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Estimating the impacts of proximity to public transportation on residential property values: An empirical analysis for Hartford and Stamford areas, Connecticut / Bo Zhang in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 2 (February 2021) . - n° 44 Titre : Estimating the impacts of proximity to public transportation on residential property values: An empirical analysis for Hartford and Stamford areas, Connecticut Type de document : Article/Communication Auteurs : Bo Zhang, Auteur ; Weidong Li, Auteur ; Nicholas Lownes, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de la valeur [Termes descripteurs IGN] bien immobilier [Termes descripteurs IGN] Connecticut (Etats-Unis) [Termes descripteurs IGN] logement [Termes descripteurs IGN] régression des moindres carrés partiels [Termes descripteurs IGN] régression géographiquement pondérée [Termes descripteurs IGN] transport public [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Public transit infrastructure may increase residential property values by improving accessibility and reducing commute expenses in urban areas. Prior studies have investigated the impacts of the proximity to public transportation on property values and obtained mixed conclusions. Many of these studies were focused on one transit mode for a single city. In this study, a hedonic pricing model is constructed to investigate the impacts of commuter rail/Bus Rapid Transit (BRT) and bus lines separately in two different areas: the Stamford area (Stamford–Darien–New Canaan) and the Hartford area (Hartford–West Hartford–East Hartford), Connecticut. Comparison of the results from Ordinary Least Square and Geographically Weighted Regression (GWR) indicates that estimation accuracy can be improved by considering local variation. Results from GWR show that impacts of proximity to bus and rail/BRT on property values vary spatially in the Hartford area. Negative impacts of bus stops are found in downtown Hartford and positive impacts in the west and east sides of Hartford. Impacts from rail/BRT are relatively minor compared with bus lines, partly due to the relatively recent launching of the BRT and Hartford rail line. In contrast, most properties in the Stamford area show appreciation towards rail service and depreciation to bus service. This study reveals the roles of different public transit systems in affecting residential property values. It also provides empirical evidence for future transit-oriented development in this region for uplifting the real estate market. Numéro de notice : A2021-154 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10020044 date de publication en ligne : 20/01/2021 En ligne : https://doi.org/10.3390/ijgi10020044 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97065 [article]

Knowledge-guided consistent correlation analysis of multimode landslide monitoring data / Shuangxi Miao in International journal of geographical information science IJGIS, vol 31 n° 11-12 (November - December 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 11-12 (November - December 2017) . - pp 2255 - 2271 Titre : Knowledge-guided consistent correlation analysis of multimode landslide monitoring data Type de document : Article/Communication Auteurs : Shuangxi Miao, Auteur ; Qing Zhu, Auteur ; Bo Zhang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 2255 - 2271 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] base de connaissances [Termes descripteurs IGN] Chensi (Chine) [Termes descripteurs IGN] corrélation [Termes descripteurs IGN] données multisources [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] structure géologique [Termes descripteurs IGN] surveillance géologique Résumé : (Auteur) A novel method called knowledge-guided spatio-temporal consistent correlation analysis (KSTCCA) was developed to discover reliable deformation features induced by multiple factors based on multimode landslide monitoring data. Compared to conventional approaches, KSTCCA integrates both temporal and spatial correlation analysis to improve the consistency of deformation patterns and capture the spatio-temporal heterogeneities in multimode monitoring data. KSTCCA considers both the landslide deformation mechanisms and the relationships between different influential factors as knowledge. Moreover, the method extracts the morphological structures of monitoring curves based on a seven-point approach and identifies knowledge rules using the k-means clustering method. Under the guidance of prior knowledge, a spatial correlation analysis is conducted based on support vector regression, and a temporal correlation analysis of the time lag is carried out based on the morphological structure features. Finally, three kinds of typical monitoring data, including deformation, rainfall, and reservoir water level data collected in the Baishuihe landslide area, China, are used for experimental analysis to verify the validity of the proposed method. Numéro de notice : A2017-700 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1356461 En ligne : https://doi.org/10.1080/13658816.2017.1356461 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88081 [article]

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