Taïs Grippa

Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling

Stefanos Georganos, Taïs Grippa, Assane Gadiaga et al. · Geocarto International · 2019 · 461 citations · Full text

Very High Resolution Object-Based Land Use–Land Cover Urban Classification Using Extreme Gradient Boosting

Stefanos Georganos, Taïs Grippa, Sabine Vanhuysse et al. · IEEE Geoscience and Remote Sensing Letters · 2018 · 274 citations · Full text

High Resolution, Engineering, Machine Learning +18

Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application

Stefanos Georganos, Taïs Grippa, Sabine Vanhuysse et al. · GIScience & Remote Sensing · 2017 · 232 citations · Full text

Engineering, Machine Learning, Feature Detection +17

Mapping Urban Land Use at Street Block Level Using OpenStreetMap, Remote Sensing Data, and Spatial Metrics

Taïs Grippa, Stefanos Georganos, Soukaina Zarougui et al. · ISPRS International Journal of Geo-Information · 2018 · 109 citations · Full text

Engineering, Land Use, Land Cover +22

An Open-Source Semi-Automated Processing Chain for Urban Object-Based Classification

Taïs Grippa, Moritz Lennert, Benjamin Beaumont et al. · Remote Sensing · 2017 · 81 citations · Full text

Precision Agriculture, Engineering, Object Categorization +22