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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Aboveground carbon stocks and sinks in recovering tropical forests
Wageningen University. Promotor(en): M. Herold, co-promotor(en): V. De Sy, D.M.A. Rozendaal - Wageningen: Wageningen University - ISBN: 9789463958905 -
Mapping of urban landuse and landcover with multiple sensors : Joining close and remote sensing with deep learning
Wageningen University. Promotor(en): D. Tuia - Wageningen: Wageningen University - ISBN: 9789463952514 -
Towards performance assessment of subnational forest-based climate change mitigation initiatives
Wageningen University. Promotor(en): M. Herold, co-promotor(en): V. De Sy, A.E. Duchelle - Wageningen: Wageningen University - ISBN: 9789463952149
Latest publications
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An assessment of recent peat forest disturbances and their drivers in the Cuvette Centrale, Africa
Environmental Research Letters (2024), Volume: 19, Issue: 10 - ISSN 1748-9326 -
Designing affective workplace environments : The impact of typology, contour, ceiling and partition height on cognitive and aesthetic appraisal
Building and Environment (2024), Volume: 265 - ISSN 0360-1323 -
New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests
Global Change Biology (2024), Volume: 30, Issue: 8 - ISSN 1354-1013 -
Relationships between geo-spatial features and COVID-19 hospitalisations revealed by machine learning models and SHAP values
International Journal of Digital Earth (2024), Volume: 17, Issue: 1 - ISSN 1753-8947 -
Supporting stakeholder dialogue on ecosystem service tradeoffs with a simulation tool for land use configuration effects
Environmental Modelling and Software (2024), Volume: 179 - ISSN 1364-8152