Human activities on the Earth’s surface continue to accelerate, where future impacts in terms of deforestation, biodiversity, climate and social-economic processes are still far from known.
Monitoring and modelling these processes is increasingly carried out within a multidisciplinary approach where remote sensing and geo-information science plays a key role, providing processing and analysis of spatially explicit information at scales varying from local to global.
As a multidisciplinary group, the Laboratory for Geo-information Science and Remote Sensing links to various scientific fields to study, understand and manage human impact on landscapes, ecosystem services and to support sustainable and climate-friendly future developments. Within this theme we focus on three main topics:
- Development of novel approaches for the assessment of land change dynamics on multiple scales;
- Integration of earth observation data and products in interdisciplinary research, models and applications;
- Monitoring and modelling the influence of climate and humans on terrestrial ecosystems.
Dedicated research activities are ongoing in the real-time monitoring of global deforestation and forest degradation, precision agriculture, tracking of forest carbon, land use change and greenhouse gas emissions, remote sensing support for ecological modelling, and mapping and assessment of soil properties.
- Karina Winkler: A data-driven reconstruction of global land use change from 1960-2015 and its linkage with land management.
- Arnan Araza: Biomass remote sensing for improving forest carbon and hydrological modelling.
- Daniela Requena Suarez: Tropical forest cover gain and carbon sequestration for climate change mitigation.
- Sabina Rosca: Large scale forest change monitoring using satellite data
- Dainius Masiliunas: Large-scale land cover change monitoring from dense time series of satellite data
- Paulo Negri Bernardino
- Maria da Conceição Pereira: Linking REDD+ monitoring and implementation in forests and agriculture of Southern Africa
- Marcio Sales: Pre-Assessment of the value of remote sensing derived data for reducing uncertainty about carbon emissions estimation in Brazil
- Jose Gonzalez de Tanago: Improving GHG emission factors for various forest change processes
- Lorenzo Vita: Dynamics of land use change and the consequences on forest characteristics: the case of Mau Forest, Kenia
- Valerio Avitabile: Improving pan-tropical forest biomass mapping: a fusion approach
- Kathleen Neumann (VENI grant): Rural migration and environmental degradation: A vicious cycle?
Recently finished PhDs:
A data-driven reconstruction of historic land cover/use change of Europe for the period 1900 to 2010Wageningen University. Promotor(en): Martin Herold, co-promotor(en): Peter Verburg; Jan Clevers. - Wageningen : Wageningen University - ISBN 9789462574632 - p.
Interactive community-based tropical forest monitoring using emerging technologiesWageningen University. Promotor(en): Martin Herold, co-promotor(en): L. Ribbe; Sytze de Bruin; Valerio Avitabile. - Wageningen : Wageningen University - ISBN 9789462574786 - p.
Combining SAR and optical satellite image time series for tropical forest monitoringWageningen University. Promotor(en): Martin Herold, co-promotor(en): Dirk Hoekman; Jan Verbesselt. - Wageningen : Wageningen University - ISBN 9789462573130 - p.
Improving near-real time deforestation monitoring in tropical dry forests by combining dense Sentinel-1 time series with Landsat and ALOS-2 PALSAR-2Remote Sensing of Environment 204 (2018). - ISSN 0034-4257 - p. 147 - 161.
Using space-time features to improve detection of forest disturbances from Landsat time seriesRemote Sensing 9 (2017)6. - ISSN 2072-4292
Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation MonitoringRemote Sensing 9 (2017)10. - ISSN 2072-4292 - 17 p.
An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributorGlobal Change Biology 23 (2017)9. - ISSN 1354-1013 - p. 3581 - 3599.
Connecting Earth observation to high-throughput biodiversity dataNature Ecology & Evolution 1 (2017)7. - ISSN 2397-334X - 9 p.
Land management: data availability and process understanding for global change studiesGlobal Change Biology 23 (2017)2. - ISSN 1354-1013 - p. 512 - 533.
An integrated pan-tropical biomass map using multiple reference datasetsGlobal Change Biology 22 (2016)4. - ISSN 1354-1013 - p. 1406 - 1420.
Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time SeriesPLoS ONE 11 (2016)3. - ISSN 1932-6203
Combining satellite data for better tropical forest monitoringNature Climate Change 6 (2016)2. - ISSN 1758-678X - p. 120 - 122.
Trend change detection in NDVI time series: Effects of inter-annual variability and methodologyRemote Sensing 5 (2013)5. - ISSN 2072-4292 - p. 2113 - 2144.