A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Geostatistical strategy to build spatial coastal-flooding models
The intensification of flooding events and the management of ecosystems became global issues. The combination of statistical modelling techniques and geospatial analysis represents a promising strategy to provide a holistic representation of the systems. This paper aimed to develop a strategy to build Spatial Coastal-Flooding Models based on evidence of flooding points and environmental and artificial characteristics of the area. The procedure combines statistical techniques, such as PCA, Cluster analysis, ANOVA, OLS regression, and geospatial data obtained from open databases. The geostatistical strategy was applied in Florianópolis city – Brazil. 108 photographic records of flooding were inventoried. The OLS regression analysis constructed three Spatial Coastal-Flooding Models considering eight factors. The analysis specifies the ability of models to explain the flooding in C1, C2, and C3 sub-regions through calculus (76, 68, and 40%). The results find that relationships between environmental and artificial variables and flooding events are not homogeneous over space.
Geostatistical strategy to build spatial coastal-flooding models
The intensification of flooding events and the management of ecosystems became global issues. The combination of statistical modelling techniques and geospatial analysis represents a promising strategy to provide a holistic representation of the systems. This paper aimed to develop a strategy to build Spatial Coastal-Flooding Models based on evidence of flooding points and environmental and artificial characteristics of the area. The procedure combines statistical techniques, such as PCA, Cluster analysis, ANOVA, OLS regression, and geospatial data obtained from open databases. The geostatistical strategy was applied in Florianópolis city – Brazil. 108 photographic records of flooding were inventoried. The OLS regression analysis constructed three Spatial Coastal-Flooding Models considering eight factors. The analysis specifies the ability of models to explain the flooding in C1, C2, and C3 sub-regions through calculus (76, 68, and 40%). The results find that relationships between environmental and artificial variables and flooding events are not homogeneous over space.
Geostatistical strategy to build spatial coastal-flooding models
Caprario, Jakcemara (author) / Azevedo, Larissa Thainá Schmitt (author) / Santana, Paula Lidia (author) / Wu, Fernando Kit (author) / Uda, Patrícia Kazue (author) / Finotti, Alexandra Rodrigues (author)
Urban Water Journal ; 19 ; 395-409
2022-04-21
15 pages
Article (Journal)
Electronic Resource
Unknown
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