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.
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Education
In the field of education, the Laboratory is strongly participating in the Master Geo-Information Science.
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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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Integrating UAV-based LiDAR and 3D computer vision to enhance cattle growth monitoring in precision livestock farming
Wageningen University. Promotor(en): Lammert Kooistra, Wensheng Wang, co-promotor(en): Caspar Alexander Mücher - Wageningen: Wageningen University - ISBN: 9789465104041 -
The changing face of smallholder farming : Insights from an Amazonian landscape in transition
Wageningen University. Promotor(en): Katrien K.E. Descheemaeker, co-promotor(en): Erika N. Speelman, Daniel Callo-Concha - Wageningen: Wageningen University -
Landscape quality assessments using deep learning
Wageningen University. Promotor(en): D. Tuia, co-promotor(en): D. Marcos - Wageningen: Wageningen University - ISBN: 9789464471687
Latest publications
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Comparative analysis of single-view and multiple-view data collection strategies for detecting partially-occluded grape bunches: Field trials
Journal of Agriculture and Food Research (2025), Volume: 19 - ISSN 2666-1543 -
Being there : effectiveness of a 360-degree virtual tour for increasing understanding of forest treatments for fire hazard reduction in California, USA
Fire Ecology (2025), Volume: 21 - ISSN 1933-9747 -
Body Weight Estimation of Cattle in Standing and Lying Postures Using Point Clouds Derived from Unmanned Aerial Vehicle-Based LiDAR
Drones (2025), Volume: 9, Issue: 2 - ISSN 2504-446X -
Do urban digital twins need agents?
Environment and Planning B: Urban Analytics and City Science (2025) - ISSN 2399-8083 -
Time series of Landsat-based bimonthly and annual spectral indices for continental Europe for 2000–2022
Earth System Science Data (2025), Volume: 17, Issue: 2 - ISSN 1866-3508 - p. 741-772.