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Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale / Elena Barbierato in European journal of remote sensing, sans n° (2019)  

Public [article]  inEuropean journal of remote sensing > sans n° (2019) . - 11 p. Titre : Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale Type de document : Article/Communication Auteurs : Elena Barbierato, Auteur ; Iacopo Bernetti, Auteur ; Irene Capecchi, Auteur ; Claudio Saragosa, Auteur Année de publication : 2019 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] climat urbain [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] flore urbaine [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] Toscane (Italie) Résumé : (auteur) The climate of a city influences the ways in which its outdoor spaces are used. Especially, public spaces intended for use by pedestrians and cyclists, such as parks, squares, residential and commercial streets, and foot and cycle paths will be used and enjoyed more frequently if they have a comfortable and healthy climate. Due to the predicted global temperature increase, urban climate is likely to become more uncomfortable, especially in summer when an increase in heat stress is expected. Urban forestry has been proposed as one approach for mitigating the human health consequences of increased temperature resulting from climate change. The aims of the current research were to (a) provide a transferable methodology useful for analyzing the effect of urban trees on surface temperature reduction, particularly in public spaces, and (b) provide high-resolution urban mapping for adaptation strategies to climate change based on green space projects. To achieve the established aims, we developed a methodology that uses multisource data: LiDAR data, high-resolution Landsat imagery, global climate model data from CMIP5 (IPPC Fifth Assessment), and data from meteorological stations. The proposed model can be a useful tool for validating the efficiency of design simulations of new green spaces for temperature mitigation. Numéro de notice : A2019-320 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2019.1646104 date de publication en ligne : 29/07/2019 En ligne : https://doi.org/10.1080/22797254.2019.1646104 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93266 [article]