Prof. Dr. Martin Raubal ("Spatial decision-making for sustainability"), Dr. Linnet Taylor ("The God’s eye view? Geospatial data, power and politics"),
Prof. Gilberto Câmara ("Satellite Image Time Series Analysis for Big Earth Observation Data") and Brendan O’Neill ("Geographic Information Systems in the Humanitarian and Global Development Communities") have confirmed their
participation as Keynote Speakers.
Professor for Geoinformation Engineering
Institute of Cartography and Geoinformation, ETH Zurich
KEYNOTE:
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.
Dr. Linnet Taylor
Associate Professor
Tilburg Law School
KEYNOTE:
The God’s eye view? Geospatial data, power and politics
Since the 2010s there has been a shift in the nature and quantity of digital data on social processes flowing into both research and policy. Much of this data stems from sensing and monitoring through GIS and related technologies, whether using people themselves as sensors (as with mobile phone location data) or using classic forms of sensing in new ways (such as satellite data for migration monitoring, or social media data for development policy). New forms of data such as those stemming from fintech, from ID systems around the world, and other sources promise to broaden the uses and potential abuses of people’s digital traces. The new data provides what Pentland (2012) has termed ‘the god’s eye view’ – but to whose benefit, and in whose interests? There are two views on this in the world of research. First, do the new sources provide better-quality data, do they add something to the analysis of social phenomena, can they enable policy and research to do a better job of serving society? The second view asks how these data sources become available, whose interests they serve, and what this means for their legitimacy, and the legitimacy of research and policy based on them. This presentation will explore the tensions between these two views, and ask how these new sources of geospatial data interact with questions of rights, ethics and politics.
Researcher on Geoinformatics and Land Use Change
Brazil National Institute for Space Research
KEYNOTE:
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.
Solutions Engineer
Esri's Nonprofit and Global Organizations & Johns Hopkins University
KEYNOTE:
Geographic Information Systems in the Humanitarian and Global Development Communities
Geographic information technology has evolved rapidly in recent years but challenges in designing systems and solutions that meet the increasingly complex needs of humanitarian and development organizations persist. In this keynote he will discuss trends and challenges that face the United Nations System and international NGOs in effectively making use of the latest developments in geospatial technology. Brendan will also present solutions that despite these challenges have succeeded in positively impacting outcomes in areas such as food security, mine action, disaster response, and climate change resilience.
Two workshops will take place during GeoMundus 2021 thanks to the workshop leaders Dr. Thomas Bartoschek and Mario Pesch ("Environmental Citizen Science with senseBox and openSenseMap"), and Pedro Cabral, Felipe Campos and João David ("Open data and models for mapping ecosystem services").
Postdoctoral researcher & CEO
University of Münster & re:edu
WORKSHOP:
Environmental Citizen Science with senseBox 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.
Mario Pesch
Research assistant and PhD candidate
University of Münster
WORKSHOP:
Environmental Citizen Science with senseBox 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.
Dr. Pedro Cabral
Associate Professor
NOVA University of Lisbon
WORKSHOP:
Open data and models for mapping ecosystem services
Ecosystem services (ES) are the benefits provided to humans by the natural environment, such as clean air, natural pollination, drought regulation, food from agriculture, climate regulation, etc. Providing Information about ES for decision-making is essential to preserve their supply and, consequently, their benefits to society. Making these services visible through the mapping of biophysical, social and economic indicators enables understanding of potential trade-offs and the design of conservation strategies. The provision of ES is influenced by land cover changes (LCC) and efficient land use planning is required for maintaining ES flow. Land use planning can be supported by ES-based modelling tools to estimate ES supply based on land cover. In this workshop we explore available open data and models which can be used for ES modelling and mapping. A hands-on exercise using an InVEST model will be carried out.
Dr. Felipe Campos
Postdoctoral Researcher
NOVA University of Lisbon
WORKSHOP:
Open data and models for mapping ecosystem services
Ecosystem services (ES) are the benefits provided to humans by the natural environment, such as clean air, natural pollination, drought regulation, food from agriculture, climate regulation, etc. Providing Information about ES for decision-making is essential to preserve their supply and, consequently, their benefits to society. Making these services visible through the mapping of biophysical, social and economic indicators enables understanding of potential trade-offs and the design of conservation strategies. The provision of ES is influenced by land cover changes (LCC) and efficient land use planning is required for maintaining ES flow. Land use planning can be supported by ES-based modelling tools to estimate ES supply based on land cover. In this workshop we explore available open data and models which can be used for ES modelling and mapping. A hands-on exercise using an InVEST model will be carried out.
João David
Guest lecturer
NOVA University of Lisbon
WORKSHOP:
Open data and models for mapping ecosystem services
Ecosystem services (ES) are the benefits provided to humans by the natural environment, such as clean air, natural pollination, drought regulation, food from agriculture, climate regulation, etc. Providing Information about ES for decision-making is essential to preserve their supply and, consequently, their benefits to society. Making these services visible through the mapping of biophysical, social and economic indicators enables understanding of potential trade-offs and the design of conservation strategies. The provision of ES is influenced by land cover changes (LCC) and efficient land use planning is required for maintaining ES flow. Land use planning can be supported by ES-based modelling tools to estimate ES supply based on land cover. In this workshop we explore available open data and models which can be used for ES modelling and mapping. A hands-on exercise using an InVEST model will be carried out.
