Alireza Arabameri
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View article: Soil erosion and sediment yield estimation in a tropical monsoon dominated river basin using GIS-based models
Soil erosion and sediment yield estimation in a tropical monsoon dominated river basin using GIS-based models Open
The increasing soil erosion (SE) and the associated problems for society, economy, and environment sparked a lot of interest in estimating and mapping SE at different basin scales. The estimation of SE exhibits that SE ranges from 10 to 50…
View article: Landslide risk assessment and management using hybrid machine learning‐based empirical models
Landslide risk assessment and management using hybrid machine learning‐based empirical models Open
Landslides are a prevalent geologic phenomenon that substantially threatens human life and infrastructure, resulting in considerable loss and destruction. The practice of landslide susceptibility mapping is crucial for the mitigation of ri…
View article: Spatial Distribution of Drought Vulnerability Mapping: Introducing a new methodology
Spatial Distribution of Drought Vulnerability Mapping: Introducing a new methodology Open
Droughts as a natural calamity have wreaked havoc on human health, environment, and the economy around the world. Due to its complex and multi-faceted nature, the risk assessment of drought requires the analysis of diverse parameters and m…
View article: Novel ensemble models and their optimization based flood susceptibility modelling in Indian Himalayan Foreland Basin
Novel ensemble models and their optimization based flood susceptibility modelling in Indian Himalayan Foreland Basin Open
This study focuses on the mapping of flood susceptibility in a specific region characterized by a low-altitude-range, sub-tropical monsoonal climate, and a riverine floodplain environment within the Middle Ganga Plain. To achieve this, fou…
View article: Integrated assessment of landslide susceptibility in the Kalaleh Basin, Golestan Province, Iran using novel SVR-GOA ensemble validated with BRT, ANN, and elastic net models
Integrated assessment of landslide susceptibility in the Kalaleh Basin, Golestan Province, Iran using novel SVR-GOA ensemble validated with BRT, ANN, and elastic net models Open
Landslides cause severe environmental problems, such as severe damages to infrastructures (i.e., bridges, roads, network masts, and buildings) and agricultural lands, across many parts of the world. Unfortunately, a high degree of accuracy…
View article: Optimizing machine learning algorithms for spatial prediction of gully erosion susceptibility with four training scenarios
Optimizing machine learning algorithms for spatial prediction of gully erosion susceptibility with four training scenarios Open
Gully erosion causes high soil erosion rates and is an environmental concern posing major risk to the sustainability of cultivated areas of the world. Gullies modify the land, shape new landforms and damage agricultural fields. Gully erosi…
View article: Spatial modelling and mapping of Gully Erosion Susceptibility using Neural Network Methods
Spatial modelling and mapping of Gully Erosion Susceptibility using Neural Network Methods Open
It plays a key role in redistributing degraded soils on a track. It is very important therefore to discuss the pattern of spatial occurrences of this phenomenon. Different methods have been used to map the susceptibility of gully erosion, …
View article: New machine learning ensemble for flood susceptibility estimation
New machine learning ensemble for flood susceptibility estimation Open
Natural disasters in particular have resulted in several economic losses that are resulting from an exponential increase in the number of economic losses in general across the globe. The floods are among the most severe natural hazards phe…
View article: Flood susceptibility mapping using meta-heuristic algorithms
Flood susceptibility mapping using meta-heuristic algorithms Open
Flood is a common global natural hazard, and detailed flood susceptibility maps for specific watersheds are important for flood management measures. We compute the flood susceptibility map for the Kaiser watershed in Iran using machine lea…
View article: Flood susceptibility computation using state-of-the-art machine learning and optimization algorithms
Flood susceptibility computation using state-of-the-art machine learning and optimization algorithms Open
The present study aims to estimate the flood susceptibility degree over the Prahova River basin located in the central-southern part of Romania. To obtain the proposed outcomes, the next 10 flood predictors were used as independent variabl…
View article: Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach
Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach Open
This study has developed a new ensemble model and tested another ensemble model for flood susceptibility mapping in the Middle Ganga Plain (MGP). The results of these two models have been quantitatively compared for performance analysis in…
View article: Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping
Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping Open
The optimal prediction of land subsidence (LS) is very much difficult because of limitations in proper monitoring techniques, field-base surveys and knowledge related to functioning and behavior of LS. Thus, due to the lack of LS susceptib…
View article: Weather Indicators and Improving Air Quality in Association with COVID-19 Pandemic in India
Weather Indicators and Improving Air Quality in Association with COVID-19 Pandemic in India Open
The COVID-19 pandemic enforced nationwide lockdown, which has restricted human activities from March 24 to May 3 2020, resulted an improved air quality across India. The present research investigates the connection between COVID-19 pandemi…
View article: Land Subsidence Spatial Modeling and Assessment of the Contribution of Geo-Environmental Factors to Land Subsidence: Comparison of Different Novel Ensemble Modeling Approaches
Land Subsidence Spatial Modeling and Assessment of the Contribution of Geo-Environmental Factors to Land Subsidence: Comparison of Different Novel Ensemble Modeling Approaches Open
Land subsidence is a worldwide threat. In arid and semiarid land, groundwater depletion is the main factor that induce the subsidence and results in environmental damages, with high economic losses. To foresee and prevent the impact of lan…
View article: Flood Susceptibility Assessment Using Novel Ensemble of Hyperpipes and Support Vector Regression Algorithms
Flood Susceptibility Assessment Using Novel Ensemble of Hyperpipes and Support Vector Regression Algorithms Open
Recurrent floods are one of the major global threats among people, particularly in developing countries like India, as this nation has a tropical monsoon type of climate. Therefore, flood susceptibility (FS) mapping is indeed necessary to …
View article: Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors
Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors Open
There is an evident increase in the importance that remote sensing sensors play in the monitoring and evaluation of natural hazards susceptibility and risk. The present study aims to assess the flash-flood potential values, in a small catc…
View article: Spatial prediction of shallow landslide: application of novel rotational forest-based reduced error pruning tree
Spatial prediction of shallow landslide: application of novel rotational forest-based reduced error pruning tree Open
Landslides are a form of soil erosion threatening the sustainability of some areas of the world. There is, therefore, a need to investigate landslide rates and behaviour. In this research, we introduced a novel hybrid artificial intelligen…
View article: Detection of areas prone to flood risk using state-of-the-art machine learning models
Detection of areas prone to flood risk using state-of-the-art machine learning models Open
The present study aims to evaluate the susceptibility to floods in the river basin of Buzau in Romania through the following 6 machine learning models: Support Vector Machine (SVM), J48 decision tree, Adaptive Neuro-Fuzzy Inference System …
View article: Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms
Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms Open
Spatial modelling of gully erosion at regional level is very relevant for local authorities to establish successful counter-measures and to change land-use planning. This work is exploring and researching the potential of a genetic algorit…
View article: Ensemble of Machine-Learning Methods for Predicting Gully Erosion Susceptibility
Ensemble of Machine-Learning Methods for Predicting Gully Erosion Susceptibility Open
Gully formation through water-induced soil erosion and related to devastating land degradation is often a quasi-normal threat to human life, as it is responsible for huge loss of surface soil. Therefore, gully erosion susceptibility (GES) …