Research Project
This project is funded by the ERC Consolidator Grant. It assesses the potential of using crowdsourcing to close big data gaps of ground sourced data on land cover, land use and change. The project builds on the Geo-Wiki crowdsourcing tool and moves from an online environment to a mobile ground-based collection system.
Research Project
The LACO-Wiki project will integrate the current LACOVAL (LAnd Cover VALidation) software prototype for the validation of land cover maps with Geo-Wiki, a visualization and crowdsourcing tool. The result will be an open access on-line validation platform offering standardized validation functionality for map users and producers.
Research Project
The CrowdVal project has developed innovative tools for data collection by the crowd; these have been demonstrated in three African countries for in situ data collection as well as an online data collection exercise using visual interpretation, leading to the validation of the first 20 m land cover map of Africa.
Research Project
The SIGMA project provides EU support to the international GEOGLAM (Group on Earth Observations Global Agricultural Monitoring) initiative, which together will strengthen the international community’s capacity to produce and disseminate relevant, timely and accurate forecasts of agricultural production at national, regional and global scales using Earth Observation.
Research Project
This project is funded by the Government of Norway’s International Climate and Forest Initiative (NORAD). It aims to build an independent alliance that can efficiently monitor forest governance in the DRC and to promote the conservation of natural forests to maintain their carbon storage capacity particularly in REDD+ areas.
Research Project
The Citizens for Copernicus (C4C) project, coordinated by the IIASA Novel Data Ecosystems for Sustainability Research Group in the Advancing Systems Analysis Program, aims to develop an Austrian citizen science data component to bridge the in situ data gap for more reliable forest mapping with Copernicus data. The project focuses on the combined use of citizen science and satellite images to develop AI models for forest resource (biomass/carbon) monitoring.