Automatic detection of actual water depth of urban floods from social media images-Reference-Cited by-同舟云学术

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Automatic detection of actual water depth of urban floods from social media images

Published:2023-07 Issue: Volume:216 Page:112891
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Li Jingru,Cai Ruying,Tan Yi,Zhou Haijun,Sadick Abdul-Manan,Shou Wenchi,Wang Xiaoling

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference42 articles.

1. Spatial and temporal changes of meteorological disasters in China during 1950–2013;Guan;Nat. Hazards,2015

2. Water level prediction from social media images with a multi-task ranking approach;Chaudhary;ISPRS J. Photogramm. Remote Sens.,2020

3. Review and prospect of the emergency management of urban rainstorm waterlogging based on big data fusion;Wu;Chin. Sci. Bull.,2017

4. Social media as an information source for rapid flood inundation mapping;Fohringer;Nat. Hazards Earth Syst. Sci.,2015

5. Assessing the utility of social media as a data source for flood risk management using a real-time modelling framework;Smith;J. Flood Risk Manage.,2017

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1. The Causes of Waterlogging in Chinese Southern Hilly Cities Based on Hydrological Processes;Sustainability;2024-09-07

2. State-of-the-Art Techniques for Real-Time Monitoring of Urban Flooding: A Review;Water;2024-08-30

3. Automatic detection of urban flood level with YOLOv8 using flooded vehicle dataset;Journal of Hydrology;2024-08

4. Automated floodwater depth estimation using large multimodal model for rapid flood mapping;Computational Urban Science;2024-05-27

5. GPT, large language models (LLMs) and generative artificial intelligence (GAI) models in geospatial science: a systematic review;International Journal of Digital Earth;2024-05-20

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