Johannes Fürle

Johannes Fürle is Research Associate at the Geoinformatics Research Group of the Institute of Geography at Heidelberg University with background in physics and geography.

Research Interests

• Geoinformatics in context of interdisciplinary data analysis, physics and climate change adaptation
• Volunteered geographic information (VGI) / crowd data
• Machine learning
• Big data analysis
• Development & management of scientific software
• IoT & smart cities
• sensor networks

Research Projects (current + recent)

• HEAL – Heat adaptation for vulnerable populations: Heat stress avoidance routing and heat stress modelling. ML, IoT, software development, project manager
• SocialMedia2Traffic – Deriving traffic information from social media data. ML, software development
• Heidelberg Center for the Environment (HCE) - Climate Action Science (CAS): Estimation of greenhouse gases emissions

Talks, cooperations and workshops

• 09/2022: „Measurement and data requirements in HEAL: A safe way through the heat” at GeoNet.MRN - A HyperMode Meetup with Johannes Fürle
• 06/2022: “data handling and analysis of intra-urban features in Heidelberg in the domain of heat stress detection” together with Dr. Kathrin Foshag. Presentation at Forschungstag 2022 Baden-Württemberg Stiftung
• 07/2022: “climate assessment of intra-urban features in Heidelberg with free and open source data and software” together with Dr. Kathrin Foshag. Presentation at Städtetag Baden-Württemberg
• 04/2022: project management and efficient time planning in scientific projects. HCE Heidelberg
• 06/2021-dato: cooperation on IoT and sensor implementation in the city environment with Digital-Agentur Heidelberg
• 06/2021-dato: cooperation on intra-urban sensing, climate assessment and weather measurements with Environmental Agency Heidelberg
• 09/2021: „Heatstress and climate adaption – a open data and sensing approach” together with Dr. Kathrin Foshag. Presentation at Baden-Württemberg Stiftung, Stuttgart

Teaching

• 04/2024-07/2024: "Spatial decision support systems with Python". Hands-on seminar on Multi-Criteria Decision Making (MCDM) with advanced python analysis, DBs, data integrations and visualisation. (MA)
• 10/2022-02/2023: lecture statistics, by Prof. Dr. S. Lautenbach and assistant Johannes Fürle
• 04/2022-08/2022: Seminar about python programming and data handling, visualisation and analysis in geoinformatics and climate science: “Urban Climate and Heat Stress: Approaches from Geoinformatics and Transdisciplinary Research” (MA+BA)
• 10/2021-02/2022: Seminar about data analysis, ethics, privacy concerns, project planning and scientific reporting in “Geographical Analysis of Social Media Data” (MA+BA)

Curriculum Vitae

Professional Occupation:

• 2021: research associate at the Geoinformatics Research Group of Prof. Dr. Zipf, Heidelberg University
• 2020: research assistant at the Geoinformatics Research Group of Prof. Dr. Zipf, Heidelberg University
• 2016 –2019: IT quality management SAP Screen Personas for SAP GUI for Windows, Java and Web & software testing planner, working student at SAP SE, Germany

Prior internships:

• BASF SE: robotics, lab automation and software development
• Pepperl+Fuchs: QA sensing techniques and software development

Educational:

• 2013 – 2019: Studies of physics and of geography at Heidelberg University, Germany

Publications

ORCiD reference

• Foshag, K., Fürle, J., Ludwig, C., Fallmann, J., Lautenbach, S., Rupp, S., Burst, P., Betsch, M., Zipf, A., Aeschbach, N., 2024. How to assess the needs of vulnerable population groups towards heat-sensitive routing?: An evidence-based and practical approach to reducing urban heat stress. ERDKUNDE 1–33. https://doi.org/ 10.3112/erdkunde.2024.01.01
• Martinez-Soto, A., Fürle, J., Zipf, A. (2023): Urban Heat Island Prediction in the Context of Heat Waves: An Evaluation of Model Performance. Eng. Proc. 2023, 39(1), 80. https://doi.org/10.3390/engproc2023039080
• Ludwig, C., Psotta, J., Buch, A., Kolaxisi, N., Fendrich, S., Zia, M., Fürle, J., Rousell, A., Zipf, A. (2023): Traffic speed modelling to improve travel time estimation in openrouteservice. ISPRS Int. J. Geo-Inf. 2023. https://isprs-archives.copernicus.org/articles/XLVIII-4-W7-2023/109/2023/
• Ulrich V, Brückner J, Schultz M, Vardag SN, Ludwig C, Fürle J, Zia M, Lautenbach S, Zipf A. (2023): Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data. ISPRS International Journal of Geo-Information. 12(4):138. https://doi.org/10.3390/ijgi12040138
• Zia, M.; Fürle, J.; Ludwig, C.; Lautenbach, S.; Gumbrich, S.; Zipf, A. SocialMedia2Traffic: Derivation of Traffic Information from Social Media Data. ISPRS Int. J. Geo-Inf. 2022, 11, 482. https://doi.org/10.3390/ijgi11090482