Machine learning in environmental research: common pitfalls and best practices

JJ Zhu, M Yang, ZJ Ren - Environmental Science & Technology, 2023 - ACS Publications
Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …

Flood hazard map** methods: A review

RB Mudashiru, N Sabtu, I Abustan, W Balogun - Journal of hydrology, 2021 - Elsevier
Flood hazard map** (FHM) has undergone significant development in terms of approach
and capacity of the result to meet the target of policymakers for accurate prediction and …

XGBoost-based method for flash flood risk assessment

M Ma, G Zhao, B He, Q Li, H Dong, S Wang, Z Wang - Journal of Hydrology, 2021 - Elsevier
Flash flood risk assessment, a widely applied technology in preventing catastrophic flash
flood disasters, has become the current research hotspot. However, most existing machine …

[HTML][HTML] Evaluating urban flood risk using hybrid method of TOPSIS and machine learning

E Rafiei-Sardooi, A Azareh, B Choubin… - International Journal of …, 2021 - Elsevier
With the growth of cities, urban flooding has increasingly become an issue for regional and
national governments. The destructive effects of floods are magnified in cities. Accurate …

Land use/land cover prediction and analysis of the middle reaches of the Yangtze River under different scenarios

S Zhang, P Yang, J ** based on social media data in Chengdu city, China
Y Li, FB Osei, T Hu, A Stein - Sustainable Cities and Society, 2023 - Elsevier
Increase in urban flood hazards has become a major threat to cities, causing considerable
losses of life and in the economy. To improve pre-disaster strategies and to mitigate …