| Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling S Georganos, T Grippa, A Niang Gadiaga, C Linard, M Lennert, ... Geocarto International 36 (2), 121-136, 2019 | 341 | 2019 |
| Very high resolution object-based land use–land cover urban classification using extreme gradient boosting S Georganos, T Grippa, S Vanhuysse, M Lennert, M Shimoni, E Wolff IEEE geoscience and remote sensing letters 15 (4), 607-611, 2018 | 278 | 2018 |
| Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application S Georganos, T Grippa, S Vanhuysse, M Lennert, M Shimoni, S Kalogirou, ... GIScience & Remote Sensing, 2017 | 229 | 2017 |
| Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression S Georganos, AM Abdi, DE Tenenbaum, S Kalogirou Journal of Arid Environments 146, 64-74, 2017 | 120 | 2017 |
| Mapping urban land use at street block level using openstreetmap, remote sensing data, and spatial metrics T Grippa, S Georganos, S Zarougui, P Bognounou, E Diboulo, Y Forget, ... ISPRS International Journal of Geo-Information 7 (7), 246, 2018 | 112 | 2018 |
| using local climate zones in Sub-Saharan Africa to tackle urban health issues O Brousse, S Georganos, M Demuzere, S Vanhuysse, H Wouters, E Wolff, ... Urban climate 27, 227-242, 2019 | 86 | 2019 |
| Fully convolutional networks and geographic object-based image analysis for the classification of VHR imagery N Mboga, S Georganos, T Grippa, M Lennert, S Vanhuysse, E Wolff Remote Sensing 11 (5), 597, 2019 | 70 | 2019 |
| Towards user-driven earth observation-based slum mapping M Owusu, M Kuffer, M Belgiu, T Grippa, M Lennert, S Georganos, ... Computers, environment and urban systems 89, 101681, 2021 | 52 | 2021 |
| Scale matters: Spatially partitioned unsupervised segmentation parameter optimization for large and heterogeneous satellite images S Georganos, T Grippa, M Lennert, S Vanhuysse, BA Johnson, E Wolff Remote Sensing 10 (9), 1440, 2018 | 46 | 2018 |
| Identifying degrees of deprivation from space using deep learning and morphological spatial analysis of deprived urban areas A Abascal, I Rodríguez-Carreńo, S Vanhuysse, S Georganos, R Sliuzas, ... Computers, environment and urban systems 95, 101820, 2022 | 45 | 2022 |
| A forest of forests: a spatially weighted and computationally efficient formulation of geographical random forests S Georganos, S Kalogirou ISPRS International Journal of Geo-Information 11 (9), 471, 2022 | 42 | 2022 |
| Fully convolutional networks for land cover classification from historical panchromatic aerial photographs N Mboga, T Grippa, S Georganos, S Vanhuysse, B Smets, O Dewitte, ... ISPRS Journal of Photogrammetry and Remote Sensing 167, 385-395, 2020 | 42 | 2020 |
| Spatial information gaps on deprived urban areas (slums) in low-and-middle-income-countries: A user-centered approach M Kuffer, J Wang, DR Thomson, S Georganos, A Abascal, M Owusu, ... Urban Science 5 (4), 72, 2021 | 37 | 2021 |
| Extending data for urban health decision-making: a menu of new and potential neighborhood-level health determinants datasets in LMICs DR Thomson, C Linard, S Vanhuysse, JE Steele, M Shimoni, J Siri, ... Journal of urban health 96, 514-536, 2019 | 36 | 2019 |
| Improving urban population distribution models with very-high resolution satellite information T Grippa, C Linard, M Lennert, S Georganos, N Mboga, S Vanhuysse, ... Data 4 (1), 13, 2019 | 31 | 2019 |
| Diversity of urban growth patterns in Sub-Saharan Africa in the 1960–2010 period E Wolff, T Grippa, Y Forget, S Georganos, S Vanhuysse, M Shimoni, ... African Geographical Review 39 (1), 45-57, 2020 | 27 | 2020 |
| Modelling the wealth index of demographic and health surveys within cities using very high-resolution remotely sensed information S Georganos, AN Gadiaga, C Linard, T Grippa, S Vanhuysse, N Mboga, ... Remote Sensing 11 (21), 2543, 2019 | 27 | 2019 |
| Normalization in unsupervised segmentation parameter optimization: A solution based on local regression trend analysis S Georganos, M Lennert, T Grippa, S Vanhuysse, B Johnson, E Wolff Remote Sensing 10 (2), 222, 2018 | 26 | 2018 |
| Is it all the same? Mapping and characterizing deprived urban areas using Worldview-3 superspectral imagery. A case study in Nairobi, Kenya S Georganos, A Abascal, M Kuffer, J Wang, M Owusu, E Wolff, ... Remote Sensing 13 (24), 4986, 2021 | 24 | 2021 |
| Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities? O Brousse, S Georganos, M Demuzere, S Dujardin, M Lennert, C Linard, ... Environmental Research Letters 15 (12), 124051, 2020 | 23 | 2020 |
Taďs GrippaPhD, Department of Geoscience Environment & Society, Université Libre de BruxellesVerified email at ulb.ac.be
