| A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran A Arabameri, K Rezaei, A Cerdą, C Conoscenti, Z Kalantari Science of the Total Environment 660, 443-458, 2019 | 204 | 2019 |
| Erodibility prioritization of sub-watersheds using morphometric parameters analysis and its mapping: A comparison among TOPSIS, VIKOR, SAW, and CF multi-criteria decision … AA Ameri, HR Pourghasemi, A Cerda Science of the Total Environment 613, 1385-1400, 2018 | 200 | 2018 |
| GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches A Arabameri, K Rezaei, A Cerda, L Lombardo, J Rodrigo-Comino Science of the total environment 658, 160-177, 2019 | 153 | 2019 |
| GIS-based gully erosion susceptibility mapping: a comparison among three data-driven models and AHP knowledge-based technique A Arabameri, K Rezaei, HR Pourghasemi, S Lee, M Yamani Environmental earth sciences 77, 1-22, 2018 | 138 | 2018 |
| A novel ensemble approach for landslide susceptibility mapping (LSM) in Darjeeling and Kalimpong districts, West Bengal, India J Roy, S Saha, A Arabameri, T Blaschke, DT Bui Remote Sensing 11 (23), 2866, 2019 | 137 | 2019 |
| Gully erosion zonation mapping using integrated geographically weighted regression with certainty factor and random forest models in GIS A Arabameri, B Pradhan, K Rezaei Journal of environmental management 232, 928-942, 2019 | 133 | 2019 |
| Landslide susceptibility evaluation and management using different machine learning methods in the Gallicash River Watershed, Iran A Arabameri, S Saha, J Roy, W Chen, T Blaschke, D Tien Bui Remote Sensing 12 (3), 475, 2020 | 128 | 2020 |
| Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India A Arora, A Arabameri, M Pandey, MA Siddiqui, UK Shukla, DT Bui, ... Science of the Total Environment 750, 141565, 2021 | 125 | 2021 |
| GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms A Arabameri, B Pradhan, K Rezaei, M Sohrabi, Z Kalantari Journal of Mountain Science 16 (3), 595-618, 2019 | 121 | 2019 |
| Spatial modelling of gully erosion using GIS and R programing: A comparison among three data mining algorithms A Arabameri, B Pradhan, HR Pourghasemi, K Rezaei, N Kerle Applied sciences 8 (8), 1369, 2018 | 114 | 2018 |
| Comparison of machine learning models for gully erosion susceptibility mapping A Arabameri, W Chen, M Loche, X Zhao, Y Li, L Lombardo, A Cerda, ... Geoscience Frontiers 11 (5), 1609-1620, 2020 | 108 | 2020 |
| Assessment of landslide susceptibility using statistical-and artificial intelligence-based FR–RF integrated model and multiresolution DEMs A Arabameri, B Pradhan, K Rezaei, CW Lee Remote Sensing 11 (9), 999, 2019 | 105 | 2019 |
| Gully erosion susceptibility mapping using GIS-based multi-criteria decision analysis techniques A Arabameri, B Pradhan, K Rezaei, C Conoscenti Catena 180, 282-297, 2019 | 97 | 2019 |
| Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function–logistic regression algorithm A Arabameri, B Pradhan, K Rezaei, M Yamani, HR Pourghasemi, ... Land Degradation & Development 29 (11), 4035-4049, 2018 | 97 | 2018 |
| Flood susceptibility assessment using novel ensemble of hyperpipes and support vector regression algorithms A Saha, SC Pal, A Arabameri, T Blaschke, S Panahi, I Chowdhuri, ... Water 13 (2), 241, 2021 | 93 | 2021 |
| Novel ensembles of COPRAS multi-criteria decision-making with logistic regression, boosted regression tree, and random forest for spatial prediction of gully erosion susceptibility A Arabameri, M Yamani, B Pradhan, A Melesse, K Shirani, DT Bui Science of the total environment 688, 903-916, 2019 | 90 | 2019 |
| Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, REPTree: A case study at the Gumani River Basin, India S Saha, M Saha, K Mukherjee, A Arabameri, PTT Ngo, GC Paul Science of the Total Environment 730, 139197, 2020 | 88 | 2020 |
| Comparative assessment using boosted regression trees, binary logistic regression, frequency ratio and numerical risk factor for gully erosion susceptibility modelling A Arabameri, B Pradhan, L Lombardo Catena 183, 104223, 2019 | 84 | 2019 |
| Flash flood susceptibility modelling using functional tree and hybrid ensemble techniques A Arabameri, S Saha, W Chen, J Roy, B Pradhan, DT Bui Journal of Hydrology 587, 125007, 2020 | 82 | 2020 |
| Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS A Arabameri, B Pradhan, HR Pourghasemi, K Rezaei Geomatics, Natural Hazards and Risk 9 (1), 1129-1155, 2018 | 82 | 2018 |
Professor Biswajeet Pradhan, SMIEEE...Distinguished Prof. & Director, CAMGIS Center, University of Technology Sydney, AustraliaVerified email at uts.edu.au
