Contribution and behavioral assessment of physical and anthropogenic factors for soil erosion using integrated deep learning and game theory

IA Ahmed, S Talukdar, ARMT Islam, M Rihan… - Journal of Cleaner …, 2023 - Elsevier
Ensuring sustainable management of soil erosion is of utmost importance to prevent its
adverse effects. Unfortunately, this issue has received limited attention in the past, therefore …

Performance comparison of landslide susceptibility mapping under multiple machine-learning based models considering InSAR deformation: a case study of the …

J Yao, X Yao, Z Zhao, X Liu - Geomatics, Natural Hazards and Risk, 2023 - Taylor & Francis
Landslide susceptibility mapping (LSM) comprehensively evaluates the spatial probability of
landslide occurrence by using different environmental factors. However, most of the …

[HTML][HTML] Examining the spatially varying relationships between landslide susceptibility and conditioning factors using a geographical random forest approach: A case …

X Dai, Y Zhu, K Sun, Q Zou, S Zhao, W Li, L Hu… - Remote Sensing, 2023 - mdpi.com
Landslide susceptibility assessment is an important means of helping to reduce and
manage landslide risk. The existing studies, however, fail to examine the spatially varying …

Assessing effectiveness of a dual-barrier system for mitigating granular flow hazards through DEM-DNN framework

Y Cui, J Fang, Y Li, H Liu - Engineering Geology, 2022 - Elsevier
Constructing multiple-barrier systems is efficient in mitigating flow-like geological hazards
and potentially serves as an optimal solution to protect the heavily threatened …

Bivariate landslide susceptibility analysis: clarification, optimization, open software, and preliminary comparison

L Li, H Lan - Remote Sensing, 2023 - mdpi.com
Bivariate data-driven methods have been widely used in landslide susceptibility analysis.
However, the names, principles, and correlations of bivariate methods are still confused. In …

[HTML][HTML] Landslide identification and gradation method based on statistical analysis and spatial cluster analysis

H Dai, H Zhang, H Dai, C Wang, W Tang, L Zou… - Remote Sensing, 2022 - mdpi.com
As a type of earth observation technology, interferometric synthetic aperture radar (InSAR) is
increasingly widely used in the field of geological disaster detection. However, the …

Improving landslide prediction by computer vision and deep learning

B Guerrero-Rodriguez… - Integrated …, 2023 - journals.sagepub.com
The destructive power of a landslide can seriously affect human beings and infrastructures.
The prediction of this phenomenon is of great interest; however, it is a complex task in which …

Susceptibility Analysis of Glacier Debris Flow Based on Remote Sensing Imagery and Deep Learning: A Case Study along the G318 Linzhi Section

J Chen, H Gao, L Han, R Yu, G Mei - Sensors, 2023 - mdpi.com
Glacial debris flow is a common natural disaster, and its frequency has been increasing in
recent years due to the continuous retreat of glaciers caused by global warming. To reduce …

Formation mechanism and evolution of the Jiaju landslide in the Dadu River, China

Y Bai, Y Tie, J Wang, X Xiong, H Ge - Bulletin of Engineering Geology and …, 2024 - Springer
The Jiaju landslide is a large soil‒rock palaeolandslide in the Danba section of the Upper
Dadu River in southwestern Sichuan Province, China. In this work, geological investigations …

Long-term prediction for railway track geometry based on an optimised DNN method

L Han, Y Liao, H Wang, H Zhang - Construction and Building Materials, 2023 - Elsevier
Railway transportation becomes increasingly important due to the rapidly emerging needs of
global trade, environmental protection, and high oil costs. Thus, railway infrastructure …