.176 Date de publication en ligne : 04/08/2020 En ligne : https://doi.org/10.1002/rse2.176 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98678
in Remote sensing in ecology and conservation > vol 7 n° 2 (June 2021) . - pp 139 - 153[article]Cloud-native seascape mapping of Mozambique’s Quirimbas National Park with Sentinel-2 / Dimitris Poursanidis in Remote sensing in ecology and conservation, vol 7 n° 2 (June 2021)
[article]
Titre : Cloud-native seascape mapping of Mozambique’s Quirimbas National Park with Sentinel-2 Type de document : Article/Communication Auteurs : Dimitris Poursanidis, Auteur ; Dimosthenis Traganos, Auteur ; Luisa Teixeira, Auteur ; Aurélie Shapiro, Auteur ; Lara Muaves, Auteur Année de publication : 2021 Article en page(s) : pp 275 - 291 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] classification et arbre de régression
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] écosystème
[Termes IGN] Google Earth Engine
[Termes IGN] habitat (nature)
[Termes IGN] image Sentinel-MSI
[Termes IGN] Mozambique
[Termes IGN] récif corallien
[Termes IGN] réserve naturelle
[Termes IGN] surveillance écologiqueRésumé : (auteur) The lack of detailed spatial information on coastal resources, notably shallow water coral reefs and associated benthic habitats, impedes our ability to protect and manage them in the face of global climate change and anthropogenic impacts. Here, we develop a semi-automated workflow in the cloud that uses freely available Sentinel-2 data from the European Space Agency (ESA) Copernicus programme to derive information on near-shore coral reef habitats in the Quirimbas National Park (QNP), a recently declared biosphere reserve in northern Mozambique. We use an end-to-end cloud-based framework within the Google Earth Engine cloud geospatial platform to process imagery from raw pixels to cloud-free composites which are corrected for glint and surface artefacts, water column and derived estimated depth and then classified into four benthic habitats. Using independent training and validation data, we apply three supervised classification algorithms: random forests (RF), support vector machine (SVM) and classification and regression trees (CART). Our results show that random forests are the most accurate supervised algorithm with over 82% overall accuracy. We mapped over 105 000 ha of shallow water habitat inside the protected area, of which 18% are dominated by coral and hardbottom; 27.5% are seagrass and submerged aquatic vegetation and another 23.4% are soft and sandy substrates, and the remaining area is optically deep water. We employ satellite-derived bathymetry to assess slope, bathymetric position, rugosity and underwater topography of these habitats. Finally, a spectral unmixing model provides further sub-pixel–level information of habitats with the potential to monitor changes over time. This effort provides the first, consistent and repeatable and also scalable coastal information system for an east African tropical marine protected area, which hosts shallow-water ecosystems which are of great significance to local communities and building resilience towards climate change. Numéro de notice : A2021-733 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1002/rse2.187 Date de publication en ligne : 29/11/2020 En ligne : https://doi.org/10.1002/rse2.187 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98679
in Remote sensing in ecology and conservation > vol 7 n° 2 (June 2021) . - pp 275 - 291[article]