A5046177232- Soil Geostatistics and Mapping
- Soil and Land Suitability Analysis
- Geochemistry and Geologic Mapping
- Soil Carbon and Nitrogen Dynamics
- Soil erosion and sediment transport
- Remote Sensing in Agriculture
- Soil and Unsaturated Flow
- Soil Management and Crop Yield
- Soil and Water Nutrient Dynamics
- Banana Cultivation and Research
- Hydrology and Watershed Management Studies
- Land Use and Ecosystem Services
- Hydrology and Sediment Transport Processes
- Geology and Paleoclimatology Research
- Aeolian processes and effects
- Water Quality and Pollution Assessment
- Soil Moisture and Remote Sensing
- Heavy metals in environment
- Invertebrate Taxonomy and Ecology
- Remote-Sensing Image Classification
- Soil Mechanics and Vehicle Dynamics
- Ecology and Vegetation Dynamics Studies
- Tree Root and Stability Studies
- Photovoltaic Systems and Sustainability
- Soil and Environmental Studies
University of Vermont
2022-2024
Henan University
2018-2022
Isfahan University of Technology
2017-2019
Agricultural Sciences and Natural Resources University of Khuzestan
2018-2019
Ramin Agriculture and Natural Resources University of Khouzestan
2019
Ghent University
2017
Understanding the spatial distribution of soil organic carbon (SOC) content over different climatic regions will enhance our knowledge gains and losses due to change. However, little is known about SOC in contrasting arid sub-humid Iran, whose complex SOC–landscape relationships pose a challenge analysis. Machine learning (ML) models with digital mapping framework can solve such relationships. Current research focusses on ensemble ML increase accuracy prediction. The usual method boosting or...
Soils constitute one of the most critical natural resources and maintaining their health is vital for agricultural development ecological sustainability, providing many essential ecosystem services. Driven by climatic variations anthropogenic activities, soil degradation has become a global issue that seriously threatens environment food security. Remote sensing (RS) technologies have been widely used to investigate as it highly efficient, time-saving, broad-scope. This review encompasses...
Drought is a natural hazard which affects ecosystems in the eastern Mediterranean. However, limited historical data for drought monitoring and forecasting are available Thus, implementing machine learning (ML) algorithms could allow prediction of future events. In this context, main goals research were to capture agricultural hydrological trends by using Standardized Precipitation Index (SPI) assess applicability four ML (bagging (BG), random subspace (RSS), tree (RT), forest (RF))...
Citrus spp. are one of the most important commercial crops with global marketing potential in world, as Iran. A soil management zone (MZ) an appropriate approach is necessary to achieve sustainable production, along improving and increasing economic benefits citrus plantations northern As first report, biological terrain attributes physicochemical properties (57 samples, 0–30 cm) were used for MZ delineation using integration principal component analysis (PCA) fuzzy c-means clustering...
Evaluation of spatial variability and mapping soil properties is critical for sustainable agricultural production in arid lands. The main objectives the present study were to spatialize organic carbon (SOC), particle size distribution(clay, sand, silt contents), calcium carbonate equivalent (CCE) by integrating multisource environmental covariates, including digital elevation model (DEM) remote sensing data machine learning (Cubist, Cu random forest, RF) an region Iran. Additionally,...
Digital soil maps can be used to depict the ability of fulfill certain functions. offer reliable information that in spatial planning programs. Several broad types data mining approaches through Soil Mapping (DSM) have been tested. The usual approach is select a model produces best validation statistics. However, instead choosing model, it possible combine all models realizing their strengths and weaknesses. We applied seven different techniques for prediction classes based on 194 sites...
Photovoltaic (PV) technology is becoming more popular due to climate change because it allows for replacing fossil-fuel power generation reduce greenhouse gas emissions. Consequently, many countries have been attempting generate electricity through PV plants over the last decade. Monitoring satellite imagery, machine learning models, and cloud-based computing systems that may ensure rapid precise locating with current status on a regional basis are crucial environmental impact assessment...
This study tested and evaluated a suite of nine individual base learners seven model averaging techniques for predicting the spatial distribution soil properties in central Iran. Based on nested-cross validation approach, results showed that artificial neural network Random Forest were most effective organic matter electrical conductivity, respectively. However, all performed better than learners. For example, Granger–Ramanathan approach resulted highest prediction accuracy matter, while...
Soil organic carbon (SOC) is an essential property of soil, and understanding its spatial patterns critical to vegetation management, soil degradation, environmental issues. This study applies a framework using remote sensing data digital mapping techniques examine the spatiotemporal dynamics SOC for Yazd-Ardakan Plain, Iran, from 1986 2016. Here, conditioned Latin hypercube sampling method was used select 201 sites. A set 37 predictors were obtained Landsat imagery taken in 1986, 1999, 2010...
This study was conducted to examine the capability of topographic features and remote sensing data in combination with other auxiliary environmental variables (geology geomorphology) predict CEC by using different machine learning models ((random forest (RF), k-nearest neighbors (kNNs), Cubist model (Cu), support vector machines (SVMs)) west Iran. Accordingly, collection ninety-seven soil samples performed from surface layer (0-20 cm), a number properties X-ray analyses, as well CEC, were...