Parties d'ouvrages collectifs (1)
  1. 1. Kuffer, M. M., Grippa, T., Persello, C., Taubenböck, H. T., Pfeffer, K., & Sliuzas, R. (2021). Mapping the Morphology of Urban Deprivation: The Role of Remote Sensing for Developing a Global Slum Repository. In X. Yang (Ed.), Urban Remote Sensing (2 ed., p. 528). John Wiley & Sons.
    2.   Articles dans des revues avec comité de lecture (35)
  2. 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
  3. 2. Demissie, B., Vanhuysse, S., Grippa, T., Flasse, C., & Wolff, E. (2023). Using Sentinel-1 and Google Earth Engine cloud computing for detecting historical flood hazards in tropical urban regions: a case of Dar es Salaam. Geomatics, Natural Hazards and Risk, 14(1). doi:10.1080/19475705.2023.2202296
  4. 3. 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. 4. Grippa, T., & Dobruszkes, F. (2023). You’re Surrounded! Measuring the Enclosure of Airports in Urban Areas. The Professional geographer, 75(1), 102-117. doi:10.1080/00330124.2022.2081226
  6. 5. Wyard, C. W., Beaumont, B., Grippa, T., & Hallot, E. (2022). UAV-Based Landfill Land Cover Mapping: Optimizing Data Acquisition and Open-Source Processing Protocols. Drones, 6(5), 123. doi:10.3390/drones6050123
  7. 6. Dobruszkes, F., Grippa, T., Hanaoka, S., Loko, Y. B., Redondi, R., Vowles, T., & Wang, J. (2021). Multiple-airport systems: The (re)development of older airports in view of noise pollution issues. Transport policy. doi:10.1016/j.tranpol.2021.10.013
  8. 7. 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
  9. 8. 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
  10. 9. Flasse, C., Grippa, T., & Fennia, S. (2021). A tool for machine learning based dasymetric mapping approaches in GRASS GIS. The international archives of the photogrammetry, remote sensing and spatial information sciences, XLVI-4/W2-2021, 55-62. doi:10.5194/isprs-archives-XLVI-4-W2-2021-55-2021
  11. 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
  12. 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
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