Détail de l'auteur
Auteur Hei Gao |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externes
Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning / Jiayu Wu in Computers, Environment and Urban Systems, vol 91 (January 2022)
[article]
Titre : Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning Type de document : Article/Communication Auteurs : Jiayu Wu, Auteur ; Yutian Lu, Auteur ; Hei Gao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101716 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] Chine
[Termes IGN] conservation du patrimoine
[Termes IGN] distribution spatiale
[Termes IGN] données massives
[Termes IGN] échantillonnage de données
[Termes IGN] Extreme Gradient Machine
[Termes IGN] morphologie urbaine
[Termes IGN] patrimoine culturel
[Termes IGN] planification urbaine
[Termes IGN] point d'intérêt
[Termes IGN] régularisation de Tychonoff
[Termes IGN] variation diurneRésumé : (auteur) The conservation of historical heritage can bring social benefits to cities by promoting community economic development and societal creativity. In the early stages of historical heritage conservation, the focus was on the museum-style concept for individual structures. At present, heritage area vitality is often adopted as a general conservation method to increase the vibrancy of such areas. However, it remains unclear whether urban morphological elements suitable for urban areas can be applied to heritage areas. This study uses ridge regression and LightGBM with multi-source big geospatial data to explore whether urban morphological elements that affect the vitality of heritage and urban areas are consistent or have different spatial distributions and daily variations. From a sample of 12 Chinese cities, our analysis shows the following results. First, factors affecting urban vitality differ from those influencing heritage areas. Second, factors influencing urban and heritage areas' vitality have diurnal variations and differ across cities. The overarching contribution of this study is to propose a quantitative and replicable framework for heritage adaptation, combining urban morphology and vitality measures derived from big geospatial data. This study also extends the understanding of forms of heritage areas and provides theoretical support for heritage conservation, urban construction, and economic development. Numéro de notice : A2022-007 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101716 Date de publication en ligne : 30/09/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101716 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99048
in Computers, Environment and Urban Systems > vol 91 (January 2022) . - n° 101716[article]