[HTML][HTML] Multi-hazard susceptibility mapping based on Convolutional Neural Networks

K Ullah, Y Wang, Z Fang, L Wang, M Rahman - Geoscience Frontiers, 2022 - Elsevier
Multi-hazard susceptibility prediction is an important component of disasters risk
management plan. An effective multi-hazard risk mitigation strategy includes assessing …

Debris flow susceptibility evaluation—a review

A Kumar, R Sarkar - Iranian Journal of Science and Technology …, 2023 - Springer
Debris flows are the most dangerous geological hazard in steep terrain. For systematic
debris flow mitigation and management, debris flow evaluation is required. Over the past few …

A multi-step hazard assessment for debris-flow prone areas influenced by hydroclimatic events

V Cabral, F Reis, V Veloso, A Ogura, C Zarfl - Engineering Geology, 2023 - Elsevier
Hazard assessment studies are fundamental to identifying disaster-prone areas, especially
in locations with high environmental and socioeconomic vulnerability. This study proposes a …

Influence of human activity on landslide susceptibility development in the Three Gorges area

Y Li, X Wang, H Mao - Natural Hazards, 2020 - Springer
Human activities are important factors that trigger frequent occurrences of landslides; thus,
for landslide control, it is critical to determine the influence of human activity on landslide …

Risk assessment of debris flow along the northern line of the Sichuan-Tibet highway

Y Sun, Y Ge, X Chen, L Zeng… - … , Natural Hazards and Risk, 2023 - Taylor & Francis
Debris flow occurs frequently in mountainous areas due to the special geographical and
geological environment, causing significant damage to linear infrastructure. However, a …

Debris flow susceptibility zonation using statistical models in parts of Northwest Indian Himalayas—implementation, validation, and comparative evaluation

RK Dash, PO Falae, DP Kanungo - Natural Hazards, 2022 - Springer
Debris flows are natural disasters with devastating consequences and frequent recurrence
in changing climatic regime of the Indian Himalayas. Therefore, it is necessary to delineate …

Analysis of land use/land cover change (LULCC) and debris flow risks in Adama district, Ethiopia, aided by numerical simulation and deep learning-based remote …

AK Bojer, ME Ahmed, DJ Bekalo, TG Debelee… - … Research and Risk …, 2023 - Springer
Detecting land use/land cover change (LULCC) and assessing the risk of slope failure and
debris flow has been a worldwide concern. This study is the first in Adama District, Ethiopia …

Model performance analysis for landslide susceptibility in cold regions using accuracy rate and fluctuation characteristics

Q Liu, D Huang, A Tang, X Han - Natural Hazards, 2021 - Springer
Considering the increasing number of landslides due to permafrost degradation, this paper
reports a performance evaluation of three classical landslide susceptibility models applied to …

Debris flow susceptibility assessment and runout prediction: A case study in Shiyang Gully, Beijing, China

Y Li, J Chen, Y Zhang, S Song, X Han… - International Journal of …, 2020 - Springer
Abstract At 14: 00 on 18 June 2017, floods occurred in Shiyang gully at the junction of
Beijing and Hebei Province, China. The floods put 12 people at risk, 6 of whom died. After …

CCP-federated deep learning based on user trust chain in social IoV

PC Zhao, YH Huang, DX Zhang, L Xing, HH Wu… - Wireless …, 2023 - Springer
Federated learning is widely used in the context of wireless networks to protect sensitive
user data. However, centralized federated learning encounters some issues when applied to …