ThinkSpatial: Alina Ristea

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On Tuesday, May 5, 2020, the UCSB forum on spatial thinking presents

Spatial Crime Patterns vs. Safety Perception: Mixed Experiments

 

Alina Ristea

Boston Area Research Initiative (BARI)
School of Public Policy and Urban Affairs
Northeastern University, Boston

11:30 a.m. (PST) Tuesday, May 5, 2020

Zoom* : https://ucsb.zoom.us/j/98445704485

Abstract:
The occurrence of crime depends on a multitude of factors, namely crime attractors or generators, and it shows high spatiotemporal complexity. This presentation is targeting two opposite crime perspectives: (1) objective crime, and (2) subjective crime—perceived crime safety—fear of crime. This work contributes to the research on environmental crime analysis and prediction by pursuing two objectives. The first goal is to uncover spatial relationships between crime occurrences and nearby social media activity, whereas the second goal is to estimate the possible influence of social media posts on crime prediction models. The focus of this part of the presentation is on sporting events, suggesting that spatial crime patterns and people’s social posts are similar on event days and more dissimilar on non-event days. The subjectivity in crime is captured through the lenses of fear of crime. This project is an approach to amalgamate the knowledge about safety features already studied in the urban environment. The primary goal of this work is in using a fusion methodology for integrating a systematic video data acquisition, geographical storytelling, and human physiological measurements to build upon the analysis of the urban environment through a GIS-based platform. The three main objectives of this project are: (1) to test the compatibility of data acquisition through mixed technologies; (2) to extract safety information from the data acquired using mixed methods and to implement it in a GIS-based model; (3) to compare official crime data reported to the police, urban blight indicators, and people’s perceived safety, extracted from the mixed-method approach.

Bio:
Alina Ristea
is a Postdoctoral Research Associate at the Boston Area Research Initiative (BARI), part of the School of Public Policy and Urban Affairs, Northeastern University. She has a Ph.D. in Applied Geoinformatics from the University of Salzburg, Austria (2019), entitled Integration and Evaluation of Social Media in Crime Prediction Models. Her background studies are in the domains of geography, cartography, and Geographic Information Systems (GIS). Ristea’s research interests are highly interdisciplinary, and include interdisciplinary level, focusing among others on combining elements of GIScience, urban informatics, neighborhood effects, spatiotemporal crime analysis, social media mining, predictive analytics, and safety perception. She is a guest editor for the International Journal of Geo-Information (IJGI), by MDPI: Special Issue Urban Crime Mapping and Analysis Using GIS. In addition, she is a member of the International Association of Crime Analysts (IACA) and the American Association of Geographers (AAG). Among others, Ristea won a Marshall Plan Scholarship (February–May 2019), from the Austrian Marshall Plan Foundation, for a research stay at Louisiana State University (LSU).

Material:

ThinkSpatial - Alina Ristea

 

* Note, if you are participating from outside the UCSB community, please contact epd@ucsb.edu to get access to the credentials.

The objectives of the ThinkSpatial brown-bag presentations are to exchange ideas about spatial perspectives in research and teaching, to broaden communication and cooperation across disciplines among faculty and graduate students, and to encourage the sharing of tools and concepts.

Please contact Emmanuel Papadakis (epd@ucsb.edu) to review and schedule possible discussion topics or presentations that share your disciplinary interest in spatial thinking.

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ThinkSpatial: Konstadinos Goulias

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On Tuesday, April 28, 2020, the UCSB forum on spatial thinking presents

Life Cycle Stages, Daily Contacts, and Activity—Travel Time Allocation for the Benefit of Self and Others

 

Konstadinos G. Goulias

Department of Geography
University of California, Santa Barbara

11:30 a.m. (PST) Tuesday, April 28, 2020

Zoom: https://ucsb.zoom.us/j/96140245863

Abstract:

In this research, we study the correlation between life cycle stages and time allocation for the benefit of self and others. Life cycle stages are defined based on age, employment, family status, and disabilities. Time allocation is classified based on the people with whom each respondent came into contact and for whom he or she performed activities and travel. Based on a two-day time use diary, daily time allocation is classified in social fields that we define as family, friends, schoolmates, co-workers, clubmates, among others. We also include time for sleeping and activities and personal travel. The data analysis creates a taxonomy using cluster analysis of time-of-day activity sequences, complexity of time schedules, and uncovers its correlation with life cycle stages.

Bio:
Since 2004, Konstadinos (Kostas) G. Goulias has been a Professor of Transportation at the Department of Geography at the University of California, Santa Barbara. From 1991 to 2004 he was Professor of Transportation in the Department of Civil and Environmental Engineering of PennState University, where he also directed research centers. His research is on large-scale transportation systems modeling and simulation, travel behavior dynamics, sustainable transportation, smart cities, economic geography, travel survey methods, geocomputation, and geoinformation. He chairs the International Association for Travel Behaviour Research and he is the co-editor-in-chief of Transportation Letters an international peer-reviewed journal published by Taylor and Francis. He received a Laurea (5 years and a thesis equivalent to M.S.) in Engineering from the University of Calabria (Italy) in 1986, an M.S. in Engineering from the University of Michigan, Ann Arbor, in 1987, and a Ph.D. in Engineering from University of California Davis, in 1991.

The objectives of the ThinkSpatial presentations are to exchange ideas about spatial perspectives in research and teaching, to broaden communication and cooperation across disciplines among faculty and graduate students, and to encourage the sharing of tools and concepts.

Please contact Emmanuel Papadakis (epd@ucsb.edu) to review and schedule possible discussion topics or presentations that share your disciplinary interest in spatial thinking.

Follow spatial@ucsb on Twitter | Google+ | Google Calendar

ThinkSpatial: George Baryannis

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On Tuesday, April 21, 2020, the UCSB forum on spatial thinking presents

Qualitative Spatial Reasoning Using Answer Set Programming

 

George Baryannis

Department of Computer Science
University of Huddersfield, UK

11:30 a.m. Tuesday, April 21, 2020 | Zoom meeting room:

https://ucsb.zoom.us/j/96140245863

Abstract:

Spatial (and temporal) information is often expressed using qualitative terms such as natural language expressions instead of coordinates; reasoning over such terms has several practical applications, such as naval traffic monitoring, warehouse process optimization, and robot manipulation. Well over 40 qualitative calculi have been proposed so far, including Allen’s interval algebra and the Region Connection Calculus. Reasoning with such calculi has been the focus of extensive research within the wider AI community, with a number of specialized reasoning tools developed. One barrier to the wide adoption of these tools is that only qualitative reasoning is supported natively when real-world problems most often require a combination of qualitative and other forms of reasoning.

I will discuss research to overcome this barrier (conducted at the University of Huddersfield, UK, and the University of Calabria, Italy), focusing on using Answer Set Programming (ASP) as a unified formalism to tackle problems that require qualitative reasoning in addition to non-qualitative reasoning. ASP is a logic-based knowledge representation and reasoning approach that includes a rich but simple modeling language and is capable of handling search problems of high complexity. Research is motivated by two case studies: reasoning about the relations among large numbers of trajectories and determining optimal coverage of telecommunication antennas.

Bio:
George Baryannis is Senior Lecturer (Associate Professor) at the Department of Computer Science of the University of Huddersfield, UK. He received his Dipl.Eng. in Electronic and Computer Engineering from the Technical University of Crete, Greece, and his M.Sc. and Ph.D. in Computer Science from the University of Crete, Greece. His teaching and research interests lie within Artificial Intelligence, mainly focusing on knowledge representation and reasoning, machine learning, and interpretability, as well as applications in supply chain risk management, smart homes, and service-oriented computing.

Material:

ThinkSpatial-QSRASP

 

The objectives of the ThinkSpatial presentations are to exchange ideas about spatial perspectives in research and teaching, to broaden communication and cooperation across disciplines among faculty and graduate students, and to encourage the sharing of tools and concepts.

Please contact Emmanuel Papadakis (epd@ucsb.edu) to review and schedule possible discussion topics or presentations that share your disciplinary interest in spatial thinking.

Follow spatial@ucsb on Twitter | Google+ | Google Calendar