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.
People
Vacancy
Assistant Professor Geo-Information Science
Read moreNews
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Urban tourism: Developing a model framework to explore spatio-temporal patterns of pedestrian tourist in Amsterdam -
Estimating aboveground net biomass change for tropical and subtropical forests: refinement of IPCC default rates using forest plot data -
Nonlinear Feature Normalization for Hyperspectral Domain Adaptation and Mitigation of Nonlinear Effects -
The Role and Need for Space-Based Forest Biomass-Related Measurements in Environmental Management and Policy -
Upscaling Forest Biomass from Field to Satellite Measurements: Sources of Errors and Ways to Reduce Them
Agenda
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
Projects & Facilities
Key publications
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Cooperation can improve the resilience of common-pool resource systems against over-harvesting
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Roles and drivers of agribusiness shaping Climate-Smart Landscapes : A review
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Evolving Spatial Data Infrastructures and the Role of Adaptive Governance
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Intercomparison of unmanned aerial vehicle and ground-based narrow band spectrometers applied to crop trait monitoring in organic potato production
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Large scale land acquisitions and REDD+: a synthesis of conflicts and opportunities
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Mapping reflectance anisotropy of a potato canopy using aerial images acquired with an unmanned aerial vehicle
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Using Sentinel-2 data for retrieving LAI and leaf and canopy chlorophyll content of a potato crop
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Using space-time features to improve detection of forest disturbances from Landsat time series
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What are the prospects for citizen science in agriculture? Evidence from three continents on motivation and mobile telephone use of resource-poor farmers