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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, vol 52 n° 4 (2019)  

Public [article]  inEuropean journal of remote sensing > vol 52 n° 4 (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 IGN] arbre urbain [Termes IGN] changement climatique [Termes IGN] climat urbain [Termes IGN] couvert végétal [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] données météorologiques [Termes IGN] flore urbaine [Termes IGN] ilot thermique urbain [Termes IGN] image Landsat-8 [Termes IGN] image thermique [Termes IGN] température au sol [Termes 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]