[HTML][HTML] Landslide susceptibility mapping using machine learning: A literature survey

M Ado, K Amitab, AK Maji, E Jasińska, R Gono… - Remote Sensing, 2022 - mdpi.com
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …

[HTML][HTML] Digital post-disaster risk management twinning: a review and improved conceptual framework

U Lagap, S Ghaffarian - International Journal of Disaster Risk Reduction, 2024 - Elsevier
Digital Twins (DT) is the real-time virtual representation of systems, communities, cities, or
even human beings with the substantial potential to revolutionize post-disaster risk …

Modeling landslide susceptibility based on convolutional neural network coupling with metaheuristic optimization algorithms

Z Chen, D Song - International Journal of Digital Earth, 2023 - Taylor & Francis
Landslides are one of the most common geological hazards worldwide, especially in
Sichuan Province (Southwest China). The current study's main purposes are to explore the …

A novel evolutionary combination of artificial intelligence algorithm and machine learning for landslide susceptibility mapping in the west of Iran

Y Shen, A Ahmadi Dehrashid, RA Bahar… - … Science and Pollution …, 2023 - Springer
Detecting and mapping landslides are crucial for effective risk management and planning.
With the great progress achieved in applying optimized and hybrid methods, it is necessary …

LogRF: An approach to human pose estimation using skeleton landmarks for physiotherapy fitness exercise correction

A Raza, AM Qadri, I Akhtar, NA Samee… - IEEE …, 2023 - ieeexplore.ieee.org
Human pose and gesture estimation are crucial in correcting physiotherapy fitness
exercises. In recent years, advancements in computer vision and machine learning …

Novel ensemble machine learning modeling approach for groundwater potential mapping in Parbhani District of Maharashtra, India

M Masroor, H Sajjad, P Kumar, TK Saha, MH Rahaman… - Water, 2023 - mdpi.com
Groundwater is an essential source of water especially in arid and semi-arid regions of the
world. The demand for water due to exponential increase in population has created stresses …

Modeling land use/cover change based on LCM model for a semi-arid area in the Latian Dam Watershed (Iran)

B Shafie, AH Javid, HI Behbahani, H Darabi… - Environmental Monitoring …, 2023 - Springer
The monitoring and modeling of changes, based on a time-series LULC approach, is
fundamental for planning and managing regional environments. The current study analyzed …

Assessing landscape ecological vulnerability to riverbank erosion in the Middle Brahmaputra floodplains of Assam, India using machine learning algorithms

N Bhuyan, H Sajjad, TK Saha, Y Sharma, M Masroor… - Catena, 2024 - Elsevier
Riverbank erosion is one of the most catastrophic hazards that renders floodplains
vulnerable across the world vulnerable. It creates a significant negative impact on the …

[HTML][HTML] Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania

DC Diaconu, R Costache, ARMT Islam… - Journal of Hydrology …, 2024 - Elsevier
Study region Prahova river basin located in the central-southern region of Romania. Study
focus This study aims to assess the susceptibility to flooding by using state-of-the-art …

An innovative method for landslide susceptibility mapping supported by fractal theory, GeoDetector, and random forest: a case study in Sichuan Province, SW China

Z Chen, D Song, L Dong - Natural Hazards, 2023 - Springer
Globally, but especially in Sichuan Province (Southwest China), landslides are considered
to be one of the most common geological hazards. The purpose of the current study is to …