This workshop will provide a fast paced introduction to georeferenced vector data analysis. We will explore the power and functionalities of QGIS and R for reading, manipulating, and analyzing vector GIS data. Participants will also learn to generate production quality maps. Some exposure to R will he helpful but is not required.
This workshop will cover GIS concepts and techniques for analyzing geometric networks embedded in geographical space. We will mainly focus on road network, but the ideas and techniques apply to similar network such as the water and electricity distribution networks and gas pipelines. We will use open source tools in R and QGIS.
You should know the introductory concepts and tools in GIS and should be familiar with R. Familiarity with QGIS is not required.
This workshop will provide a gentle introduction to open source GIS tools in R and QGIS. We will cover introductory GIS concepts and will explore the functionalities of R and QGIS for manipulating and analyzing vector GIS data. Familiarity with R is required.
A paper by lead author Greg Rybarczyk, Associate Professor of Geography and GIS at U-M Flint, and Syagnik Banerjee, Associate Professor of Marketing at UM-Flint, has been accepted for forthcoming publication by the Journal of Location-Based Services. Both Banerjee and Rybarczyk are MIDAS Affiliated Faculty Members.
Citation: Rybarczyk, G., S. Banerjee, and M. Starking-Szymanski, and R. Shaker. (2018) “Travel and us: The impact of mode share on sentiment using geosocial media data and GIS” Journal of Location-Based Services (forthcoming)
Abstract: Commute stress is a serious health problem that impacts nearly everyone. Considering that microblogged geo-locational information offers new insight into human attitudes, the present research examined the utility of geo-social media data for understanding how different active and inactive travel modes affect feelings of pleasure, or displeasure, in two major U.S. cities: Chicago, Illinois and Washington D.C. A popular approach was used to derive a sentiment index (pleasure or valence) for each travel Tweet. Methodologically, exploratory spatial data analysis (ESDA) and global and spatial regression models were used to examine the geography of all travel modes and factors affecting their valence. After adjusting for spatial error associated with socioeconomic, environmental, weather, and temporal factors, spatial autoregression models proved superior to the base global model. The results showed that water and pedestrian travel were universally associated with positive valences. Bicycling also favorably influenced valence, albeit only in D.C. A noteworthy finding was the negative influence temperature and humidity had on valence. The outcomes from this research should be considered when additional evidence is needed to elevate commuter sentiment values in practice and policy, especially in regards to active transportation.
This workshop will provide a fast paced introduction to open source GIS tools, especially QGIS (but also R). We will explore QGIS’s power and functionalities for manipulating and analyzing vector GIS data. The workshop will be especially useful for students and researchers who use ArcGIS, but would like to learn about open source GIS tools. Participant should have at least one semester or equivalent exposure to GIS.
This workshop will cover introductory GIS concepts, tools, and techniques. We will use ArcGIS to learn basics of GIS by solving 2-3 specific problems. We will use the graphical user interface of ArcGIS and no programming experience is required for this workshop. The workshop will also cover the basics of projections and spatial data.
The workshop is meant for students and researchers who want to have a quick and simple exposure to GIS concepts and tools.