A.Journal Publications
https://scholar.google.com/citations?user=jyRVQdwAAAAJ&hl=en
A1. Farzin Shabani, Mahyat Shafapourtehrany, Mohsen Ahmadi, Bahareh Kalantar, Haluk Özener, Kieran Clancy, Atefeh Esmaeili, Ricardo Siqueira da Silva, Linda J. Beaumont, John Llewelyn, Simon Jones, Alessandro Ossola, (2023). Habitat in flames: how climate change will affect fire risk across koala forests. Environmental Technology & Innovation (Q1)
A2. Borges, C. E., Von dos Santos Veloso, R., da Conceição, C. A., Mendes, D. S., Ramirez-Cabral, N. Y., Shabani, F., ... & da Silva, R. S. (2023). Forecasting Brassica napus production under climate change with a mechanistic species distribution model. Scientific Reports (Q1).
A3. Shafapourtehrany, M., Batur, M., Shabani, F., Pradhan, B., Kalantar, B., & Özener, H. (2023). A Comprehensive Review of Geospatial Technology Applications in Earthquake Preparedness, Emergency Management, and Damage Assessment. Remote Sensing (Q1).
A4. Shafapourtehrany, M. (2023). Geospatial Wildfire Risk Assessment from Social, Infrastructural and Environmental Perspectives: A Case Study in Queensland Australia. Fire (Q1)
A5. SHAFAPOURTEHRANY, M. (2022). Exploring the Risky Areas Due to Landslide Using Decision Tree Analysis: Case Study Tasmania, Australia. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 18, 86-101.
A6. Shafapourtehrany, M., Yariyan, P., Özener, H., Pradhan, B., & Shabani, F. (2022). Evaluating the application of K-mean clustering in Earthquake vulnerability mapping of Istanbul, Turkey. International Journal of Disaster Risk Reduction (Q1).
A7. Shafapourtehrany, M. (2022). Evaluation of Machine Learning Performance in Wildfire Susceptibility Mapping Under Limited Training Data Condition. Mühendislik Bilimleri ve Araştırmaları Dergisi , 4 (2) , 317-327 . DOI: 10.46387/bjesr.1174006
A8. MS Tehrany, H Özener, B Kalantar, N Ueda, MR Habibi, F Shabani, V Saeidi, F Shabani, 2021. Application of an Ensemble Statistical Approach in Spatial Predictions of Bushfire Probability and Risk Mapping. Journal of Sensors (Q3).
A9. K Tshering, P Thinley, M Tehrany, U Thinley, F Shabani, 2020. A comparison of the qualitative Analytic Hierarchy Process and the quantitative Frequency Ratio techniques in predicting forest fire-prone areas in Bhutan using GIS. Forecasting.
A10. F Shabani, M Ahmadi, L Kumar, S Solhjouy-fard, M Tehrany, FZ Shabani, 2020. Invasive weed species threats to global biodiversity: Future scenarios of changes in the number of invasive species in a changing climate. Ecological Indicators (Q1).
A11. Shafapour Tehrany, M., Jones, S., Shabani, F, 2019. Identifying the Essential Flood Conditioning Factors for Flood Prone Area Mapping Using Machine Learning Techniques for consideration to Journal of Hydrology. Catena (Q1).
A12. MS Tehrany, S Jones, F Shabani, F Martínez-Álvarez, DT Bui, 2019. A novel ensemble modeling approach for the spatial prediction of tropical forest fire susceptibility using logitboost machine learning classifier and multi-source geospatial data. Theoretical and Applied Climatology (Q2).
A13. MS Tehrany, L Kumar, F Shabani, 2019. A Novel GIS-Based Ensemble Technique for Flood Susceptibility Mapping Using Evidential Belief Function and Support Vector Machine: Brisbane, Australia. PeerJ (Q1).
A14. M Shafapour Tehrany, L Kumar, M Neamah Jebur, F Shabani, 2019. Evaluating the application of the statistical index method in flood susceptibility mapping and its comparison with frequency ratio and logistic regression methods. Geomatics, Natural Hazards and Risk (Q1).
A15. Shafapour Tehrany, M., Kumar L. 2018. The application of a Dempster-Shafer-based evidential belief function in flood susceptibility mapping and comparison with frequency ratio and logistic regression methods. Environmental earth sciences (Q2).
A16. Shabani F, Tehrany MS, Solhjouy-fard S, Kumar L. 2018. A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus). PeerJ (Q1).
A17. Shafapour Tehrany, M., Kumar, L., Jebur, M. 2018. Evaluating the application of statistical index method in flood susceptibility mapping and its comparison with frequency ratio and logistic regression methods. Geomatics Natural Hazards and Risk (Q1).
A18. Shafapour Tehrany, M., Jones, S., Shabani, F; Francisco Martínez Álvarez; Quang-Thanh Bui; Dieu Tien Bui 2018. A Novel Ensemble Modeling Approach for the Spatial Prediction of Tropical Forest Fire Danger Using Logitboost Machine Learning Classifier and Multi-source Geospatial Data. Theoretical and Applied Climatology (Q2).
A19. Kumar, L. and Shafapour Tehrany, M. 2017. Climate change impacts on the threatened terrestrial vertebrates of the Pacific Islands. Scientific Reports, Nature Publishing Group (Q1).
A20. Shafapour Tehrany, M. Kumar, L. and Drielsma, M. 2017. Review of native vegetation condition assessment concepts, methods and future trends'. Journal for Nature Conservation (Q1).
A21. Shafapour Tehrany, M. Shabani, F. Jebur, M. Hong. Chen, W. and Xie, X. 2017. GIS-based spatial prediction of flood prone areas using standalone frequency ratio, logistic regression, weight of evidence and their ensemble techniques. Geomatics, Natural Hazards and Risk (Q1).
A22. Shafapour Tehrany, M. Shabani, F. Javier, D. and Kumar, L. 2017. Soil erosion susceptibility mapping for current and 2100 climate conditions using evidential belief function and frequency ratio. Geomatics Natural Hazards and Risk (Q1).
A23. Shafapour Tehrany, M. Jones, S., 2017. Evaluating the variations in the flood susceptibility maps accuracies due to the alterations in the type and extent of the flood inventory. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.
A24. Shafapour Tehrany, M., & Kumar, L. 2016. The application of a Dempster–Shafer-based evidential belief function in flood susceptibility mapping and comparison with multivariate and bivariate statistical methods. Geomatics, Natural Hazards and Risk (Q1)
A25. Shafapour Tehrany, M., & Kumar, L. 2016. A Novel GIS-Based Ensemble Technique for Flood Susceptibility Mapping Using Evidential Belief Function and Support Vector Machine. Catena (Q1).
A26. Pradhan, B., Shafapour Tehrany, M., & Jebur, M. N. 2016. A New Semiautomated Detection Mapping of Flood Extent From TerraSAR-X Satellite Image Using Rule-Based Classification and Taguchi Optimization Techniques. IEEE Transactions on Geoscience and Remote Sensing (Q1).
A27. Pradhan, B., Jebur, M. N., Shafri, H. Z. M., & Shafapour Tehrany, M. 2016. Data Fusion Technique Using Wavelet Transform and Taguchi Methods for Automatic Landslide Detection From Airborne Laser Scanning Data and QuickBird Satellite Imagery. IEEE Transactions on Geoscience & Remote Sensing (Q1).
A28. Shafapour Tehrany, M., Pradhan, B., & Jebur, M. N. 2015. Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method. Stochastic Environmental Research and Risk Assessment (Q1).
A29. Shafapour Tehrany, M., Pradhan, B., Mansor, S., & Ahmad, N. 2015. Flood susceptibility assessment using GIS-based support vector machine model with different kernel types. Catena (Q1).
A30. Jebur, M. N., Pradhan, B., & Shafapour Tehrany, M. 2015. Manifestation of LiDAR-Derived Parameters in the Spatial Prediction of Landslides Using Novel Ensemble Evidential Belief Functions and Support Vector Machine Models in GIS. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Q1).
A31. Jebur, M. N., Pradhan, B., & Shafapour Tehrany, M. 2015. Using ALOS PALSAR derived high-resolution DInSAR to detect slow- moving landslides in tropical forest: Cameron Highlands, Malaysia. Geomatics, Natural Hazards and Risk (Q1).
A32. Shafapour Tehrany, M., Pradhan, B., & Jebur, M. N. 2014. Flood susceptibility mapping using a novel ensemble weights-of- evidence and support vector machine models in GIS. Journal of Hydrology (Q1).
A33. Shafapour Tehrany, M., Lee, M. J., Pradhan, B., Jebur, M. N., & Lee, S. 2014. Flood susceptibility mapping using integrated bivariate and multivariate statistical models. Environmental Earth Sciences (Q2).
A34. Shafapour Tehrany, M., Pradhan, B., & Jebu, M. N. 2014. A comparative assessment between object and pixel-based classification approaches for land use/land cover mapping using SPOT 5 imagery. Geocarto International.
A35. Jebur, M. N., Pradhan, B., & Shafapour Tehrany, M. 2014. Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale. Remote Sensing of Environment (Q1).
A36. Jebur, M. N., Mohd Shafri, H. Z., Pradhan, B., & Shafapour Tehrany, M. 2014. Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery. Geocarto International (Q1).
A37. Jebur, M. N., Pradhan, B., & Shafapour Tehrany, M. 2014. Detection of vertical slope movement in highly vegetated tropical area of Gunung pass landslide, Malaysia, using L-band InSAR technique. Geosciences Journal (Q2).
A38. Jebur, M. N., Pradhan, B., Mohd Shafri, H. Z., & Shafapour Tehrany, M. 2014. An integrated user-friendly ArcMAP tool for bivariate statistical modeling in geoscience applications. Geoscientific Model Development (Q1).
A39. Pradhan, B., Abokharima, M. H., Jebur, M. N., & Shafapour Tehrany, M. 2014. Land subsidence susceptibility mapping at Kinta Valley (Malaysia) using the evidential belief function model in GIS. Natural Hazards (Q1).
A40. Siyahghalati, S., Saraf, A. K., Pradhan, B., Jebur, M. N., & Shafapour Tehrany, M. 2014. Rule-based semi-automated approach for the detection of landslides induced by 18 September 2011 Sikkim, Himalaya earthquake using IRS LISS3 satellite images. Geomatics, Natural Hazards and Risk (Q1).
A41. Umar, Z., Pradhan, B., Ahmad, A., Jebur, M. N., & Shafapour Tehrany, M. 2014. Earthquake induced landslide susceptibility mapping using an integrated ensemble frequency ratio and logistic regression models in West Sumatera Province, Indonesia. Catena (Q1).
A42. Pradhan, B., Hagemann, U., Shafapour Tehrany, M.,& Prechtel, N. 2014. An easy to use ArcMap based texture analysis program for extraction of flooded areas from TerraSAR-X satellite image. Computers & Geosciences (Q1).
A43. Shafapour Tehrany, M., Pradhan, B., & Jebur, M. N. 2013. Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. Journal of Hydrology (Q1).
A44. Shafapour Tehrany, M., Pradhan, B., & Jebur, M. N. 2013. Remote sensing data reveals eco-environmental changes in urban areas of Klang Valley, Malaysia: contribution from object-based analysis. Journal of the Indian Society of Remote Sensing (Q2).
B. International Conference Proceedings
B1. AGU23, San Francisco, 11-15 December 2023
B2. The General Assembly 2023 of the European Geosciences Union (EGU), Austria Center Vienna (ACV) in Vienna, Austria, 23–28 April 2023.
- Web Based Tectonic Hazard Monitoring: A case study of 2020 Elazig Earthquake
- Surface Displacement and Source Parameters of the Mw 7.7 and Mw 7.6 Kahramanmaraş Earthquakes
B3. International Symposium on Applied Geoinformatics 2022 (ISAG2022) - Chania, Crete, Greece 12-14 October, 2022.
B4. 2nd Global Conference on Engineering Research (GLOBCER'22)- 7-11 September 2022.
B5. International Conference on Basic Sciences, Engineering and Technology (ICBASET)-August 25 - 28, 2022.
B6. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4/W5, 2017 GGT 2017, 4 October 2017, Kuala Lumpur, Malaysia.
