Supply chain network design with financial considerations: A comprehensive review
Supply chain network design (SCND) is a large and growing area of research. Although
SCND has a remarkable effect on companies' main financial accounts, our examination …
SCND has a remarkable effect on companies' main financial accounts, our examination …
Can soil piping impact environment and society? Identifying new research gaps
A Bernatek‐Jakiel… - Earth Surface Processes …, 2023 - Wiley Online Library
Soil piping is a widespread, although often overlooked land degradation process. So far,
subsurface soil erosion studies have been focused on the importance of soil piping in …
subsurface soil erosion studies have been focused on the importance of soil piping in …
[HTML][HTML] Comparison of machine learning models for gully erosion susceptibility mapping
A Arabameri, W Chen, M Loche, X Zhao, Y Li… - Geoscience …, 2020 - Elsevier
Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory,
especially in the Northern provinces. A number of studies have been recently undertaken to …
especially in the Northern provinces. A number of studies have been recently undertaken to …
Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia
A quantitative understanding of the hydro-environmental factors that influence the
occurrence of agricultural drought events would enable more strategic climate change …
occurrence of agricultural drought events would enable more strategic climate change …
Land subsidence hazard modeling: Machine learning to identify predictors and the role of human activities
Land subsidence caused by land use change and overexploitation of groundwater is an
example of mismanagement of natural resources, yet subsidence remains difficult to predict …
example of mismanagement of natural resources, yet subsidence remains difficult to predict …
An ensemble approach of feature selection and machine learning models for regional landslide susceptibility mapping in the arid mountainous terrain of Southern …
This study evaluates the utility of the ensemble framework of feature selection and machine
learning (ML) models for regional landslide susceptibility mapping (LSM) in the arid climatic …
learning (ML) models for regional landslide susceptibility mapping (LSM) in the arid climatic …
Novel machine learning approaches for modelling the gully erosion susceptibility
A Arabameri, O Asadi Nalivan, S Chandra Pal… - Remote Sensing, 2020 - mdpi.com
The extreme form of land degradation caused by the formation of gullies is a major
challenge for the sustainability of land resources. This problem is more vulnerable in the arid …
challenge for the sustainability of land resources. This problem is more vulnerable in the arid …
Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates
Landslide susceptibility (LS) mapping is an essential tool for landslide risk assessment. This
study aimed to provide a new approach with better performance for landslide mapping and …
study aimed to provide a new approach with better performance for landslide mapping and …
Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region
Y Chen, W Chen, S Janizadeh, GS Bhunia… - Geocarto …, 2022 - Taylor & Francis
Piping erosion is one of the water erosions that cause significant changes in the landscape,
leading to environmental degradation. To prevent losses resulting from tube growth and …
leading to environmental degradation. To prevent losses resulting from tube growth and …
Performance evaluation for four GIS-based models purposed to predict and map landslide susceptibility: A case study at a World Heritage site in Southwest China
Landslide susceptibility mapping is a prerequisite for preventing and mitigating hazardous
risks, especially in landslide-prone mountainous areas. This study applies two well-known …
risks, especially in landslide-prone mountainous areas. This study applies two well-known …