Leveraging machine learning and open-source spatial datasets to enhance flood susceptibility mapping in transboundary river basin-Reference-Cited by-同舟云学术

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Leveraging machine learning and open-source spatial datasets to enhance flood susceptibility mapping in transboundary river basin

Published:2024-02-09 Issue:1 Volume:17 Page:
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Bhattarai Yogesh¹^ORCID,Duwal Sunil¹^ORCID,Sharma Sanjib²^ORCID,Talchabhadel Rocky³^ORCID

Affiliation:

1. Department of Civil Engineering, Khwopa College of Engineering, Bhaktapur, Nepal

2. Department of Civil and Environmental Engineering, Howard University, Washington, DC, USA

3. Department of Civil and Environmental Engineering, Jackson State University, MS, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2313857

Reference92 articles.

1. When the river talks to its people: Local knowledge-based flood forecasting in Gandak River basin, India

2. Flooding and Inundation in Nepal Terai: Issues and Concerns

3. Evaluation of flood susceptibility prediction based on a resampling method using machine learning

4. GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and logistic regression: A case of Topľa basin, Slovakia

5. Integration of hard and soft supervised machine learning for flood susceptibility mapping

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2. A detection method for multi-type earth's surface anomalies based on multi-dimensional feature space;International Journal of Digital Earth;2024-08-30

3. Robustness of machine learning algorithms to generate flood susceptibility maps for watersheds in Jordan;Geomatics, Natural Hazards and Risk;2024-07-20

4. Urban inundation mapping by coupling 1D − 2D models and model comparison;International Journal of Applied Earth Observation and Geoinformation;2024-06

5. Harnessing multisatellite remote sensing data and machine learning for flood risk assessment in Nam Ngum River Basin, Lao PDR;SPIE Future Sensing Technologies 2024;2024-05-28

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