Hamid Gholami

发表

Long-term (2012–2020) PM10 concentrations and increasing trends in the Sistan Basin: The role of levar wind and synoptic meteorology

P. Kosmopoulos, D. Kaskaoutis, R. D. Behrooz, 2022, Atmospheric Pollution Research.

Assessment of the uncertainty and interpretability of deep learning models for mapping soil salinity using DeepQuantreg and game theory

S. Golzari, A. Mohammadifar, Hamid Gholami, 2022, Scientific reports.

Evaluation of pollution indices, health hazards and source identification of heavy metal in dust particles and storm trajectory simulation using HYSPLIT model (Case study: Hendijan center dust, southwest of Iran)

Payman Rezaee, Hamid Gholami, Seyedeh Akram Jooybari, 2022, Environmental Monitoring and Assessment.

Fingerprinting the spatial sources of fine-grained sediment deposited in the bed of the Mehran River, southern Iran

A. Fatahi, Aboalhasan Fathabadi, Hamid Gholami, 2022, Scientific Reports.

Fingerprinting the Spatial Sources of Fine-grained Sediment Deposited in the Bed of the Mehran River Draining into the Northern Coast of the Persian Gulf using Elemental Geochemistry

A. Fatahi, Aboalhasan Fathabadi, Hamid Gholami, 2021 .

High-resolution, spatially resolved quantification of wind erosion rates based on UAV images (case study: Sistan region, southeastern Iran)

A. Rashki, N. Moradi, Hamid Gholami, 2022, Environmental Science and Pollution Research.

Stacking- and voting-based ensemble deep learning models (SEDL and VEDL) and active learning (AL) for mapping land subsidence

S. Golzari, A. Mohammadifar, Hamid Gholami, 2022, Environmental Science and Pollution Research.

The role of geometric properties of ephemeral arid streams in the control of soil and sediment quality, and vegetation canopy distribution: a case study in the southwest of Fars province, Iran

A. Nohegar, Mohammad Taher Sehati, Hamid Gholami, 2023, Journal of Soils and Sediments.

Integrated modelling for mapping spatial sources of dust in central Asia - An important dust source in the global atmospheric system

S. Golzari, A. Collins, D. Kaskaoutis, 2021 .

Desertification of Iran in the early twenty-first century: assessment using climate and vegetation indices

A. Collins, M. Telfer, J. Jansen, 2021, Scientific Reports.

Fingerprinting Sources of Fine-grained Sediment Deposited in a Riverine System by GLUE

Seyed Masoud Soleimanpour, Omid Rahmati, S. Shadfar, 2023, Water Resources Management.

Disentangling variations of dust concentration in Greenland ice cores over the last glaciation: An overview of current knowledge and new initiative

D. Kaskaoutis, Yougui Song, Xinzhou Li, 2023, Earth-Science Reviews.

Predicting of dust storm source by combining remote sensing, statistic-based predictive models and game theory in the Sistan watershed, southwestern Asia

D. Kaskaoutis, Sima Pourhashemi, Hamid Gholami, 2021, Journal of Arid Land.

Mapping of the Wind Erodible Fraction of Soil by Bidirectional Gated Recurrent Unit (Bigru) and Bidirectional Recurrent Neural Network (Birnn) Deep Learning Models

C. Ritsema, A. Mohammadifar, M. Riksen, 2023, SSRN Electronic Journal.

Late Pleistocene dynamics of dust emissions related to westerlies revealed by quantifying loess provenance changes in North Tian Shan, Central Asia

D. Kaskaoutis, Yue Li, Yougui Song, 2023, CATENA.

Modeling land susceptibility to wind erosion hazards using LASSO regression and graph convolutional networks

D. Kaskaoutis, K. Fitzsimmons, A. Mohammadifar, 2023, Frontiers in Environmental Science.

Novel integrated modelling based on multiplicative long short-term memory (mLSTM) deep learning model and ensemble multi-criteria decision making (MCDM) models for mapping flood risk.

S. Golzari, A. Mohammadifar, Hamid Gholami, 2023, Journal of Environmental Management.

Novel deep learning hybrid models (CNN-GRU and DLDL-RF) for the susceptibility classification of dust sources in the Middle East: a global source

A. Mohammadifar, Hamid Gholami, 2022, Scientific Reports.

Mineral Resource Classification Using Geostatistical and Fractal Simulation in the Masjed Daghi Cu–Mo Porphyry Deposit, NW Iran

N. Madani, P. Afzal, A. Yasrebi, 2023, Minerals.

Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates (TSP) in Zabol, Iran during the dusty period of 120-days wind.

D. Kaskaoutis, A. Mohammadifar, R. D. Behrooz, 2023, Environmental pollution.

Interpretability of simple RNN and GRU deep learning models used to map land susceptibility to gully erosion.

S. Golzari, A. Mohammadifar, Hamid Gholami, 2023, The Science of the total environment.

An interpretable deep learning model to map land subsidence hazard.

S. Golzari, Hamid Gholami, Paria Rahmani, 2024, Environmental science and pollution research international.

An assessment of global land susceptibility to wind erosion based on deep-active learning modelling and interpretation techniques

P. Borrelli, Panos Panagos, A. Mohammadifar, 2024, Scientific reports.

Using an interpretable deep learning model for the prediction of riverine suspended sediment load.

Hamid Gholami, Biswajeet Pradhan, Aliakbar Mohamadifar, 2024, Environmental science and pollution research international.