Artificial intelligence algorithms in flood prediction: a general overview

M Pandey - Geo-information for Disaster Monitoring and …, 2024 - Springer
This paper presents a comprehensive general overview of the extensive literature available
in the field of application of artificial intelligence (AI) in flood prediction. The initial approach …

Multi-criteria analysis and geospatial applications-based mapping flood vulnerable areas: a case study from the eastern Mediterranean

HG Abdo, T Zeng, MJ Alshayeb, P Prasad… - Natural Hazards, 2024 - Springer
Floods are considered one of the most common natural hazards in the Eastern
Mediterranean. In western Syria, floods annually cause dozens of casualties with massive …

[HTML][HTML] Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean

S Mohammed, S Arshad, B Bashir, B Ata… - Journal of …, 2024 - Elsevier
Soil salinization is a critical global issue for sustainable agriculture, impacting crop yields
and posing a threat to achieving the Sustainable Development Goal (SDG) of ensuring food …

Using Public Landslide Inventories for Landslide Susceptibility Assessment at the Basin Scale: Application to the Torto River Basin (Central-Northern Sicily, Italy)

C Martinello, C Mercurio, C Cappadonia, V Bellomo… - Applied Sciences, 2023 - mdpi.com
In statistical landslide susceptibility evaluation, the quality of the model and its prediction
image heavily depends on the quality of the landslide inventories used for calibration …

[HTML][HTML] Application of machine learning in the assessment of landslide susceptibility: a case study of mountainous eastern Mediterranean region, Syria

HG Abdo, SM Richi - Journal of King Saud University-Science, 2024 - Elsevier
Landslide is a considerable geomorphological risk in terrain systems worldwide. Advanced
techniques present a unique tool for predicting landslide susceptibility with unbiased and …

Soil erosion sensitivity and prediction for hilly areas of Hubei Province, China, using combined RUSLE and LSTM models

Y Ping, P Tian, L Luo, Y Guo, Y Gong, Z Zhu… - Journal of Soils and …, 2024 - Springer
Purpose Hilly areas are highly susceptible to soil erosion. This study aims to discover the
drivers of soil erosion, identify soil erosion–sensitive areas, and predict future soil erosion in …