Measuring, modelling and managing gully erosion at large scales: A state of the art

M Vanmaercke, P Panagos, T Vanwalleghem… - Earth-Science …, 2021 - Elsevier
Soil erosion is generally recognized as the dominant process of land degradation. The
formation and expansion of gullies is often a highly significant process of soil erosion …

[HTML][HTML] Earth observation in the emmena region: Sco** review of current applications and knowledge gaps

M Eliades, S Michaelides, E Evagorou, K Fotiou… - Remote Sensing, 2023 - mdpi.com
Earth observation (EO) techniques have significantly evolved over time, covering a wide
range of applications in different domains. The scope of this study is to review the research …

A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran

A Arabameri, K Rezaei, A Cerdà, C Conoscenti… - Science of the Total …, 2019 - Elsevier
In north of Iran, flood is one of the most important natural hazards that annually inflict great
economic damages on humankind infrastructures and natural ecosystems. The Kiasar …

Landslide susceptibility evaluation and management using different machine learning methods in the Gallicash River Watershed, Iran

A Arabameri, S Saha, J Roy, W Chen, T Blaschke… - Remote Sensing, 2020 - mdpi.com
This analysis aims to generate landslide susceptibility maps (LSMs) using various machine
learning methods, namely random forest (RF), alternative decision tree (ADTree) and …

Assessment of the importance of gully erosion effective factors using Boruta algorithm and its spatial modeling and map** using three machine learning algorithms

M Amiri, HR Pourghasemi, GA Ghanbarian, SF Afzali - Geoderma, 2019 - Elsevier
The Maharloo watershed has witnessed many gullies in the recent due to the specific topo-
climatic conditions and man-made activities in that area. The present study is set out to …

GIS-based groundwater potential map** in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches

A Arabameri, K Rezaei, A Cerda, L Lombardo… - Science of the total …, 2019 - Elsevier
In arid and semi-arid areas, groundwater resource is one of the most important water
sources by the humankind. Knowledge of groundwater distribution over space, associated …

Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models

A Azareh, O Rahmati, E Rafiei-Sardooi… - Science of the Total …, 2019 - Elsevier
Gully erosion susceptibility map** is a fundamental tool for land-use planning aimed at
mitigating land degradation. However, the capabilities of some state-of-the-art data-mining …

Predicting heavy metal contents by applying machine learning approaches and environmental covariates in west of Iran

K Azizi, S Ayoubi, K Nabiollahi, Y Garosi… - Journal of Geochemical …, 2022 - Elsevier
The cuurent study was performed to predict spatial distribution of some heavy metals (Ni, Fe,
Cu, Mn) in western Iran, using environmental covariates and applying two machine learning …

[HTML][HTML] Novel ensemble approach of deep learning neural network (DLNN) model and particle swarm optimization (PSO) algorithm for prediction of gully erosion …

SS Band, S Janizadeh, S Chandra Pal, A Saha… - Sensors, 2020 - mdpi.com
This study aims to evaluate a new approach in modeling gully erosion susceptibility (GES)
based on a deep learning neural network (DLNN) model and an ensemble particle swarm …

Assessing the performance of GIS-based machine learning models with different accuracy measures for determining susceptibility to gully erosion

Y Garosi, M Sheklabadi, C Conoscenti… - Science of the Total …, 2019 - Elsevier
The main purpose was to compare discrimination and reliability of four machine learning
models to create gully erosion susceptibility map (GESM) in a part of Ekbatan Dam Basin …