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• W4362671020 abstract "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." @default.
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• W4362671020 date "2023-04-06" @default.
• W4362671020 modified "2023-10-12" @default.
• W4362671020 title "Physical- and Social-Based Rain Gauges—A Case Study on Urban Flood Detection" @default.
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• W4362671020 doi "https://doi.org/10.3390/geosciences13040111" @default.
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