Physical- and Social-Based Rain Gauges—A Case Study on Urban Flood Detection
Floods are among the most frequent and costly rainfall-triggered disasters. In this context, geospatial content generated by non-professionals using geolocated systems offers the possibility of monitoring environmental events. This study shows a statistical correlation between in situsensors, radar,...
| Autores: | , , , , , , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2023 |
| País: | Brasil |
| Recursos: | Universidade Estadual Paulista (UNESP) |
| Repositório: | Repositório Institucional da UNESP |
| Idioma: | inglês |
| OAI Identifier: | oai:repositorio.unesp.br:11449/247273 |
| Acesso em linha: | http://dx.doi.org/10.3390/geosciences13040111 http://hdl.handle.net/11449/247273 |
| Access Level: | Acceso aberto |
| Palavra-chave: | floods rain gauge VGI weather radar |
| Resumo: | Floods are among the most frequent and costly rainfall-triggered disasters. In this context, geospatial content generated by non-professionals using geolocated systems offers the possibility of monitoring environmental events. This study shows a statistical correlation between in situsensors, radar, Twitter posts, and flooding events. Furthermore, we observed in this study that flooding-related keywords are statistically more significant on flooding days than on non-flooding days and reinforce that Twitter can be employed as a complementary data source for flood management systems. |
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