Flood sequence mapping with multimodal remote sensing under the influence of dense vegetation-Reference-Cited by-同舟云学术

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Flood sequence mapping with multimodal remote sensing under the influence of dense vegetation

Published:2024-02-02 Issue:4 Volume:45 Page:1059-1078
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Li Zhouyayan¹²,Demir Ibrahim¹²³^ORCID

Affiliation:

1. Dept. of Civil and Environmental Engineering, University of Iowa, Iowa City, Iowa, USA

2. IIHR Hydroscience and Engineering, University of Iowa, Iowa City, Iowa, USA

3. Dept. of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2024.2305629

Reference67 articles.

1. Comparison of new generation low-complexity flood inundation mapping tools with a hydrodynamic model

2. Comprehensive flood vulnerability analysis in urban communities: Iowa case study

3. Flood mitigation data analytics and decision support framework: Iowa Middle Cedar Watershed case study

4. Social Media and Disasters: Highlighting Some Wicked Problems [Leading Edge]

5. Using machine learning models, remote sensing, and GIS to investigate the effects of changing climates and land uses on flood probability

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MultiRS flood mapper: a google earth engine application for water extent mapping with multimodal remote sensing and quantile-based postprocessing;Environmental Modelling & Software;2024-05

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