Laboratory of Geo-information Science and Remote Sensing
The mission of the Laboratory of Geo-information Science and Remote Sensing is to improve spatial competences for a sustainable world through research and education.
Inaugural lectures
Education
In the field of education, the Laboratory is strongly participating in the Master Geo-Information Science.
More Education
Research
Geo-information has become a societal commodity and geo-information science is the driver of its innovation. This trend is evident in the activities of the Laboratory of Geo-Information Science and Remote Sensing (GRS).
Our research aims to Realize the Digital Earth of Locations.
Research topics
- Sensing & measuring
- Modelling & visualization
- Integrated land monitoring
- Human - space interaction
- Empowering & engaging communities
Latest PhD dissertations
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Crop load estimation in orchards: the potential of single RGB images from unmanned aerial vehicles
Wageningen University. Promotor(en): L. Kooistra, co-promotor(en): W. Wang, J. Valente, L. Guo - Wageningen: Wageningen University - ISBN: 9789464478716 -
Landscape quality assessments using deep learning
Wageningen University. Promotor(en): D. Tuia, co-promotor(en): D. Marcos - Wageningen: Wageningen University - ISBN: 9789464471687 -
Temporally-dense multi-source satellite remote sensing for advancing the monitoring and characterization of tropical forest disturbances
Wageningen University. Promotor(en): M. Herold, co-promotor(en): J. Reiche - Wageningen: Wageningen University - ISBN: 9789464470536
Latest publications
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DTM resolution controls the accuracy of estimating surface runoff indicators in flat, lowland landscapes
Hydrological Processes (2024), Volume: 38, Issue: 5 - ISSN 0885-6087 -
Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-series at 250 m spatial resolution
PeerJ (2024), Volume: 12 - ISSN 2167-8359 -
Virtual Reality for Spatial Planning and Emergency Situations : Challenges and Solution Directions
Applied Sciences (Switzerland) (2024), Volume: 14, Issue: 9 - ISSN 2076-3417 -
Analysis and Comparison of New-Born Calf Standing and Lying Time Based on Deep Learning
Animals (2024), Volume: 14, Issue: 9 - ISSN 2076-2615 -
Panarchy to explore land use : a historical case study from the Peruvian Amazon
Sustainability Science (2024), Volume: 19, Issue: 4 - ISSN 1862-4065 - p. 1187-1203.