Geo-Wiki: An online platform for improving global land cover. - Steffen Fritz; Ian McCallum; Christian Schill; Christoph Perger; Linda See; Dmitry Schepaschenko; Marijn Van der Velde; Florian Kraxner; Michael Obersteiner (Environ. Model. Softw., 2012)

Using control data to determine the reliability of volunteered geographic information about land cover. - Alexis J. Comber; Linda M. See; Steffen Fritz; Marijn Van der Velde; Christoph Perger; Giles M. Foody (Int. J. Appl. Earth Obs. Geoinformation, 2013)

Assessing the Accuracy of Volunteered Geographic Information arising from Multiple Contributors to an Internet Based Collaborative Project. - Giles M. Foody; Linda M. See; Steffen Fritz; Marijn Van der Velde; Christoph Perger; Christian Schill; Doreen S. Boyd (Trans. GIS, 2013)

Framework for minimising the impact of regional shocks on global food security using multi-objective ant colony optimisation. - Peter Golding; Sam Kapadia; Stella Naylor; Jonathan Schulz; Holger R. Maier; Upmanu Lall; Marijn Van der Velde (Environ. Model. Softw., 2017)

Targeted Grassland Monitoring at Parcel Level Using Sentinels, Street-Level Images and Field Observations. - Raphaël d'Andrimont; Guido Lemoine; Marijn Van der Velde (Remote. Sens., 2018)

A Crop Group-Specific Pure Pixel Time Series for Europe. - Christof J. Weissteiner; Raul Lopez-Lozano; Giacinto Manfron; Grégory Duveiller; Josh Hooker; Marijn Van der Velde; Bettina Baruth (Remote. Sens., 2019)

Accuracy Assessment of the First Eu-Wide Crop Type Map with Lucas Data. - Astrid Verhegghen; Raphaël d'Andrimont; François Waldner; Marijn Van der Velde (IGARSS, 2021)

From parcel to continental scale - A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations. - Raphaël d'Andrimont; Astrid Verhegghen; Guido Lemoine; Pieter Kempeneers; Michele Meroni; Marijn Van der Velde (CoRR, 2021)

Monitoring crop phenology with street-level imagery using computer vision. - Raphaël d'Andrimont; Momchil Yordanov; Laura Martinez-Sanchez; Marijn Van der Velde (Comput. Electron. Agric., 2022)

Skyline variations allow estimating distance to trees on landscape photos using semantic segmentation. - Laura Martinez-Sanchez; Daniele Borio; Raphaël d'Andrimont; Marijn Van der Velde (Ecol. Informatics, 2022)

Assessing crop diversity across scales using high-resolution remote sensing over the European Union: first insights for agro-environmental policies. - Mélissande Machefer; Matteo Zampieri; Marijn Van der Velde; Frank Dentener; Martin Claverie; Raphaël d'Andrimont (CoRR, 2023)

Crop Identification Using Deep Learning on LUCAS Crop Cover Photos. - Momchil Yordanov; Raphaël d'Andrimont; Laura Martinez-Sanchez; Guido Lemoine; Dominique Fasbender; Marijn Van der Velde (Sensors, 2023)

Automatic detection of charcoal kilns on Very High Resolution images with a computer vision approach in Somalia. - Astrid Verhegghen; Laura Martinez-Sanchez; Michele Bolognesi; Michele Meroni; Felix Rembold; Petar Vojnovic; Marijn Van der Velde (Int. J. Appl. Earth Obs. Geoinformation, 2023)

Automatic classification of land cover from LUCAS in-situ landscape photos using semantic segmentation and a Random Forest model. - Laura Martinez-Sanchez; Linda See; Momchil Yordanov; Astrid Verhegghen; Neija Elvekjaer; Davide Muraro; Raphaël d'Andrimont; Marijn Van der Velde (Environ. Model. Softw., 2024)