A5063208791- Flood Risk Assessment and Management
- Groundwater and Watershed Analysis
- Soil erosion and sediment transport
- Hydrology and Watershed Management Studies
- Landslides and related hazards
- Hydrology and Drought Analysis
- Fire effects on ecosystems
- Hydrology and Sediment Transport Processes
- Tree Root and Stability Studies
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Hydrological Forecasting Using AI
- Geotechnical Engineering and Analysis
- Soil and Land Suitability Analysis
- Geochemistry and Geologic Mapping
- COVID-19 impact on air quality
- COVID-19 Pandemic Impacts
- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Anomaly Detection Techniques and Applications
- Geophysical Methods and Applications
- Groundwater flow and contamination studies
- Water resources management and optimization
- Dam Engineering and Safety
- Hydrocarbon exploration and reservoir analysis
- COVID-19 epidemiological studies
Tarbiat Modares University
2015-2024
This analysis aims to generate landslide susceptibility maps (LSMs) using various machine learning methods, namely random forest (RF), alternative decision tree (ADTree) and Fisher’s Linear Discriminant Function (FLDA). The results of the FLDA, RF ADTree models were compared with regard their applicability for creating an LSM Gallicash river watershed in northern part Iran close Caspian Sea. A inventory map was created GPS points obtained a field analysis, high-resolution satellite images,...
Landslides are among the most harmful natural hazards for human beings. This study aims to delineate landslide hazard zones in Darjeeling and Kalimpong districts of West Bengal, India using a novel ensemble approach combining weight-of-evidence (WofE) support vector machine (SVM) techniques with remote sensing datasets geographic information systems (GIS). The area currently faces severe problems, causing fatalities losses property. In present study, inventory database was prepared Google...
Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory, especially in Northern provinces. A number of studies have been recently undertaken to study this process and predict it over space ultimately, broader national effort, limit its negative effects on local communities. We focused Bastam watershed where 9.3% surface currently affected by gullying. Machine learning algorithms are under magnifying glass across geomorphological community for their high...
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 climate. Therefore, flood susceptibility (FS) mapping is indeed necessary to overcome natural hazard phenomena. With mind, we evaluated prediction performance FS Koiya River basin, Eastern India. The present research work was done through preparation sophisticated inventory map; eight conditioning variables were selected based on...
The concept of leveraging the predictive capacity predisposing factors for landslide susceptibility (LS) modeling has been continuously improved in recent work focusing on computational and machine learning algorithms. This paper explores different approaches to LS modelling using artificial intelligence. key objective this study is estimate a map Taleghan-Alamut basin Iran Credal Decision Tree (CDT)-based (i.e. CDT-Bagging, CDT-Multiboost CDT-SubSpace) hybrid approaches, which are...
Landslide is one of the most important geomorphological hazards that cause significant ecological and economic losses results in billions dollars financial thousands casualties per year. The occurrence landslide northern Iran (Alborz Mountain Belt) often due to geological climatic conditions tectonic human activities. To reduce or control damage caused by landslides, susceptibility mapping (LSM) risk assessment are necessary. In this study, efficiency integration frequency ratio (FR) random...
Gully erosion triggers land degradation and restricts the use of land. This study assesses spatial relationship between gully (GE) geo-environmental variables (GEVs) using Weights-of-Evidence (WoE) Bayes theory, then applies three data mining methods—Random Forest (RF), boosted regression tree (BRT), multivariate adaptive spline (MARS)—for susceptibility mapping (GESM) in Shahroud watershed, Iran. locations were identified by extensive field surveys, a total 172 GE mapped. Twelve...
Abstract This study aims to assess gully erosion susceptibility and delineate erosion‐prone areas in Toroud Watershed, Semnan Province, Iran. Two different methods, namely, logistic regression (LR) evidential belief function (EBF), were evaluated, a new ensemble method was proposed using the combination of both methods. We initially created inventory map resources, including early reports, Google Earth images, Global Positioning System‐aided field surveys. subsequently split this information...
The awareness of erosion risk in watersheds provides the possibility identifying critical areas and prioritising protective management plans. Soil is one major natural hazards rainy mountainous regions Neka Roud Watershed Mazandaran Province, Iran. This research assesses soil susceptibility through morphometric parameters land use/land cover (LU/LC) factor based on multiple-criteria decision-making (MCDM) techniques, remote sensing GIS. A set 17 linear, relief shape 5 LU/LC classes are used...
Gully erosion is a form of natural disaster and one the land loss mechanisms causing severe problems worldwide. This study aims to delineate areas with most gully susceptibility (GES) using machine learning techniques Random Forest (RF), Gradient Boosted Regression Tree (GBRT), Naïve Bayes (NBT), Ensemble (TE). The inventory map (GIM) consists 120 gullies. Of gullies, 84 gullies (70%) were used for training 36 (30%) validate models. Fourteen conditioning factors (GCFs) GES modeling...
The present study has been carried out in the Tabriz River basin (5397 km2) north-western Iran. Elevations vary from 1274 to 3678 m above sea level, and slope angles range 0 150.9 %. average annual minimum maximum temperatures are 2 °C 12 °C, respectively. rainfall ranges 243 641 mm, northern southern parts of receive highest amounts. In this study, we mapped groundwater potential (GWP) with a new hybrid model combining random subspace (RS) multilayer perception (MLP), naïve Bayes tree...