| Spatial and temporal deep learning methods for deriving land-use following deforestation: A pan-tropical case study using Landsat time series RN Masolele, V De Sy, M Herold, D Marcos, J Verbesselt, F Gieseke, ... Remote Sensing of Environment 264, 112600, 2021 | 77 | 2021 |
| Using high-resolution imagery and deep learning to classify land-use following deforestation: a case study in Ethiopia RN Masolele, V De Sy, D Marcos, J Verbesselt, F Gieseke, KA Mulatu, ... GIScience & Remote Sensing 59 (1), 1446-1472, 2022 | 13 | 2022 |
| Mapping the diversity of land uses following deforestation across Africa RN Masolele, D Marcos, V De Sy, IO Abu, J Verbesselt, J Reiche, ... Scientific Reports 14 (1), 1681, 2024 | 9 | 2024 |
| ALOS-2 PALSAR-2 L-band cross-polarized radar data analysis for modelling above-ground biomass/carbon stock and carbon sequestration of tropical rainforest, Berkelah, Malaysia RN Masolele University of Twente, 2018 | 5 | 2018 |
| Integrating satellite-based forest disturbance alerts improves detection timeliness and confidence J Reiche, J Balling, AH Pickens, RN Masolele, A Berger, MJ Weisse, ... Environmental Research Letters 19 (5), 054011, 2024 | | 2024 |
| Artisanal Mining Triggers Deforestation in the Democratic Republic of Congo M Ladewig, R Masolele, C Chervier, A Angelsen | | 2024 |
| Assessing land use following tropical deforestation: Combining remote sensing and deep learning RN Masolele PQDT-Global, 2023 | | 2023 |
