Stefanos Georganos
Stefanos Georganos
Senior Lecturer, Karlstad University, Geomatics Unit /Affiliate with ULB
Verified email at - Homepage
Cited by
Cited by
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
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, 2021
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
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
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
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
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
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
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
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
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
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
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
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
A local segmentation parameter optimization approach for mapping heterogeneous urban environments using VHR imagery
T Grippa, S Georganos, M Lennert, S Vanhuysse, E Wolff
Remote Sensing Technologies and Applications in Urban Environments II 10431 …, 2017
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
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
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
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
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
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