Methodological approach for mapping the flood physical vulnerability index with geographical open-source data: an example in a small-middle city (Ponferrada, Spain) DOI Creative Commons

Laura Tascón-González,

Montserrat Ferrer‐Julià, Eduardo García‐Meléndez

и другие.

Natural Hazards, Год журнала: 2024, Номер 120(5), С. 4053 - 4081

Опубликована: Янв. 4, 2024

Abstract To increase the resilience of communities against floods, it is necessary to develop methodologies estimate vulnerability. The concept vulnerability multidimensional, but most flood studies have focused only on social approach. Nevertheless, in recent years, following seismic analysis, physical point view has increased its relevance. Therefore, present study proposes a methodology map and applies using an index at urban parcel scale for medium-sized town (Ponferrada, Spain). This based multiple indicators fed by geographical open-source data, once they been normalized combined with different weights extracted from Analytic Hierarchic Process. results show raster that facilitates future emergency risk management diminish potential damages. A total 22.7% parcels studied value higher than 0.4, which considered highly vulnerable. location these would passed unnoticed without use open governmental datasets, when average calculated overall municipality. Moreover, building percentage covered water was influential indicator area, where simulated generated alleged dam break. exceeds spatial constraints collecting this type data direct interviews inhabitants allows working larger areas, identifying buildings infrastructure differences among parcels.

Язык: Английский

Coverage and bias of street view imagery in mapping the urban environment DOI
Zicheng Fan, Chen‐Chieh Feng, Filip Biljecki

и другие.

Computers Environment and Urban Systems, Год журнала: 2025, Номер 117, С. 102253 - 102253

Опубликована: Янв. 23, 2025

Язык: Английский

Процитировано

2
Achieving fine-grained urban flood perception and spatio-temporal evolution analysis based on social media DOI
Zhiyu Yan, Xiaogang Guo, Zilong Zhao

и другие.

Sustainable Cities and Society, Год журнала: 2023, Номер 101, С. 105077 - 105077

Опубликована: Ноя. 21, 2023

Язык: Английский

Процитировано

39
Dynamic risk assessment of urban flood disasters based on functional area division—A case study in Shenzhen, China DOI
Ting Wang, Huimin Wang, Zhiqiang Wang

и другие.

Journal of Environmental Management, Год журнала: 2023, Номер 345, С. 118787 - 118787

Опубликована: Авг. 26, 2023

Язык: Английский

Процитировано

21
Flood vulnerability assessment of Thailand's flood-prone Pathum Thani province and vulnerability mitigation strategies DOI

Prinya Mruksirisuk,

Nawhath Thanvisitthpon,

Kewaree Pholkern

и другие.

Journal of Environmental Management, Год журнала: 2023, Номер 347, С. 119276 - 119276

Опубликована: Окт. 6, 2023

Язык: Английский

Процитировано

18
Boosting urban community resilience to multi-hazard scenarios in open spaces: A virtual reality – serious game training prototype for heat wave protection and earthquake response DOI Creative Commons
Mariella De Fino, Riccardo Tavolare, Gabriele Bernardini

и другие.

Sustainable Cities and Society, Год журнала: 2023, Номер 99, С. 104847 - 104847

Опубликована: Авг. 13, 2023

A key role in making cities resilient has been acknowledged raising risk preparedness and awareness of urban communities, by appropriate education communication strategies, which should rely on innovative pervasive tools. In this regard, an outstanding paradigm shift is driven the advancement Virtual Reality, can take advantage Serious Games, for helping individuals develop responsive behaviours case both slow sudden disasters and, thus, boosting effective human-urban-building interaction within a wider process safety sustainability. To end, paper proposes VR-SGs training prototype multi-hazard scenarios open spaces. The integrates results from phenomenological behavioural analyses applied to representative typologies built environment. demonstrated heat wave protection earthquake response through design implementation its functional features – virtual environment, mode, learning outcomes storyline informative contents, including simulation-based data surface temperatures, extent falling debris crowd motion. final goal validate reliable flexible tool view wide replication contexts instructing critical situations communicating mitigation strategies.

Язык: Английский

Процитировано

17
Auditing Flood Vulnerability Geo-Intelligence Workflow for Biases DOI Creative Commons
Brian K. Masinde, Caroline Gevaert, Michael Nagenborg

и другие.

ISPRS International Journal of Geo-Information, Год журнала: 2024, Номер 13(12), С. 419 - 419

Опубликована: Ноя. 21, 2024

Geodata, geographical information science (GISc), and GeoAI (geo-intelligence workflows) play an increasingly important role in predictive disaster risk reduction management (DRRM), aiding decision-makers determining where when to allocate resources. There have been discussions on the ethical pitfalls of these systems context DRRM because documented cases biases AI other socio-technical systems. However, none expound how audit geo-intelligence workflows for from data collection, processing, model development. This paper considers a case study that uses characterize housing stock vulnerability flooding Karonga district, Malawi. We use Friedman Nissenbaum’s definition categorization emphasize as negative undesirable outcome. limit scope affect visibility different typologies workflow. The results show introduces amplifies against houses certain materials. Hence, group within population area living would potentially miss out interventions. Based this example, we urge community researchers practitioners normalize auditing prevent disasters biases.

Язык: Английский

Процитировано

8
Data-driven urban waterlogging risk management approach considering efficiency-equity trade-offs and risk mitigation capability evaluation DOI

Ying'an Yuan,

Deyun Wang,

Ludan Zhang

и другие.

Journal of Hydrology, Год журнала: 2024, Номер 634, С. 131004 - 131004

Опубликована: Март 6, 2024

Язык: Английский

Процитировано

6
Association between multilevel landscape characteristics and rural sustainability: A case study of the water-net region in the Yangtze River Delta, China DOI Creative Commons
Chengyu Meng, Yimei Chen,

Jiexin Yang

и другие.

Ecological Informatics, Год журнала: 2024, Номер 82, С. 102677 - 102677

Опубликована: Июнь 12, 2024

In the Yangtze River Delta in China, known for its intricate water network, achieving harmonious development between humans and nature rural areas is imperative. However, identification of water-net landscape characteristics relationship sustainability these remain unclear. The aim this study was to bridge gap by proposing a novel framework investigating from typo-morphological perspective. Specifically, through regression analysis, influence multilevel spatial on selected as research focus. First, metrics were introduced delineate characteristics, including single multiple elements types, using deep learning methods achieve automatic classification. Subsequently, employing an improved entropy method, we comprehensively quantified indicators economic, social, ecological dimensions. Finally, ordinary least squares (OLS) model two variation coefficient models, namely, geographically weighted (GWR) multiscale (MGWR), used quantitatively analyze sustainability. Significant performances obtained with adjusted R2 values 0.33, 0.35, 0.4 at each characteristic level. GWR MGWR, which incorporated all metrics, 0.84 0.88, respectively. results demonstrate that highly depends proposed exhibits heterogeneity. findings improve our understanding provide important planning decision-making references sustainable areas.

Язык: Английский

Процитировано

6
Segmentation and Visualization of Flooded Areas Through Sentinel-1 Images and U-Net DOI Creative Commons
Fernando Pech May, Raúl Aquino-Santos, Omar Álvarez Cárdenas

и другие.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Год журнала: 2024, Номер 17, С. 8996 - 9008

Опубликована: Янв. 1, 2024

Floods are the most common phenomenon and cause significant economic social damage to population.They becoming more frequent dangerous.Consequently, it is necessary create strategies intervene effectively in mitigation resilience of affected areas.Different methods techniques have been developed mitigate caused by this phenomenon.Satellite programs provide a large amount data on Earth's surface, geospatial information processing tools help manage different natural disasters.Likewise, deep learning an approach capable forecasting time series that can be applied satellite images for flood prediction mapping.This paper presents segmentation visualization using U-Net architecture Sentinel-1 SAR imagery.The capture relevant features images.The comprises various phases, from loading preprocessing inference visualization.For study, georeferenced dataset Sen1Floods11 used train validate model through epochs training.A study area southeastern Mexico floods was chosen.The results demonstrate achieves high accuracy detecting flooded areas, with promising metrics regarding loss, precision, F1-score.

Язык: Английский

Процитировано

5
Assessing the social risks of flooding for coastal societies: a case study for Prince Edward Island, Canada DOI Creative Commons
Tianze Pang, Mohammad Aminur Rahman Shah, Quan Van Dau

и другие.

Environmental Research Communications, Год журнала: 2024, Номер 6(7), С. 075027 - 075027

Опубликована: Июль 1, 2024

Abstract With the worldwide growing threat of flooding, assessing flood risks for human societies and associated social vulnerability has become a necessary but challenging task. Earlier research indicates that islands usually face heightened due to higher population density, isolation, oceanic activities, while there is an existing lack experience in island-focused risk under complex interactions between geography socioeconomics. In this context, our study employs high-resolution hazard data principal component analysis (PCA) method comprehensively assess exposure Prince Edward Island (PEI), Canada, where limited been delivered on assessments. The findings reveal exposed populations are closely related distribution areas, with increasingly severe impact from current future climate conditions, especially island’s north shore. Exposed buildings exhibit concentrated at different levels community centers, change projected significantly worsen building compared population, possibly urban agglomeration effect. most populated cities towns show highest vulnerabilities PEI, results reflect relatively less economic structure islands. Recommendations management coming stage include necessity particular actions, recognizing centers as critical sites responses, incorporating hazards into planning mitigate impacts continuous urbanization ecosystem services prevention.

Язык: Английский

Процитировано

5