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A thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding / Mohammad Khalid Hossain in Computers, Environment and Urban Systems, vol 79 (January 2020)  

Public [article]  inComputers, Environment and Urban Systems > vol 79 (January 2020) Titre : A thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding Type de document : Article/Communication Auteurs : Mohammad Khalid Hossain, Auteur ; Qingmin Meng, Auteur Année de publication : 2020 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Alabama (Etats-Unis) [Termes IGN] aléa [Termes IGN] approche hiérarchique [Termes IGN] cartographie des risques [Termes IGN] catastrophe naturelle [Termes IGN] données socio-économiques [Termes IGN] ethnographie [Termes IGN] inondation [Termes IGN] risque naturel [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité [Termes IGN] zone inondable [Termes IGN] zone urbaine Résumé : (Auteur) About 30% of the total global economic loss inflicted by natural hazards is caused by flooding. Among them, the most serious situation is urban flooding. Urban impervious surface enhances storm runoff and overwhelms the drainage capacity of the storm sewer system, while the urban socioeconomic characteristics most often exacerbate them even more vulnerable to urban flooding impacts. Currently, there is still a significant knowledge gap of comparable assessment and understanding of minority's and non-minority's vulnerability. Therefore, this study designs a quantitative thematic mapping method–location quotient (LQ), using Birmingham, Alabama, USA as the study area. Urban residents' vulnerability to flooding is then analyzed demographically using LQ with census data. Comparing with the widely used social vulnerability index (SVI), LQ is more robust, which not only provides more detailed measurements of both the minority's and the White's vulnerability, but also shows a direct comparison for all populations with finer information about their potential spatial risk assessment. Although SVI showed the Shades Creek is the most vulnerable area with a SVI value above 0.75, only 228 Hispanic people and 2290 African-American live there that is not a significant aggregation of minorities in Birmingham; however, a total White population 12,872 is identified by LQ with a significant aggregation in the Shades Creek. Overall, LQ suggests that the White populations are highly and significantly concentrated in the flood areas, while SVI never considered the White as vulnerable. LQ further indicates that the concentration of minorities (i.e., 88,895) and vulnerable houses (i.e., 26,235) are much higher compared to the numbers of the minorities and houses indicated by SVI, which are only 11,772 and 8323, respectively. The LQ based thematic mapping, as a promising method for vulnerability assessment of urban hazards and risks, can make a significant contribution to hazard management efforts to reduce urban vulnerability and hence enhance urban resilience to hazards in the future. Numéro de notice : A2020-002 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2019.101417 Date de publication en ligne : 14/09/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101417 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93621 [article]

Assessment of regression kriging for spatial interpolation: comparisons of seven GIS interpolation methods / Qingmin Meng in Cartography and Geographic Information Science, vol 40 n° 1 (January 2013)  

Public [article]  inCartography and Geographic Information Science > vol 40 n° 1 (January 2013) . - pp 28 - 39 Titre : Assessment of regression kriging for spatial interpolation: comparisons of seven GIS interpolation methods Type de document : Article/Communication Auteurs : Qingmin Meng, Auteur ; Zhijun Liu, Auteur ; Bruce E. Borders, Auteur Année de publication : 2013 Article en page(s) : pp 28 - 39 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] analyse comparative [Termes IGN] interpolation spatiale [Termes IGN] krigeage [Termes IGN] lissage de données [Termes IGN] régression [Termes IGN] système d'information géographique Résumé : (Auteur) As an important GIS function, spatial interpolation is one of the most often used geographic techniques for spatial query, spatial data visualization, and spatial decision-making processes in GIS and environmental science. However, less attention has been paid on the comparisons of available spatial interpolation methods, although a number of GIS models including inverse distance weighting, spline, radial basis functions, and the typical geostatistical models (i.e. ordinary kriging, universal kriging, and cokriging) are already incorporated in GIS software packages. In this research, the conceptual and methodological aspects of regression kriging and GIS built-in interpolation models and their interpolation performance are compared and evaluated. Regression kriging is the combination of multivariate regression and kriging. It takes into consideration the spatial autocorrelation of the variable of interest, the correlation between the variable of interest and auxiliary variables (e.g., remotely sensed images are often relatively easy to obtain as auxiliary variables), and the unbiased spatial estimation with minimized variance. To assess the efficiency of regression kriging and the difference between stochastic and deterministic interpolation methods, three case studies with strong, medium, and weak correlation between the response and auxiliary variables are compared to assess interpolation performances. Results indicate that regression kriging has the potential to significantly improve spatial prediction accuracy even when using a weakly correlated auxiliary variable. Numéro de notice : A2013-741 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/15230406.2013.762138 En ligne : https://doi.org/10.1080/15230406.2013.762138 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32877 [article]

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