ILUS 2017

Workshop on Big Data Analytics
Topological and Scaling Perspective on Urban Structure and Dynamics
30 October 2017, Dresden, Germany, in conjunction with ILUS: International Land Use Symposium 2017, http://www.ilus2017.ioer.info/

NEW: Workshop location and schedule updated

The workshop will take place at the Leibniz Institute of Ecological Urban and Regional Development (IOER) and the Dresden University of Technology (TU Dresden).

The workshop will start at 09:00 am in the lecture hall of IOER. For directions to IOER please see: https://www.ioer.de/1/contact/ After an introductory lecture given by Bin Jiang in the morning we will have lunch at the TU Dresden Mensa (lunch at one's own expense). After lunch we will continue the workshop with a practical session in a computer lab of the TU Dresden (from 01:00 – 04:30 pm). This session will take place in the Hülsse-Bau (PC-Pool – HÜLS 590).

Motivation:
There are two fundamental laws of geography: Scaling law of far more small things than large ones, and Tobler’s law of more or less similar things. Scaling law can also be rephrased as the scaling hierarchy of numerous smallest, a very few largest, and some in between the smallest and the largest. Tobler’s law states that “everything is related to everything else, but near things are related than distant things”. These two laws complement each other and can effectively characterize the Earth’s surface as a fractal or scaling or living structure at different levels of scale. Geospatial big data emerging from the Internet and in particular social media such as OpenStreetMap, Flickr, and Twitter provide a new instrument for verifying these two laws and for better understanding urban structure and dynamics. Big data differs fundamentally from small data in terms of the characteristics such as whether accurately measured or roughly estimated, and whether individual based or aggregated. Big data also differs fundamentally from small data in terms of data analytics both geometrically and statistically. Euclidean geometry has been a default paradigm and it serves as the scientific foundation for various geographic concepts such as distances, directions, and map projections. There is little wonder that current geospatial analysis is essentially Euclidean, dealing with regular shapes and smooth curves. However, geographic features are no doubt irregular and rough, and it implies that Euclidean geometry is not an appropriate paradigm for geography. Instead, fractal geometry, in particular under the third definition of fractal: “a set or pattern is fractal if there are far more small things than large ones in it”, should be adopted for developing penetrating insights into urban structure and dynamics.

In order to see clearly the fractal or scaling or living structure, we must adopt a topological perspective. The topology refers to topological relationship among spatially or geometrically coherent entities such as rivers, mountains, buildings, streets, and cities, rather than that among geometric elements such as pixels, points, lines, and polygons as conceived and used in geographic information systems. Thus scaling and topology are interrelated in the sense that the latter enables us to see the former. This workshop will be organized through a series of lectures, hands-on exercises, and discussions surrounding two major concepts: natural cities and natural streets. Those interested in the workshop are encouraged to download the NaturalCitiesModel and run the enclosed tutorial prior to the workshop. This way we would more time on presentations and discussions. The participants must have their laptops with basic tools including Excel, Axwoman 6.3, and ArcGIS 10.x installed for some hands-on exercises. Internet access is essential for the workshop.

Tools to be used in the workshop:
Axwoman: http://fromto.hig.se/~bjg/axwoman/
NaturalCitiesModel: http://www.arcgis.com/home/item.html?id=47b1d6fdd1984a6fae916af389cdc57d
Head/tail breaks: http://en.wikipedia.org/wiki/Head/tail_Breaks

Biosketch of the workshop instructor:
Dr. Bin Jiang is Professor in GeoInformatics and Computational Geography at University of Gävle, Sweden. He worked in the past with The Hong Kong Polytechnic University, and the University College London’s Centre for Advanced Spatial Analysis. He is the principal developer of the software tool Axwoman for topological and scaling analysis of urban street networks (http://fromto.hig.se/~bjg/axwoman/). He is the founding chair of the International Cartographic Association Commission on Geospatial Analysis and Modeling. He used to be Associate Editor of international journal Computer, Environment and Urban Systems (2009-2014), and is currently Academic Editor of open access journal PLOS ONE, and Associate Editor of Cartographica. His research interests center on geospatial analysis and modeling of urban structure and dynamics, e.g., agent-based modeling, scaling hierarchy, and topological analysis applied to street networks, cities, and geospatial big data. Inspired by Christopher Alexander’s work, he developed a mathematical model of beauty, which helps address why a design is beautiful, and how much beauty the design has. One can refer to his ResearchGate and Google Scholar pages for more details on what he specializes in.
https://www.researchgate.net/profile/Bin_Jiang3
https://scholar.google.se/citations?user=ARKxYYUAAAAJ&hl=en&oi=ao

Contact:
Professor Bin Jiang (for queries about the content)
Faculty of Engineering and Sustainable Development, Division of GIScience
University of Gävle, 801 76 Gävle, Sweden
Email: bin.jiang@hig.se

Dr. Martin Behnisch (for queries about the general organisation)
Leibniz Institute of Ecological Urban and Regional Development (IOER)
Weberplatz1, 01217 Dresden, Germany
Email: m.behnisch@ioer.de

The workshop is organized by Leibniz Institute of Ecological Urban and Regional Development and the Gävle University College in cooperation with the VGIscience - DFG Priority Programme 1894 "Volunteered Geographic Information: Interpretation, Visualisation and Social Computing"

Twitter Hashtag
#ILUS2017

supported by