We are happy to introduce our keynote speakers, Prof. Dr. Martin Raubal, Prof. Gilberto Câmara and Brendan O’Neill.
Martin Raubal is Professor of Geoinformation Engineering at the Swiss Federal Institute of Technology (ETH) Zurich. He is also a member of the Energy Science Center at ETH Zurich and a member of the Future Resilient Systems Management Committee at the Singapore-ETH Centre. He was previously Associate Professor and Vice-Chair at the Department of Geography, University of California, Santa Barbara, and Junior Professor at the University of Münster. Martin received his Dr. techn. in Geoinformation from Vienna University of Technology in 2001 with honors. He holds a M.S. in Spatial Information Science and Engineering from the University of Maine and a Dipl.-Ing. in Surveying Engineering from Vienna University of Technology.
Martin’s research interests focus on spatial decision-making for sustainability, more specifically he concentrates on mobile Geographic Information Systems (GIS) & Location Based Services (LBS), analyzing spatio-temporal aspects of human mobility, spatial cognitive engineering, and mobile eye-tracking to investigate visual attention while interacting with geoinformation and in spatial decision situations. Prominent application domains include transportation, energy, and aviation. His group’s research has been funded by various agencies and organizations, such as the EU, National Research Foundation Singapore, U.S. National Geospatial Intelligence Agency, German Research Foundation, Swiss National Science Foundation, Swiss Federal Office of Energy, Federal Office of Civil Aviation, Innosuisse, Swiss Data Science Center, or the ETH Mobility Initiative. Industry partners include Swiss Federal Railways, Esri, HERE Technologies, Swiss International Air Lines, Lufthansa Aviation Training, SERMA, Thales, Swissgrid, ewz, and elia.
Martin’s teaching includes courses on GIS, cartography, geovisualization, location-based services, temporal aspects of GIS, spatial cognition and wayfinding, and research methods. He was Co-Chair of AGILE (Association of Geographic Information Laboratories in Europe) from 2014-19 and he was a board member of UCGIS (University Consortium for Geographic Information Science) from 2008-11. He serves on the editorial boards of Transactions in GIS, Journal of Spatial Information Science, Journal of Location Based Services, Spatial Cognition and Computation, Annals of the AAG, and Geography Compass. Martin was the General Chair of the 14th International Conference on Location Based Services in 2018. In 2008 he won the U.V. Helava Award. He has authored and co-authored 200 books and research papers published in refereed journals and conference proceedings.
“Spatial decision-making for sustainability”
Our planet is in dire straits. Several of the United Nations' Sustainable Development Goals address problems resulting from climate change and rising greenhouse gas emissions. The constant growth of urban mobility and transport has led to a dramatic increase in these emissions. In order to ensure livable environments for future generations, it will be necessary to reduce our CO2 footprint. Spatial decision-making fueled by spatial data science contributes to this effort in major ways, supported by recent progress regarding the availability of spatial big data, computational methods and geospatial technologies. This presentation will demonstrate why spatial decision-making is essential for sustainability and how spatial data science provides methods to perform large-scale spatio-temporal analyses of mobility patterns as well as geospatial technologies for changing people's mobility behavior. Examples will cover movement data analysis within the context of multi-modal and energy-efficient mobility, smart charging of electric vehicles, and mobile decision-making support.
Prof. Gilberto Câmara is a researcher on Geoinformatics and Land Use Change in Brazil's National Institute for Space Research, where he was General Director (2006-2012). He is renowned for promoting free access to geospatial data and for setting up an efficient satellite monitoring of the Brazilian Amazon rainforest. He was Director of the Secretariat of the Group on Earth Observations (GEO) from July 2018 to June 2021. He is a Dr. Honoris Causa by the University of Münster (Germany), a Chevalier de la Ordre National du Mérite of France, and received the Pecora Award from USGS and NASA.
“Satellite Image Time Series Analysis for Big Earth Observation Data”
This presentation describes sits, an open-source R package for satellite image time series analysis using machine learning. It supports the complete cycle of data analysis for land classification. Its API provides a simple but powerful set of functions. The software works in different cloud computing environments. Satellite image time series are input to machine learning classifiers, and the results are post-processed using spatial smoothing. Since machine learning methods need accurate training data, \sits includes methods for quality assessment of training samples. The software also provides methods for validation and accuracy measurement. The package thus comprises a production environment for big EO data analysis.
Brendan O'Neill has been a member of Esri’s Nonprofit and Global Organizations team for 5+ users and supports institutions like the World Bank, World Food Programme, the Food and Agriculture Organization, United Nations Refugee Agency (UNHCR), and USAID among others. Brendan focuses on helping develop and implement geospatial strategies at these institutions. Prior to working on the NGO team, he worked with Esri's education outreach team where he focused on modernizing GIS curricula and developed Do-It-Yourself Geo Apps, a Massive Open Online Course that has instructed over 20,000 students to date. Brendan is also an adjunct instructor at Johns Hopkins University and holds a B.A. from the University of Virginia, an M.A. from King's College, London, and an MSc. from Lund University.
“Geographic Information Systems in the Humanitarian and Global Development Communities”
Our workshop leaders will also play an important role during GeoMundus 2021. We have the pleasure to have Dr. Thomas Bartoschek on board this year.
Dr. Thomas Bartoschek is a postdoctoral researcher at the Institute for Geoinformatics, University of Münster and Co-Founder and CEO of the edtech Start-up re:edu since 2018 and of the non-profit openSenseLab since 2021. Thomas holds a PhD in Geoinformatics he received from ifgi in 2017. His research interests are in geotechnologies for spatial learning, human computer interaction, citizen science and digital education in general. During his career he investigated and developed various technologies for citizen science and digital learning with senseBox being the most prominent. He has experience in leading various research projects on a national level and received several awards for his work, most relevant the ACM Eugene Lawler Award for Humanitarian Contributions within Computer Science and Informatics in 2013.
Environmental Citizen Science with senesBox and openSenseMap
In this workshop participants will learn about environmental citizen science using the modular sensor platform senseBox and the open citizen science data infrastructure openSenseMap. The senseBox is a DIY Citizen Science toolkit for local and mobile measurement of environmental data such as temperature, humidity, air pressure, illuminance, UV light or air quality. It can be connected to the internet via WiFi, Ethernet or LoRa to enable Internet of Things capabilities in a sensor network. Local workshop participants will build and code measurement devices on several environmental phenomena and collect data around the campus. Remote participants will learn to access and analyze data from the openSenseMap through its APIs and other external tools. At the end environmental geodata from the local experiment will be analyzed by the whole group. We will round up with a discussion on the potential of the senseBox and openSenseMap in research projects and for educational purposes in secondary and higher education, while focusing on the data and computational, scientific and spatial literacy.