A full-view scenario model for urban waterlogging response in a big data environment

The emergence of big data is breaking the spatial and time limitations of urban waterlogging scenario description. The scenario data of different dimensions (e.g., administrative levels, sectors, granularities, and time) have become highly integrated. Accordingly, a structural and systematic model i...

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Autores principales:	Liu Zhao-ge, Li Xiang-yang, Zhu Xiao-han
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	big data urban waterlogging scenario-based analysis full-view model scenario model Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/275e57ed114d403097ad913ae69038ea
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id	oai:doaj.org-article:275e57ed114d403097ad913ae69038ea
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spelling	oai:doaj.org-article:275e57ed114d403097ad913ae69038ea2021-12-05T14:10:49ZA full-view scenario model for urban waterlogging response in a big data environment2391-544710.1515/geo-2020-0317https://doaj.org/article/275e57ed114d403097ad913ae69038ea2021-11-01T00:00:00Zhttps://doi.org/10.1515/geo-2020-0317https://doaj.org/toc/2391-5447The emergence of big data is breaking the spatial and time limitations of urban waterlogging scenario description. The scenario data of different dimensions (e.g., administrative levels, sectors, granularities, and time) have become highly integrated. Accordingly, a structural and systematic model is needed to represent waterlogging scenarios for more efficient waterlogging response decision-making. In this article, a full-view urban waterlogging scenario is first defined and described from four dimensions. Next a structured representation of scenario element is given based on knowledge unit method. The full-view scenario model is then constructed by extracting the scenario correlation structures between different dimensions (called scenario nesting), i.e., inheritance nesting, feedback nesting, aggregation nesting, and selection nesting. Finally, a real-world case study in Wuhan East Lake High-tech Development Zone, China is evaluated to verify the reasonability of the full-view model. The results show that the proposed model effectively integrates scenario data from different dimensions, which helps generate the complete key scenario information for urban waterlogging decision-making. The full-view scenario model is expected to be applicable for other disasters under big data environment.Liu Zhao-geLi Xiang-yangZhu Xiao-hanDe Gruyterarticlebig dataurban waterloggingscenario-based analysisfull-view modelscenario modelGeologyQE1-996.5ENOpen Geosciences, Vol 13, Iss 1, Pp 1432-1447 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	big data urban waterlogging scenario-based analysis full-view model scenario model Geology QE1-996.5
spellingShingle	big data urban waterlogging scenario-based analysis full-view model scenario model Geology QE1-996.5 Liu Zhao-ge Li Xiang-yang Zhu Xiao-han A full-view scenario model for urban waterlogging response in a big data environment
description	The emergence of big data is breaking the spatial and time limitations of urban waterlogging scenario description. The scenario data of different dimensions (e.g., administrative levels, sectors, granularities, and time) have become highly integrated. Accordingly, a structural and systematic model is needed to represent waterlogging scenarios for more efficient waterlogging response decision-making. In this article, a full-view urban waterlogging scenario is first defined and described from four dimensions. Next a structured representation of scenario element is given based on knowledge unit method. The full-view scenario model is then constructed by extracting the scenario correlation structures between different dimensions (called scenario nesting), i.e., inheritance nesting, feedback nesting, aggregation nesting, and selection nesting. Finally, a real-world case study in Wuhan East Lake High-tech Development Zone, China is evaluated to verify the reasonability of the full-view model. The results show that the proposed model effectively integrates scenario data from different dimensions, which helps generate the complete key scenario information for urban waterlogging decision-making. The full-view scenario model is expected to be applicable for other disasters under big data environment.
format	article
author	Liu Zhao-ge Li Xiang-yang Zhu Xiao-han
author_facet	Liu Zhao-ge Li Xiang-yang Zhu Xiao-han
author_sort	Liu Zhao-ge
title	A full-view scenario model for urban waterlogging response in a big data environment
title_short	A full-view scenario model for urban waterlogging response in a big data environment
title_full	A full-view scenario model for urban waterlogging response in a big data environment
title_fullStr	A full-view scenario model for urban waterlogging response in a big data environment
title_full_unstemmed	A full-view scenario model for urban waterlogging response in a big data environment
title_sort	full-view scenario model for urban waterlogging response in a big data environment
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/275e57ed114d403097ad913ae69038ea
work_keys_str_mv	AT liuzhaoge afullviewscenariomodelforurbanwaterloggingresponseinabigdataenvironment AT lixiangyang afullviewscenariomodelforurbanwaterloggingresponseinabigdataenvironment AT zhuxiaohan afullviewscenariomodelforurbanwaterloggingresponseinabigdataenvironment AT liuzhaoge fullviewscenariomodelforurbanwaterloggingresponseinabigdataenvironment AT lixiangyang fullviewscenariomodelforurbanwaterloggingresponseinabigdataenvironment AT zhuxiaohan fullviewscenariomodelforurbanwaterloggingresponseinabigdataenvironment
_version_	1718371709539581952

A full-view scenario model for urban waterlogging response in a big data environment

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