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Large-scale and fine-grained mapping of heathland habitats using open-source remote sensing data / Laurence Hubert-Moy in Remote Sensing in Ecology and Conservation, vol. 8, n°4 (Année 2022)  

Public [article]  inRemote Sensing in Ecology and Conservation > vol. 8, n°4 (Année 2022) . - pp. 448-463 Titre : Large-scale and fine-grained mapping of heathland habitats using open-source remote sensing data Type de document : texte imprimé Auteurs : Laurence Hubert-Moy, Auteur ; Clémence Rozo, Auteur ; Gwenhael Perrin, Auteur ; Frédéric Bioret, Auteur ; Sébastien Rapinel, Auteur Année de publication : 2022 Article en page(s) : pp. 448-463 Langues : Français (fre) Catégories : [ZG] France [ZG] Massif armoricain [habitats/milieux] 3 - Landes, fruticées et prairies [Thèmes] Cartographie des habitats [Thèmes] Télédétection Résumé : "Mapping natural habitats remains challenging, especially at a national scale. Although new open-access variables for vegetation and its environment and increased spatial resolution derived from satellite remote sensing data are available at the global scale, the relevance of these new variables for fine-grained mapping of natural habitats at a national scale remains underexplored. This study aimed to map the fine-grained pattern of four heathland habitats throughout France (550 000 km2). Environmental (bioclimatic, soil and topographic) and spectral (vegetation) variables derived from MODerate resolution Imaging Spectroradiometer, Advanced Spaceborne Thermal Emission and Reflection Radiometer, and Sentinel-2 satellite data were analyzed using the MaxEnt classifier. Open-access field databases were used to calibrate and validate the classification, based on the threshold-independent area under the curve (AUC) index and the conventional F1-score. For each heathland habitat, potential and actual areas were mapped using environmental and spectral variables, respectively. The results showed high classification accuracy for potential (AUC 0.92–0.99) and actual (AUC 0.88–0.99) suitability maps of the four heathland habitats. Visual interpretation of maps of the probability of occurrence indicated that the fine-grained distribution of heathland habitat was detected satisfactorily. However, although the accuracy of the crisp map of combined classifications of actual heathland habitats was high (overall accuracy 0.72), estimated producer's accuracies in terms of proportion of area were low (<0.25). This study provides the first fine-grained pattern maps of heathland habitats at a national scale, thus highlighting the value of combining environmental and spectral variables derived from open-remote sensing data and open-source field databases. These suitability maps could support the identification of heathland habitats in the framework of national conservation policies." (source : auteurs) Type de publication : périodique Référence biblio : Hubert-Moy L., Rozo C., Perrin G., Bioret F., Rapinel S., 2022 - Large-scale and fine-grained mapping of heathland habitats using open-source remote sensing data. Remote Sensing in Ecology and Conservation, 8 (4) : 448-463. ID PMB : 71402 En ligne : https://zslpublications.onlinelibrary.wiley.com/doi/full/10.1002/rse2.253 Format de la ressource électronique : document Permalink : http://www.cbnbrest.fr/catalogue_en_ligne/index.php?lvl=notice_display&id=71402 [article]

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