Geoinformatics Research (GIScience)

HeiGIT

We cooperate closely with the HeiGIT gGmbH at Heidelberg University. The aim of the Heidelberg Institute for Geoinformation Technology (HeiGIT) is to improve the transfer of knowledge and technology from basic geoinformatics research into practice by using innovative geoinformation technologies. It was founded in 2019 as an affiliated institute of Heidelberg University and has since then been core-funded by the Klaus Tschira Stiftung. The institute researches and develops intelligent routing and navigation services for sustainable mobility and provides geodata for humanitarian missions. In addition, innovative services from the research areas spatial data mining and machine learning are used to analyze, process, enrich and visualize user-generated geodata (e.g. OpenStreetMap).

Focus Areas:

• Smart Mobility
• Big Spatial Data Analytics
• Geoinformation for Humanitarian Aid

Current GIScience Projects

• Harnessing spatiotemporal crowdsourced data to identify key spatial and behavioral factors that inform the design and delivery of targeted public health interventions as a framework for pandemic preparedness
• GeCO: Generating high-resolution CO2 maps by Machine Learning-based geodata fusion and atmospheric transport modelling
• Climate Change and Health: Improving health care for vulnerable populations in Africa through spatially high-resolution monitoring of the natural and anthropogenic environment
• HEAL - Heat adaptation for people at-risk. A safe way through the heat: Transdisciplinary project HEAL makes everyday life easier for at-risk groups.
• geoEpi
• SocialMedia2Traffic – Derivation of traffic information from social media data
• NACHWUCHS
• LOKI – Airborne Assessment of Critical Infrastructures (BMBF)
• HCE: Klimahandeln fundiert gestalten - Fallstudie Baden-Württemberg/Kalifornien
• IDEAL-VGI – Information Discovery from Big Earth Observation Data Archives by Learning from Volunteered Geographic Information
• meinGrün - information and navigation on urban green spaces in cities
• Waterproofing Data
• DeepVGI – Deep Learning Volunteered Geographic Information
• Psychogeography – Psychoepidemiology and HealthGIS in the Metropole Region Rhein-Neckar (Psychoepidemiologisches Zentrum PEZ @ ZI Mannheim)
• OpenrouteService.org
• OSM Landuse/Landcover – Karte über Landnutzungsinformationen basierend auf OpenStreetMap

Completed PhDs

• Dr. Benjamin Herfort: Mapping what is not mapped - Investigating questions of representation and data quality in OpenStreetMap from the perspectives of humanitarian and machine learning-assisted mapping
• Dr. Hao Li: Deep Learning from Heterogeneous Geospatial Data for Automated Mapping of Man-made Infrastructures with OpenStreetMap
• Dr. Christina LudwigTowards a Global Map of Urban Green Spaces - Exploring Regional Variations and Uncertainty-Aware Methods using OpenStreetMap and Satellite Imagery
• Dr. Xuke Hu: Semi-automated crowd-supported Generation of Indoor VGI
• Dr. Amin Mobasheri: Open Geospatial Data Quality Assessment and Enrichment; The case of routing and navigation of people with restricted mobility
• Dr. Johannes Lauer: Extraction of routing relevant geodata using telemetry sensor data of agricultural vehicles
• Dr. Rene Westerholt: The analysis of spatially superimposed heterogeneous random variables – using the example of geosocial media data
• Dr. Clemens Jacobs: Data Quality of Citizen Science Observations of Organisms: Plausibility Estimation Based on Volunteered Geographic Information Context
• Dr. Michael Auer: Advancing 3D WebGIS – browser-based Methods for Visualization and Analysis and their Integration in Virtual Research Environments in the Context of Cultural Heritage
• Dr. Carolin Klonner: Participatory Geographic Information for Disaster Risk Reduction - Sketch Maps can Visualize Flood Risk Perception
• Dr. Martin Hämmerle: The Analysis of 3D Point Clouds Acquired with Low-Cost Methods for Geoscientific Research on Natural Objects
• Dr. Ming Li: Leveraging the Wisdom of the Crowd from Location-based Social Networks: Theoretical Potentials and Practical Applications
• Dr. Enrico Steiger: Explorative Spatial and Temporal Human Mobility Analysis from User-Generated Data
• Dr. Julian Hagenauer: Artificial Neural Networks: Methods and Applications in Spatial Data Mining
• Investigating Potential of VGI Data for Revealing Spatial and Temporal Patterns of Human Activity
• Geographic profiling of crime patterns
• Dr. Pascal Neis: Analyse der Qualität nutzergenerierter Geodaten zur Realisierung von Routenplanungen für Menschen mit Einschränkungen
• Dr. Marcus Götz: Using Volunteered Geographic Information for an Automated Provision of Indoor Location Based Services
• Dr. Maksim Rylov: Models and Methods for Cartographic Label Placement
• Dr. Arne Schilling: 3D Spatial Data Infrastructures for web-based Visualization
• Dr. Hossein Shafeezahdeh: Exploring and Simulating Spatial Patterns of Urban Growth Using Data-driven and Knowledge-based approaches