Candidate: Scott Heneghan
Master of Science in Geoinformatics and Geospatial Intelligence
Department of Geography and Geoinformation Science
Date: Tuesday, January 17, 2017
Time: 10:00 AM
Place: Exploratory Hall 2304
GRASSROOTS TO VOTING BOOTHS: A STUDY OF THE SPATIOTEMPORAL DYNAMICS OF TRADITIONAL MEDIA COVERAGE AND SOCIAL MEDIA IMPACT IN 2016 UNITED STATES PRESIDENTIAL CANDIDATES
Director: Dr. Anthony Stefanidis
Committee Members: Dr. Arie Croitoru, Dr. Andrew Crooks
The subject of social media effect on elections has been studied by multiple peer reviewed journals, however none take a space time statistical approach to social media’s effect on traditional media in the context of a presidential election. This article attempts to review the space time patterns of social media and how they can potentially drive news coverage from local papers across different parts of the United States. Specifically, the number of tweets around the newspaper locations as compared against the number of news reports about either Bernie Sanders or Donald Trump were reviewed in order to determine if social media is in fact a driver of change. The trends of the results over time were analyzed using the Pearson product moment correlation.
Candidate: Jason Shapiro
Doctor of Philosophy in Earth Systems and Geoinformation Sciences
Department of Geography and Geoinformation Science
Date: Friday, December 2, 2016
Time: 1:00 PM
Place: Exploratory Hall 2304
MODELING THE IMPACTS OF AIRPORTS ON URBAN DENSITY: CASE STUDY OF WASHINGTON DULLES INTERNATIONAL AIRPORT
Director: Dr. Donglian Sun
Committee Members: Dr. Matthew Rice, Dr. Terry Slonecker, Dr. Stephen Fuller
Airports are often seen as powerful anchors for urban development causing domino effects of induced impacts. Business activity caused by airports creates employment and population growth, resulting in increased urban development.
A case study of Washington Dulles International Airport is investigated to better understand the relationship between airports and urban development. The research is divided into four parts:
1. Models of urban development clustering;
2. Analysis of variables influencing urban density;
3. Temporal analysis of airport urban development dynamics; and
4. Tests of the causality relationship between airports and urban development.
The models of urban development clustering developed use a diverse set of economic and environmental urban density proxy measures including the intensity of night time lights, surface temperature, the existence of impervious surfaces, as well as property values and rents. The proxy measures are applied in an Anselin Local Moran I Cluster Analysis and in a Geographic Weighted Regression (GWR) to investigate and model the airport-urban development relationship. The Anselin Local Moran I Analysis detects, delineates, and investigates urban development clustering near an airport. A GWR investigates the impact of explanatory variables including distance to the airport, primary roads, and the central business district on urban development.
The analysis also considers the statistical significance and spatial diffusion of explanatory variables in anchoring urban development.
The results can be summarized in four key findings suggesting that there is an independent urban cluster near Dulles Airport and the airport has had a significant influence in the area’s urban dynamics:
1. Dulles Airport has anchored urban development;
2. Airport operations have affected the magnitude of development;
3. An independent urban cluster exists near Dulles Airport; and
4. Several factors in addition to the existence of the airport explain the urban development.
This research advances the science relating to the airport–urbanization relationship in several ways.
1. An empirical model for induced airport impacts on urbanization is developed. Previous efforts have focused on direct and indirect impacts such as the relationship between airports and employment and property values without addressing the induced impacts on urbanization. Other studies have conceptually identified this relationship without testing it empirically.
2. It models urban development at the local level rather than at the regional or state/nationwide level. It examines the influence of the airport and the local spatial distribution of urban development using 1200 meter cells. Previous studies examined urban development impacts from airports at a regional scale covering a metropolitan area or a larger geographic extent.
3. Remote sensing and GIS are used to model the relationship between the airport and urbanization. Previous studies have used an economic and conceptual analysis of airport-anchored development, but did not apply remote sensing data and GIS to examine the impacts.
4. It develops a case study for Washington Dulles International Airport that models airport-induced urbanization. Previous studies have conceptually identified Dulles Airport as anchoring urbanization, but have not empirically modelled the airport’s impacts on urbanization.
5. Urban clusters of development proximate to Dulles Airport are detected and delineated. The development of the Dulles Airport-anchored urban clusters is examined using the relationship of airport proximity with other explanatory variables, including distance to primary roads and the central business district. In addition, the spatial diffusion and land use of the urban clusters are analyzed. Previous studies have focused on conceptual and direct and indirect models, but have not empirically analyzed airport-anchored clusters.
George Mason University researchers and administrators briefed staff from the U.S. House Subcommittee on Research and Technology on scientific projects that will safeguard computer networks, protect drivers in automobile crashes, help airplanes fly safe, and more.
Elected officials and their staff visit George Mason as they seek to understand the latest research trends and how Mason research directly helps people.
Read the full article here
Dieter Pfoser and Andreas Züfle were awarded $507,852.00 by the National Science Foundation for their research project NSF/AitF: Collaborative Research: Modeling movement on transportation networks using uncertain data. The objective of the project is to create a unified framework for aggregating and analyzing diverse and uncertain movement data on transportation networks, with the aim to provide tools for querying and predicting traffic volume and movement in urban environments.
The Department of Geography and Geoinformation Science at George Mason University will host the upcoming Annual Meeting of the Middle Atlantic Division of the AAG. The annual meeting will be November 18-19, 2016 in Fairfax, VA.
Attend the annual meeting, submit an abstract and register at: http://ma-aag.org/
We look forward to welcoming you at Mason.
The 2016 Google Scholar metrics are out and show that 7 papers published by our faculty and students are among the top-10 most cited papers over the past 5 years in leading GIScience journals. More specifically, GGS faculty had extremely highly cited papers in the following journals:
- Transactions in GIS (http://bit.ly/2az370B), with a Mason GGS paper at the #1 spot, with 135 citations so far: Crooks, A., Croitoru, A., Stefanidis, A., & Radzikowski, J. (2013). # Earthquake: Twitter as a distributed sensor system. Transactions in GIS, 17(1), 124-147.
- Geojournal (http://bit.ly/2a1D29q), with a Mason GGS paper at the #3 spot, also with 135 citations: Stefanidis, A., Crooks, A., & Radzikowski, J. (2013). Harvesting ambient geospatial information from social media feeds. GeoJournal, 78(2), 319-338.
- Computers and Electronics in Agriculture (http://bit.ly/2a2EQPL) with a Mason GGS paper at the #8 spot, with 82 citations: Han, W., Yang, Z., Di, L., & Mueller, R. (2012). CropScape: A Web service based application for exploring and disseminating US conterminous geospatial cropland data products for decision support. Computers and Electronics in Agriculture, 84, 111-123.
- International Journal of Digital Earth (http://bit.ly/2azTU54) with a Mason GGS paper at the #9 spot with 41 citations: Yang, C., Xu, Y., & Nebert, D. (2013). Redefining the possibility of digital Earth and geosciences with spatial cloud computing. International Journal of Digital Earth, 6(4), 297-312.
- ISPRS International Journal of Geo-Information (http://bit.ly/2az44G0), with a Mason GGS paper at the #3 spot with 28 citations so far: Jackson, S. P., Mullen, W., Agouris, P., Crooks, A., Croitoru, A., & Stefanidis, A. (2013). Assessing completeness and spatial error of features in volunteered geographic information. ISPRS International Journal of Geo-Information, 2(2), 507-530.
- Cartography and Geoinformation Science (http://bit.ly/2apuVU2), with two Mason GGS paper at the top-10! One at the #7 spot with 31 citations: Stefanidis, A., Cotnoir, A., Croitoru, A., Crooks, A., Rice, M., & Radzikowski, J. (2013). Demarcating new boundaries: mapping virtual polycentric communities through social media content. Cartography and Geographic Information Science, 40(2), 116-129; and another at the #9 spot, with 28 citations: Xu, C., Wong, D. W., & Yang, C. (2013). Evaluating the “geographical awareness” of individuals: An exploratory analysis of Twitter data. Cartography and Geographic Information Science, 40(2), 103-115.
We are very proud to be a leading force in shaping tomorrow’s geoinformation science!
Andreas Züfle is an assistant professor with the department of Geography and Geoinformation Science at George Mason University. He received his PhD in Computer Science from Ludwig-Maximilians-University Munich, Germany in 2013. Dr. Züfle is a data scientist, whose research quest is to bridge the gap between databases, statistics and geoinformation science, three communities often working independently on identical research problems. To bring these communities together, Dr. Züfle’s research is focused on querying and mining of spatio-temporal and uncertain data. Since 2011, he has published more than 50 fully refereed papers receiving more than 700 citations for his innovative work. His current research activities are funded by NSF.
Office: 2215 Exploratory Hall
☎ Telephone: (703) 993-5866
- Data Science
- Reliable Data Analysis
- Uncertain Data
- Enriched Spatial and Spatio-Temporal Data
- For a list of my publications, see my DBLP entry.
Academic and Professional Activities
- GGS 787 Scientific Data Mining for Geoinformatics
Professional Organization Membership:
- Program Co-Chair:- ACM SIGMOD@GeoRich Workshop 2014, 2015 and 2016
- Program Committee:- ADBIS 2014
– ADC 2015, 2016
– CIKM 2014, 2015
– DASFAA 2015
– MSTD 2013
– SIGSPATIAL 2016
– SUM 2016