Exploring inference of a land use and land cover model trained on MultiSenGE dataset. - Romain Wenger; Anne Puissant; Jonathan Weber; Lhassane Idoumghar; Germain Forestier (JURSE, 2023)

Contribution of Sentinel-1&2 imagery and deep learning methods for land use land cover mapping and monitoring. (Apport des images Sentinel-1&2 et des méthodes d'apprentissage profond pour la cartographie et le suivi des modes d'occupation des sols). - Romain Wenger (2023)

Multimodal and Multitemporal Land Use/Land Cover Semantic Segmentation on Sentinel-1 and Sentinel-2 Imagery: An Application on a MultiSenGE Dataset. - Romain Wenger; Anne Puissant; Jonathan Weber; Lhassane Idoumghar; Germain Forestier (Remote. Sens., 2023)

Improving Urban Tree Species Classification with High Resolution Satellite Imagery and Machine Learning. - Romain Wenger; Clément Bressant; Lucie Roettele; Germain Forestier; Anne Puissant (IGARSS, 2024)

PickShift: A user-friendly Python tool to assess the surficial uncertainties associated with polygons extracted from historical planimetric data. - Timothée Jautzy; Pierrick Freys; Valentin Chardon; Romain Wenger; Gilles Rixhon; Laurent Schmitt; Pierre-Alexis Herrault (SoftwareX, 2024)

Urban trees species classification using Sentinel-2 and Planetscope satellite image time series. - Marie Latil; Romain Wenger; David Michéa; Germain Forestier; Anne Puissant (JURSE, 2025)

Automatic detection of in-stream river wood from random forest machine learning and exogenous indices using very high-resolution aerial imagery. - Gauthier Grimmer; Romain Wenger; Germain Forestier; Valentin Chardon (Environ. Model. Softw., 2025)

RiverDetectWood: A tool for automatic classification and quantification of river wood in river systems using aerial imagery. - Gauthier Grimmer; Romain Wenger; Valentin Chardon (SoftwareX, 2025)