Éléonore Wolff

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

Assessment of Very High Spatial Resolution Satellite Image Segmentations

Alexandre Carleer, Olivier Debeir, Éléonore Wolff · Photogrammetric Engineering & Remote Sensing · 2005 · 276 citations · Full text

Machine Vision, Image Analysis, Data Science +15

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

Monitoring grass nutrients and biomass as indicators of rangeland quality and quantity using random forest modelling and WorldView-2 data

Abel Ramoelo, Moses Azong Cho, Renaud Mathieu et al. · International Journal of Applied Earth Observation and Geoinformation · 2014 · 204 citations

Precision Agriculture, Engineering, Forest Biometrics +14