Ta´s Grippa
Ta´s Grippa
PhD, Department of Geoscience Environment & Society, UniversitÚ Libre de Bruxelles
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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 55 (2), 221-242, 2018
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
An open-source semi-automated processing chain for urban object-based classification
T Grippa, M Lennert, B Beaumont, S Vanhuysse, N Stephenne, E Wolff
Remote Sensing 9 (4), 358, 2017
The role of earth observation in an integrated deprived area mapping “system” for low-to-middle income countries
M Kuffer, DR Thomson, G Boo, R Mahabir, T Grippa, S Vanhuysse, ...
Remote sensing 12 (6), 982, 2020
Need for an integrated deprived area “slum” mapping system (IDEAMAPS) in low-and middle-income countries (LMICs)
DR Thomson, M Kuffer, G Boo, B Hati, T Grippa, H Elsey, C Linard, ...
Social Sciences 9 (5), 80, 2020
Mouvements migratoires et dynamiques des quartiers Ó Bruxelles
G Van Hamme, T Grippa, M Van Criekingen
Brussels studies, 2016
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 10431á…, 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
Toward an operational framework for fine-scale urban land-cover mapping in Wallonia using submeter remote sensing and ancillary vector data
B Beaumont, T Grippa, M Lennert, S Vanhuysse, N Stephenne, E Wolff
Journal of Applied Remote Sensing 11 (3), 036011-036011, 2017
Modelling and mapping the intra-urban spatial distribution of Plasmodium falciparum parasite rate using very-high-resolution satellite derived indicators
S Georganos, O Brousse, S Dujardin, C Linard, D Casey, M Milliones, ...
International journal of health geographics 19 (1), 1-18, 2020
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