| Gully erosion susceptibility assessment and management of hazard-prone areas in India using different machine learning algorithms A Gayen, HR Pourghasemi, S Saha, S Keesstra, S Bai Science of the total environment 668, 124-138, 2019 | 283 | 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 | 191 | 2020 |
| 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 | 185 | 2019 |
| Landslide susceptibility mapping using knowledge driven statistical models in Darjeeling District, West Bengal, India J Roy, S Saha Geoenvironmental Disasters 6 (1), 1-18, 2019 | 158 | 2019 |
| Applying deep learning and benchmark machine learning algorithms for landslide susceptibility modelling in Rorachu river basin of Sikkim Himalaya, India K Mandal, S Saha, S Mandal Geoscience Frontiers 12 (5), 101203, 2021 | 142 | 2021 |
| 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 | 141 | 2020 |
| Groundwater potential mapping using analytical hierarchical process: a study on Md. Bazar Block of Birbhum District, West Bengal S Saha Spatial Information Research 25 (4), 615-626, 2017 | 124 | 2017 |
| 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 | 114 | 2020 |
| Application of the GIS-based probabilistic models for mapping the flood susceptibility in Bansloi sub-basin of Ganga-Bhagirathi river and their comparison GC Paul, S Saha, TK Hembram Remote Sensing in Earth Systems Sciences 2, 120-146, 2019 | 114 | 2019 |
| Prediction of landslide susceptibility in Rudraprayag, India using novel ensemble of conditional probability and boosted regression tree-based on cross-validation method S Saha, A Arabameri, A Saha, T Blaschke, PTT Ngo, VH Nhu, SS Band Science of the total environment 764, 142928, 2021 | 110 | 2021 |
| Identification of soil erosion-susceptible areas using fuzzy logic and analytical hierarchy process modeling in an agricultural watershed of Burdwan district, India S Saha, A Gayen, HR Pourghasemi, JP Tiefenbacher Environmental Earth Sciences 78 (23), 649, 2019 | 110 | 2019 |
| Prioritization of sub-watersheds for soil erosion based on morphometric attributes using fuzzy AHP and compound factor in Jainti River basin, Jharkhand, Eastern India TK Hembram, S Saha Environment, Development and Sustainability 22 (2), 1241-1268, 2020 | 104 | 2020 |
| A novel ensemble computational intelligence approach for the spatial prediction of land subsidence susceptibility A Arabameri, S Saha, J Roy, JP Tiefenbacher, A Cerda, T Biggs, ... Science of the Total Environment 726, 138595, 2020 | 100 | 2020 |
| Machine learning-based gully erosion susceptibility mapping: A case study of Eastern India S Saha, J Roy, A Arabameri, T Blaschke, D Tien Bui Sensors 20 (5), 1313, 2020 | 99 | 2020 |
| Numerische Berechnung von Mauerwerkstrukturen in homogenen und diskreten Modellierungsstrategien R Schlegel | 99* | 2004 |
| Application of weights-of-evidence (WoE) and evidential belief function (EBF) models for the delineation of soil erosion vulnerable zones: a study on Pathro river basin … A Gayen, S Saha Modeling Earth Systems and Environment 3 (3), 1123-1139, 2017 | 88 | 2017 |
| Comparing the efficiency of weight of evidence, support vector machine and their ensemble approaches in landslide susceptibility modelling: A study on Kurseong region of … A Saha, S Saha Remote Sensing Applications: Society and Environment 19, 100323, 2020 | 85 | 2020 |
| Impact of COVID-19 induced lockdown on environmental quality in four Indian megacities Using Landsat 8 OLI and TIRS-derived data and Mamdani fuzzy logic modelling approach S Ghosh, A Das, TK Hembram, S Saha, B Pradhan, AM Alamri Sustainability 12 (13), 5464, 2020 | 85 | 2020 |
| Analyzing spatial relationship between land use/land cover (LULC) and land surface temperature (LST) of three urban agglomerations (UAs) of Eastern India S Saha, A Saha, M Das, A Saha, R Sarkar, A Das Remote Sensing Applications: Society and Environment 22, 100507, 2021 | 82 | 2021 |
| Hybrid ensemble machine learning approaches for landslide susceptibility mapping using different sampling ratios at East Sikkim Himalayan, India S Saha, J Roy, B Pradhan, TK Hembram Advances in Space Research 68 (7), 2819-2840, 2021 | 80 | 2021 |
Raju SarkarProfessor, Department of Civil Engineering, Delhi Technological University (formerly DCE)Підтверджена електронна адреса в dce.ac.in