ILUS 2025, organized by Leibniz Institute of Ecological Urban and Regional Development (IOER) and Research Area Spatial Information and Modelling, fosters an interdisciplinary dialogue on spatial dynamics of urban societies, emphasizing the role of geospatial data, analysis, modeling, and simulation in understanding and shaping urban processes. Particular focus will be on emerging approaches that bridge disciplines and address the complexities if contemporary urban environments.
HeiGIT contributes with the following presentation about the LaVerDi project:
Integrating OpenStreetMap and Satellite Data for Automated Landscape Change Detection: A Machine Learning Approach to Crowdsourced Land Use Monitoring – Mohammed Rizwan Khan, Benjamin Herfort
DT4: Digital Twins and Decision Making
07/Nov/2025: 3:45pm-5:15pm
In this presentation, Mohammed Rizwan Khan and Benjamin Herfort introduce an approach that integrates crowdsourced OpenStreetMap (OSM) data with satellite imagery to enhance land use and land cover (LULC) change detection. Building for the LaVerDi (Landschaftveränderungsdienst) operational service framework provided by Bundesamt für Kartographie und Geodäsie (BKG), the aim is to develop a machine learning pipeline that leverages the complementary strengths of both data sources for improved land use/land cover (LULC) change detection.
We are looking forward to great discussions and new insights.
Read more about LaVerDI.