AMU Invited Lectures Series in GIScience
TITLE OF THE LECTURE: Uncertainty in spatial modeling: adversity or opportunity?
Abstract: Comprehensive representations of complex socio-environmental systems usually require coupling models from various disciplines into a large consolidated model characterized by high computational cost, algorithmic complexity, and confounded uncertainty. The latter is usually perceived as an inconvenience that should be curtailed. It can be argued, however, that, if managed systematically, uncertainty can provide an opportunity to discover robust and sustainable futures. To this end, we propose three intertwined design principles that should guide the development of uncertain policy-relevant models: legitimacy, parsimony, and practicality. Model legitimacy encompasses the various sources of uncertainty – from expert opinion, through measurement error, to stakeholder preferences. Legitimacy aims at the faithful representation of the perspectives of all involved stakeholders (uncertainty differentiation). Model parsimony is necessary because legitimate models often result in many overlapping system representations, which can be further simplified and grouped to minimize model complexity (uncertainty reduction). Finally, to satisfy practicality, we need to maintain a certain level of variability in models to provide means of experimentation that can augment consensus building (uncertainty exploration). These principles provide a foundation for a unique framework for studying socio-environmental systems that acknowledges inherent system uncertainty and aims at its exploitation.
October 18th, 2022, 3:00 PM (UTC +2)
TITLE OF THE LECTURE: Movement data and geoprivacy – the caveats of using GPS data in research
Abstract: Human mobility is vital for understanding expansion processes in urban areas, the establishment of transportation services and the spatial distribution of facilities. The development of sensors such as GPS trackers or other wearable devices equipped with various sensors that capture movement data in real-time and at detailed spatial and temporal scales has transformed our ability to collect mobility data. However, even though GPS trackers record an individual's movement very accurately and potentially can be used to identify individuals, they do not record essential characteristics of travel behaviour. In this seminar, I will talk about contextually enhancing raw movement trajectories to uncover these mobility characteristics. Furthermore, I will touch upon privacy concerns resulting from the availability and accuracy of location data and its implications for research.
November 15th, 2022, 9:00 AM (UTC +2)
TITLE OF THE LECTURE: Empirical investigations into individual human behavior, decision making, and lived experiences
Abstract: In this presentation I will highlight our past research on human indoor-outdoor wayfinding on an urban college campus. Our work aims at facilitating independent travel for individuals with blindness and low vision. Our research was funded by two successive grants from the National Institute for Transportation and Communities/US Department of Transportation. One of the central research questions sought to capture wayfinding preferences, information needs, and lived experiences of blind and low-vision pedestrian travelers. The projects afforded close collaboration with external partners, and foremost the American Printing House for the Blind. My focus in the presentation will be on the discussion of considerations for wayfinding technology deployment, human subject research design, as well findings and lessons learned.
Tuesday, 24 January 2023, at 15:00 (Warsaw time)
TITLE OF THE LECTURE: Spatially-explicit predictions of future racial segregation - geographic versus statistical approaches
Abstract: The United States is a racially diverse country. In addition, its cities had been and continue to be racially segregated. It’s fair to say that the American public is obsessed with everything relating to race. On the scientific front, at American universities, the study of everything racial belongs to the discipline of sociology. This means a low level of quantitative sophistication and a lack of familiarity with spatial analysis. In particular, one topic that has not been studied is how to predict future racial geography in U.S. cities. I will present my own (geographic) approach to this problem and another (statistical) approach originating from the physics community. Both approaches show that predicting the future racial geography of U.S. cities is possible if advanced quantitative methods are used.
Tuesday, March 21st 2023, at 4:00 PM
TITLE OF THE LECTURE: Geodiversity assessment revisited: what can we learn from spatially-explicit uncertainty and sensitivity analysis?
Abstract: Uncertainty and sensitivity analysis (US-A) has long been an established method of testing the reliability of model predictions. Most of US-A applications have been in models where modeling results are spatially non-variable. In this talk, I present an extension of this approach to models with spatially variable results, an example of which is a multiple criteria geodiversity assessment model. Following a brief explanation of the method, I focus on the interpretation of US-A results for the geodiversity assessment of three national parks in Poland. I demonstrate how the visualization and interpretation of spatially-explicit uncertainty and sensitivity indicators can not only give a more holistic picture of model results, but potentially help improve the model and assist in the decision making
Tuesday, April 18 2023, at 5:00 PM
TITLE OF THE LECTURE: Where do platforms locate? Splintering amenitization in three Canadian cities
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TITLE OF THE LECTURE: What is the perfect future for geospatial data science?
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The series is funded by project ID-UB 051/01/POB1/0003.