Renata Pacheco Quevedo, PhD
T: +43-1-4277-48755
Sommersemester 2025
290010 UE Understanding, analysing and modelling Earth Surface Dynamics - Alps
Wintersemester 2024
Pacheco Quevedo, R., Andrade Maciel, D., Oliveira Andrades-Filho, C., Fossa Sampaio Mexias, L., Garcia de Oliveira, G., Boelter Herrmann, P., Corrêa Alves, F., & Glade, T. (Angenommen/Im Druck). Could such a large landslide event be expected in Rio Grande do Sul, southern Brazil? Using past events to predict the area impacted by the 2024 Mega Disaster. EGU General Assembly, Wien, Österreich.
Pacheco Quevedo, R., Andrade Maciel, D., Oliveira Andrades-Filho, C., Fossa Sampaio Mexias, L., Garcia de Oliveira, G., Boelter Herrmann, P., Corrêa Alves, F., & Glade, T. (Angenommen/Im Druck). Landslide susceptibility in Rio Grande do Sul: could past landslides indicate areas affected in May 2024?. Beitrag in Brazilian Remote Sensing Symposium, Salvador, Brasilien.
Maciel, D. A., Lousada, F., Fassoni-Andrade, A., Quevedo, R. P., Barbosa, C. C. F., Paule-Bonnet, M., & Novo, E. M. L. D. M. (2024). Sentinel-1 data reveals unprecedented reduction of open water extent due to 2023-2024 drought in the central Amazon basin. Environmental Research Letters, 19(12), 1. Artikel 124034. https://doi.org/10.1088/1748-9326/ad8a71
Pacheco Quevedo, R., Andrade Maciel, D., Souza Reis, M., Daleles Rennó, C., Vieira Dutra, L., Oliveira Andrades-Filho, C., Velástegui-Montoya, A., Zhang, T., Sehn Körting, T., & Oighenstein Anderson, L. (2024). Land use and land cover changes without invalid transitions: a case study in a landslide-affected area. Remote Sensing Applications: Society and Environment, 36, 1. Artikel 101314. https://doi.org/10.1016/j.rsase.2024.101314
Hitouri, S., Meriame, M., Ajim, A. S., Pacheco, Q. R., Nguyen-Huy, T., Bao, P. Q., ElKhrachy, I., & Varasano, A. (2024). Gully erosion mapping susceptibility in a Mediterranean environment: A hybrid decision-making model. International Soil and Water Conservation Research, 12(2), 279-297. https://doi.org/10.1016/j.iswcr.2023.09.008
Montoya, A. D. V., Romero, J. A. G., Chuizaca-Espinoza, I. A., Quevedo, R. P., Santana-Cunha, C., Ochoa-Brito, J. I., & Arias-Hidalgo, M. (2024). Assessing Regressive Erosion Effects: Unveiling Riverside Land Use Land Cover Changes Post Hydroelectric Project Construction. Environmental Challenges, 15, Artikel 100882. https://doi.org/10.1016/j.envc.2024.100882
Massao Futai, M., de Oliveira, L., Goulart Fiscina, L. F., Pacheco Quevedo, R., Rodrigues de Sousa, M. T., Matos Brasil de Araújo, G. R., Lopes Poncetti, B., Silva de Assis, L., Moraes Silveira, R., de Andrade, J. A., Monticelli, J. P., Suzuki, S., & Borges da Silva, T. (2024). Aplicação de novas tecnologias para avaliação do desempenho de taludes ferroviários em região tropical. Beitrag in Simpósio de Engenharia Ferroviária, Campinas, Brasilien.
Quevedo, R. P., Velastegui-Montoya, A., Montalván-Burbano, N., Morante-Carballo, F., Korup, O., & Rennó, C. D. (2023). Land use and land cover as a conditioning factor in landslide susceptibility: a literature review. Landslides, 20, 967. https://doi.org/10.1007/s10346-022-02020-4
Althuwaynee, O., Melillo, M., Gariano, S. L., Park, H. J., Kim, S.-W., Lombardo, L., Hader, P., Mohajane, M., Quevedo, R. P., Catani, F., & Aydda, A. (2023). DEWS: A QGIS tool pack for the automatic selection of reference rain gauges for landslide-triggering rainfall thresholds. Environmental Modelling & Software, 162, 1. https://doi.org/10.1016/j.envsoft.2023.105657
Bhagya, S. B., Sumi, A. S., Balaji, S., Danumah, J. H., Costache, R., Rajaneesh, A., Gokul, A., Chandrasenan, C. P., Quevedo, R. P., Johny, A., Sajinkumar, K. S., Saha, S., Ajin, R. S., Mammen, P. C., Abdelrahman, K., Fnais, M. S., & Abioui, M. (2023). Landslide Susceptibility Assessment of a Part of the Western Ghats (India) Employing the AHP and F-AHP Models and Comparison with Existing Susceptibility Maps. Land. https://doi.org/10.3390/land12020468
Lopes Gonçalves Horta, I. T., Albertani Pampuch Bortolozo, L., Pacheco Quevedo, R., Mauad, F. F., & Bruno Tech, A. R. (2023). Daily rainfall data validation: IMERG, CHIRPS, and gauges.. Beitrag in Brazilian Symposium on Remote Sensing, Florianópolis, Brasilien.
Fernandes do Amaral, F. H., Pacheco Quevedo, R., & Piroli, E. L. (2023). Floresta aleatória aplicada ao mapeamento de suscetibilidade a movimento de massa na bacia hidrográfica do rio Palena, Chile.. Beitrag in Brazilian Symposium on Remote Sensing, Florianópolis, Brasilien.
Paes Leme Passos Corrêa, S., Pacheco Quevedo, R., de Paula dos Santos, A., & Sanches Abreu, M. V. (2023). O que define um bom mapa?. Beitrag in Brazilian Symposium on Remote Sensing, Florianópolis, Brasilien.
Pacheco Quevedo, R., Oighenstein Anderson, L., Lopes Gonçalves Horta, I. T., Velastegui-Montoya, A., Quintella Veiga, R., Cardozo, C. P., & Sparrow, S. (2023). The relationship between landslide occurrence and land use and land cover.. Beitrag in Brazilian Symposium on Remote Sensing, Florianópolis, Brasilien.
Quevedo, R. P., Maciel, D. A., Uehara, T. D. T., Vojtek, M., Rennó, C. D., Pradhan, B., Vojteková, J., & Pham, Q. B. (2022). Consideration of spatial heterogeneity in landslide susceptibility mapping using geographical random forest model. Geocarto International, 37(25), 8190-8213. https://doi.org/10.1080/10106049.2021.1996637
Zhang, T., Fu, Q., Li, C., Liu, F., Wang, H., Han, L., Quevedo, R. P., Chen, T., & Lei, N. (2022). Modeling landslide susceptibility using data mining techniques of kernel logistic regression, fuzzy unordered rule induction algorithm, SysFor and random forest. Natural Hazards, 114, 3327-3358. https://doi.org/10.1007/S11069-022-05756-3, https://doi.org/10.1007/s11069-022-05520-7
Velastegui-Montoya, A., Rivera-Torres, H., Herrera-Matamoros, V., Sadeck, L., & Quevedo, R. P. (2022). Application of Google Earth Engine for land Cover Classification in Yasuni National Park, Ecuador. 6376-6379. Beitrag in 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia. https://doi.org/10.1109/igarss46834.2022.9884886
Zhang, T., Fu, Q., Pacheco Quevedo, R., Chen, T., Luo, D., Liu, F., & Kong, H. (2022). Landslide Susceptibility Mapping Using Novel Hybrid Model Based on Different Mapping Units. KSCE Journal of Civil Engineering, 26(6), 2888-2900. https://doi.org/10.1007/s12205-022-1471-9
Althuwaynee, O., Melillo, M., Gariano, S. L., Lombardo, L., Park, H. J., Kim, S.-W., Hader, P., Mohajane, M., Quevedo, R. P., Catani, F., & Aydda, A. (2022). DEWS: a QGIS tool pack for the automatic selection of reference rain gauges for landslide-triggering rainfall thresholds. EGU General Assembly 2022, Vienna, Österreich. https://doi.org/10.5194/egusphere-egu22-2774
Zhang, T., Pacheco Quevedo, R., Wang, H., Fu, Q., Luo, D., Wang, T., Garcia de Oliveira, G., Guasselli, L. A., & Daleles Rennó, C. (2022). Improved tree-based machine learning algorithms combining with bagging strategy for landslide susceptibility modeling. Arabian Journal of Geosciences. https://doi.org/10.1007/s12517-022-09488-3
Institut für Geographie und Regionalforschung
Universitätsstraße 7 (NIG)
1010 Wien
Zimmer: A0508
T: +43-1-4277-48755