Omid Rahmati
Omid Rahmati
Assistant Professor at AREEO - 2021& 2022 Clarivate Highly Cited Researcher
Verified email at - Homepage
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Cited by
Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS
O Rahmati, A Nazari Samani, M Mahdavi, HR Pourghasemi, H Zeinivand
Arabian Journal of Geosciences 8, 7059-7071, 2015
Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: a case study at Mehran Region, Iran
O Rahmati, HR Pourghasemi, AM Melesse
Catena 137, 360-372, 2016
Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran
O Rahmati, HR Pourghasemi, H Zeinivand
Geocarto International 31 (1), 42-70, 2016
Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS
Y Razandi, HR Pourghasemi, NS Neisani, O Rahmati
Earth Science Informatics 8, 867-883, 2015
Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis
O Rahmati, H Zeinivand, M Besharat
Geomatics, Natural Hazards and Risk 7 (3), 1000-1017, 2016
Prediction of the landslide susceptibility: Which algorithm, which precision?
HR Pourghasemi, O Rahmati
Catena 162, 177-192, 2018
Urban flood risk mapping using the GARP and QUEST models: A comparative study of machine learning techniques
H Darabi, B Choubin, O Rahmati, AT Haghighi, B Pradhan, B KlÝve
Journal of hydrology 569, 142-154, 2019
A novel machine learning-based approach for the risk assessment of nitrate groundwater contamination
F Sajedi-Hosseini, A Malekian, B Choubin, O Rahmati, S Cipullo, ...
Science of the total environment 644, 954-962, 2018
Flood detection and susceptibility mapping using sentinel-1 remote sensing data and a machine learning approach: Hybrid intelligence of bagging ensemble based on k-nearest†…
H Shahabi, A Shirzadi, K Ghaderi, E Omidvar, N Al-Ansari, JJ Clague, ...
Remote Sensing 12 (2), 266, 2020
River suspended sediment modelling using the CART model: A comparative study of machine learning techniques
B Choubin, H Darabi, O Rahmati, F Sajedi-Hosseini, B KlÝve
Science of the Total Environment 615, 272-281, 2018
Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion
O Rahmati, N Tahmasebipour, A Haghizadeh, HR Pourghasemi, ...
Geomorphology 298, 118-137, 2017
Flood susceptibility mapping with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory
TG Nachappa, ST Piralilou, K Gholamnia, O Ghorbanzadeh, O Rahmati, ...
Journal of hydrology 590, 125275, 2020
Gully erosion susceptibility mapping: the role of GIS-based bivariate statistical models and their comparison
O Rahmati, A Haghizadeh, HR Pourghasemi, F Noormohamadi
Natural hazards 82, 1231-1258, 2016
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, JB Sankey, S Lee, H Shahabi, ...
Science of the Total Environment 655, 684-696, 2019
Delineation of groundwater potential zones using remote sensing and GIS-based data-driven models
S Ghorbani Nejad, F Falah, M Daneshfar, A Haghizadeh, O Rahmati
Geocarto international 32 (2), 167-187, 2017
Evaluating the influence of geo-environmental factors on gully erosion in a semi-arid region of Iran: An integrated framework
O Rahmati, N Tahmasebipour, A Haghizadeh, HR Pourghasemi, ...
Science of the Total Environment 579, 913-927, 2017
Spatial prediction of flood-susceptible areas using frequency ratio and maximum entropy models
S Siahkamari, A Haghizadeh, H Zeinivand, N Tahmasebipour, O Rahmati
Geocarto international 33 (9), 927-941, 2018
Spatial analysis of groundwater potential using weights-of-evidence and evidential belief function models and remote sensing
N Tahmassebipoor, O Rahmati, F Noormohamadi, S Lee
Arabian Journal of Geosciences 9, 1-18, 2016
Predicting uncertainty of machine learning models for modelling nitrate pollution of groundwater using quantile regression and UNEEC methods
O Rahmati, B Choubin, A Fathabadi, F Coulon, E Soltani, H Shahabi, ...
Science of the Total Environment 688, 855-866, 2019
Identification of critical flood prone areas in data-scarce and ungauged regions: a comparison of three data mining models
O Rahmati, HR Pourghasemi
Water resources management 31, 1473-1487, 2017
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