The project seeks to provide continuous updates on landscape changes by integrating satellite data with OpenStreetMap (OSM) information. LaVerDi (Landschaftveränderungsdienst) is a service offering free access to geodata on landscape changes in Germany, available to institutions and the public. Since late 2020, the Federal Agency for Cartography and Geodesy (BKG) has been hosting LaVerDi as an operational online mapping service. This service leverages free Copernicus satellite data to deliver annual, automatically derived insights for regular monitoring of landscape changes in Germany.
Given the growing volume and accuracy of OSM data, especially in frequently updated urban areas, combining user-contributed information with satellite-derived data presents an opportunity to detect landscape changes more effectively. This approach enables higher update frequencies, potentially even continuous monitoring. Additionally, the project will explore how OSM-supported methodologies can aid in identifying data updates for systems like ATKIS and LBM-DE.
Can OSM-based crowdsourcing methods improve the results of LaVerDi operated by BKG?
Is it feasible to create a nationwide, crowdsourcing-supported, quality-assured land cover dataset that is more up-to-date than the current LaVerDi service?
Explore how landscape changes or key object classes relevant to BKG (e.g., LBM-DE or CLC) can be derived and quality-checked using OSM data.
Assess how change detection insights derived from satellite data can be utilized to update OSM datasets.
Defining methodologies for integrating satellite and OSM data.
Developing machine learning techniques for real-world change detection in OSM.
Crowdsourcing validation of detected changes through MapSwipe / MapSwipe4Web. Analysis of gamification strategies to enhance user engagement, and develop a user-friendly web interface.
Deploying a mobile validation app with gamification elements and integrating LaVerDi data into OSM.
Free geoinformation, methods and software for the benefit of the environment and society.
Core-funded by
Background imagery created with data from OpenStreetMap contributors
