Contributions to collective works (2)
  1. 1. Abascal, A., Georganos, S., Kuffer, M. M., Vanhuysse, S., Thomson, D., Wang, J., Manyasi, L., Otunga, D. M., Ochieng, B., Ochieng, T., Klinnert, J., & Wolff, E. (2024). Making Urban Slum Population Visible: Citizens and Satellites to Reinforce Slum Censuses. In Urban Inequalities from Space: Earth Observation Applications in the Majority World (pp. 287-302). Springer International Publishing. doi:10.1007/978-3-031-49183-2_14
  2. 2. Kuffer, M. M., Abascal, A., Vanhuysse, S., Georganos, S., Wang, J., Thomson, D. R., Boanada, A., & Roca, P. (2023). Data and Urban Poverty: Detecting and Characterising Slums and Deprived Urban Areas in Low- and Middle-Income Countries. In Advanced Remote Sensing for Urban and Landscape Ecology (pp. 1-22). Springer Nature Singapore. doi:10.1007/978-981-99-3006-7_1
    3.   Peer-reviewed journal articles (28)
  3. 1. Abascal, A., Vanhuysse, S., Grippa, T., Rodriguez-Carreño, I., Georganos, S., Wang, J., Kuffer, M. M., Martinez-Diez, P., Santamaria-Varas, M., & Wolff, E. (2024). AI perceives like a local: predicting citizen deprivation perception using satellite imagery. npj urban sustainability, 4(1). doi:10.1038/s42949-024-00156-x
  4. 2. Vanhuysse, S., Diédhiou, S. M., Grippa, T., Georganos, S., Konaté, L., Niang, E. H. A., & Wolff, E. (2023). Fine-scale mapping of urban malaria exposure under data scarcity: an approach centred on vector ecology. Malaria journal, 22(1). doi:10.1186/s12936-023-04527-0
  5. 3. Morlighem, C., Chaiban, C., Georganos, S., Brousse, O., Van de Walle, J., Van Lipzig, N. P. M., Wolff, E., Dujardin, S., & Linard, C. (2022). The Multi-Satellite Environmental and Socioeconomic Predictors of Vector-Borne Diseases in African Cities: Malaria as an Example. Remote Sensing, 14(21), 5381. doi:10.3390/rs14215381
  6. 4. Wang, J., Georganos, S., Kuffer, M. M., Abascal, A., & Vanhuysse, S. (2022). On the knowledge gain of urban morphology from space. Computers, environment and urban systems, 95, 101831. doi:10.1016/j.compenvurbsys.2022.101831
  7. 5. Abascal, A., Rodríguez-Carreño, I., Vanhuysse, S., Georganos, S., Sliuzas, R., Wolff, E., & Kuffer, M. M. (2022). Identifying degrees of deprivation from space using deep learning and morphological spatial analysis of deprived urban areas. Computers, environment and urban systems, 95, 101820. doi:10.1016/j.compenvurbsys.2022.101820
  8. 6. Georganos, S., Abascal, A., Kuffer, M. M., Wang, J., Owusu, M., Wolff, E., & Vanhuysse, S. (2021). Is it all the same? Mapping and characterizing deprived urban areas using worldview-3 superspectral imagery. a case study in nairobi, kenya. Remote Sensing, 13(24), 4986. doi:10.3390/rs13244986
  9. 7. Kuffer, M. M., Wang, J., Thomson, D. R., Georganos, S., Abascal, A., Owusu, M., & Vanhuysse, S. (2021). Spatial Information Gaps on Deprived Urban Areas (Slums) in Low-and-Middle-Income-Countries: A User-Centered Approach. Urban Science, 5(4), 72. doi:10.3390/urbansci5040072
  10. 8. Owusu, M., Kuffer, M. M., Belgiu, M., Grippa, T., Lennert, M., Georganos, S., & Vanhuysse, S. (2021). Towards user-driven earth observation-based slum mapping. Computers, environment and urban systems, 89, 101681. doi:10.1016/j.compenvurbsys.2021.101681
  11. 9. Mboga, N. O., D’Aronco, S., Grippa, T., Pelletier, C., Georganos, S., Vanhuysse, S., Wolff, E., Smets, B., Dewitte, O., Lennert, M., & Wegner, J. D. (2021). Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa. ISPRS International Journal of Geo-Information, 10(8), 523. doi:10.3390/ijgi10080523
  12. 10. Gadiaga, A., De Longueville, F., Georganos, S., Grippa, T., Dujardin, S., Diène, A. N., Masquelier, B., Diallo, M., & Linard, C. (2021). Neighbourhood-level housing quality indices for health assessment in Dakar, Senegal. Geospatial Health, 16(1), 910. doi:10.4081/gh.2021.910
  13. 11. Georganos, S., Grippa, T., Niang Gadiaga, A., Linard, C., Lennert, M., Vanhuysse, S., Mboga, N. O., Wolff, E., & Kalogirou, S. (2021). Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling. Geocarto international, 36(2), 121-136. doi:doi.org/10.1080/101106049.2019.1595177
  14. 12. Kuffer, M. M., Vanhuysse, S., Georganos, S., & Wang, J. (2021). Meeting user requirements for mapping and characterizing deprived urban areas in support of pro-poor policies. GI_Forum, 9(1), 85-93. doi:10.1553/GISCIENCE2021_01_S85
  15. 13. Brousse, O., Georganos, S., Demuzere, M., Dujardin, S., Lennert, M., Linard, C., Snow, R. R., Thiery, W., & Van Lipzig, N. P. M. (2020). Can we use Local Climate Zones for predicting malaria prevalence across sub-Saharan African cities? Environmental Research Letters, 15(12), 124051. doi:10.1088/1748-9326/abc996
  16. 14. Georganos, S., Brousse, O., Dujardin, S., Linard, C., Casey, D., Milliones, M., Parmentier, B., Van Lipzig, N. P. M., Demuzere, M., Grippa, T., Vanhuysse, S., Mboga, N. O., Andreo, V., Snow, R. W. B. R., & Lennert, M. (2020). Modelling and mapping the intra-urban spatial distribution of Plasmodium falciparum parasite rate using very-high-resolution satellite derived indicators. International Journal of Health Geographics, 19(1), 38. doi:10.1186/s12942-020-00232-2
  17. 15. Mboga, N. O., Grippa, T., Georganos, S., Vanhuysse, S., Smets, B., Dewitte, O., Wolff, E., & Lennert, M. (2020). Fully convolutional networks for land cover classification from historical panchromatic aerial photographs. ISPRS journal of photogrammetry and remote sensing, 167, 385-395. doi:10.1016/j.isprsjprs.2020.07.005
  18. 16. Georganos, S., Gadiaga, A., Linard, C., Grippa, T., Vanhuysse, S., Mboga, N. O., Wolff, E., Dujardin, S., & Lennert, M. (2019). Modelling the Wealth Index of Demographic and Health Surveys within Cities Using Very High-Resolution Remotely Sensed Information. Remote Sensing, 11(21), 2543. doi:10.3390/rs11212543
  19. 17. Thomson, D., Linard, C., Vanhuysse, S., Steele, J., Shimoni, M., Siri, J., Caiaffa, W. T., Rosenberg, M., Wolff, E., Grippa, T., Georganos, S., & Elsey, H. (2019). Extending Data for Urban Health Decision-Making: a Menu of New and Potential Neighborhood-Level Health Determinants Datasets in LMICs. Journal of urban health, 96(4), 514-536. doi:10.1007/s11524-019-00363-3
  20. 18. Georganos, S., Grippa, T., Gadiaga, A., Linard, C., Lennert, M., Vanhuysse, S., Wolff, E., & Kalogirou, S. (2019). Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling. Geocarto international. doi:10.1080/10106049.2019.1595177
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