Articles dans des revues avec comité de lecture (61)
  1. 1. 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
  2. 2. Dellicour, S., Linard, C., Van Goethem, N., Da Re, D., Artois, J., Bihin, J., Schaus, P., Massonnet, F., Van Oyen, H., Vanwambeke, S., Speybroeck, N., & Gilbert, M. (2021). Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence—Belgium as a study case. International Journal of Health Geographics, 20(1), 29. doi:10.1186/s12942-021-00281-1
  3. 3. 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
  4. 4. 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
  5. 5. Forget, Y., Shimoni, M., Gilbert, M., & Linard, C. (2021). Mapping 20 years of urban expansion in 45 urban areas of sub-Saharan Africa. Remote Sensing, 13(3), 525. doi:10.3390/rs13030525
  6. 6. 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
  7. 7. 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
  8. 8. Thomson, D., Kuffer, M. M., Boo, G., Hati, B., Grippa, T., Elsey, H., Linard, C., Mahabir, R., Kyobutungi, C., Maviti, J., Mwaniki, D., Ndugwa, R., Makau, J., Sliuzas, R., Cheruiyot, S., Nyambuga, K., Mboga, N. O., Kimani, N. W., de Albuquerque, J. P., & Kabaria, C. C. (2020). Need for an integrated deprived area "slum" mapping system (IDEAMAPS) in low-and middle-income countries (LMICS). Social Sciences, 9(5), 80. doi:10.3390/SOCSCI9050080
  9. 9. Vanwambeke, S., Linard, C., Gilbert, M., & Dellicour, S. (2020). SARS-CoV-2 emergence and diffusion: a new disease manifesting human–environment interactions and a global geography of health. Current Opinion in Environmental Sustainability. doi:10.1016/j.cosust.2020.10.011
  10. 10. 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
  11. 11. Thomson, D., Kuffer, M. M., Boo, G., Hati, B., Grippa, T., Elsey, H., Linard, C., Mahabir, R., Kyobutungi, C., Mulandi, J., Mwaniki, D., Ndugwa, R., Makau, J., Sliuzas, R., Cheruiyot, S., Nyambuga, K., Mboga, N. O., Wanjiru, N., De Albuquerque, J. P., & Kabaria, C. (2019). Critical Commentary: Need for an Integrated Deprived Area "Slum" Mapping System (IDeAMapS) in LMICs. Preprints. doi:10.20944/preprints201910.0242.v1
  12. 12. 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
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