Spatial Mapping of Flood Susceptibility Using Decision Tree–Based Machine Learning Models for the Vembanad Lake System in Kerala, India-Reference-Cited by-同舟云学术

Spatial Mapping of Flood Susceptibility Using Decision Tree–Based Machine Learning Models for the Vembanad Lake System in Kerala, India

Published:2023-10 Issue:10 Volume:149 Page:
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Kulithalai Shiyam Sundar Parthasarathy¹^ORCID,Kundapura Subrahmanya²^ORCID

Affiliation:

1. Research Scholar, Dept. of Water Resources and Ocean Engineering, National Institute of Technology Karnataka, Mangaluru 575 025, India (corresponding author). ORCID: .

2. Assistant Professor, Faculty of Water Resources Engineering, Dept. of Water Resources and Ocean Engineering, National Institute of Technology Karnataka, Mangaluru 575 025, India. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JWRMD5.WRENG-5858

Reference117 articles.

1. Financial adaptation to disaster risk in the European Union

2. Flash-flood susceptibility mapping based on XGBoost, random forest and boosted regression trees

3. Assessment of land use and land cover change detection and prediction using remote sensing and CA Markov in the northern coastal districts of Tamil Nadu, India

4. Assessing the impact of damage and government response toward the cyclone Gaja in Tamil Nadu, India

5. GIS-based multi-criteria analysis for identification of potential groundwater recharge zones - a case study from Ponnaniyaru watershed, Tamil Nadu, India

Cited by 8 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. Reviewing Flood Susceptibility Mapping Utilizing Machine Learning: Insights and Prospects for Future Research;2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2024-06-05

2. Flood susceptibility mapping leveraging open-source remote-sensing data and machine learning approaches in Nam Ngum River Basin (NNRB), Lao PDR;Geomatics, Natural Hazards and Risk;2024-05-28

3. Evaluation of urban flood susceptibility through integrated Bivariate statistics and Geospatial technology;Environmental Monitoring and Assessment;2024-05-09

4. Spatio-temporal classification of land use and land cover and its changes in Kerala using remote sensing and machine learning approach;Environmental Monitoring and Assessment;2024-04-18

5. Integration of machine learning and hydrodynamic modeling to solve the extrapolation problem in flood depth estimation;Journal of Water and Climate Change;2023-12-09