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Understanding spatial structure

Spatial statistics

»[E]verything is related to everything else, but near things are more related than distant things.«  (First law of geography; Waldo Tobler, 1970)

The world around us is full of complex spatial structures. But how can we reliably estimate meaningful spatial structures from our scientific and everyday data sets? What stories do quantified spatial patterns tell us? How do spatial methods interact with different types of data and their properties? How can we approach the identification of spatial structures in novel types of data sets? These are the questions we are dealing with at the Spatial Modelling Lab Dortmund.

Our lab focuses on statistical methods for the detection and characterisation of spatial regularities. One specialisation is the estimation of spatial autocorrelation. We investigate how existing estimators interact with novel data sets for which these methods were not originally intended. An example is the case of social media data, some of which are geographically referenced. However, such Big Data sources are subject to complex forms of heterogeneity and originate from largely uncontrolled, non-scientific data collection procedures. Using existing methods or novel approaches, we investigate how we can extract spatial patterns from such data sets in order to expand our knowledge about the organisation of our everyday life. We thereby contribute to the investigation of correlation measures, hotspot statistics, and measures of spatial heterogeneity.

We also focus on new ways of representing "space" in regression and other types of modelling. This includes the explicit inclusion of space as an explanatory factor in regression models to reveal the effect of space in complex systems. Our work investigates both methodological aspects of both regression modelling and spatial filtering. The latter is a set of techniques based on the representation and understanding of the interplay of all possible spatial patterns that a specific geographic configuration would theoretically allow. This holistic approach makes spatial filtering a very powerful tool for a comprehensive quantitative analysis of geographical issues. In addition to these technical foci, we emphasise the importance of modelling not only space in an abstract sense, but especially geographical space. In this way, we argue for the importance of the meaningfulness that models of geographical space should offer in order to disclose not only patterns and structures, but also a detailed and realistic understanding of the geographical environment. This is a key feature that distinguishes us from many other, more technically oriented labs and positions us clearly at the interface between technical and domain expertise.

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Location & approach

The campus of TU Dort­mund University is located close to interstate junction Dort­mund West, where the Sauerlandlinie A 45 (Frankfurt-Dort­mund) crosses the Ruhrschnellweg B 1 / A 40. The best interstate exit to take from A 45 is "Dort­mund-Eichlinghofen" (closer to Campus Süd), and from B 1 / A 40 "Dort­mund-Dorstfeld" (closer to Campus Nord). Signs for the uni­ver­si­ty are located at both exits. Also, there is a new exit before you pass over the B 1-bridge leading into Dort­mund.

To get from Campus Nord to Campus Süd by car, there is the connection via Vogelpothsweg/Baroper Straße. We recommend you leave your car on one of the parking lots at Campus Nord and use the H-Bahn (suspended monorail system), which conveniently connects the two campuses.

TU Dort­mund University has its own train station ("Dort­mund Uni­ver­si­tät"). From there, suburban trains (S-Bahn) leave for Dort­mund main station ("Dort­mund Hauptbahnhof") and Düsseldorf main station via the "Düsseldorf Airport Train Station" (take S-Bahn number 1, which leaves every 20 or 30 minutes). The uni­ver­si­ty is easily reached from Bochum, Essen, Mülheim an der Ruhr and Duisburg.

You can also take the bus or subway train from Dort­mund city to the uni­ver­si­ty: From Dort­mund main station, you can take any train bound for the Station "Stadtgarten", usually lines U41, U45, U 47 and U49. At "Stadtgarten" you switch trains and get on line U42 towards "Hombruch". Look out for the Station "An der Palmweide". From the bus stop just across the road, busses bound for TU Dort­mund University leave every ten minutes (445, 447 and 462). Another option is to take the subway routes U41, U45, U47 and U49 from Dort­mund main station to the stop "Dort­mund Kampstraße". From there, take U43 or U44 to the stop "Dort­mund Wittener Straße". Switch to bus line 447 and get off at "Dort­mund Uni­ver­si­tät S".

The AirportExpress is a fast and convenient means of transport from Dort­mund Airport (DTM) to Dort­mund Central Station, taking you there in little more than 20 minutes. From Dort­mund Central Station, you can continue to the uni­ver­si­ty campus by interurban railway (S-Bahn). A larger range of in­ter­na­tio­nal flight connections is offered at Düsseldorf Airport (DUS), which is about 60 kilometres away and can be directly reached by S-Bahn from the uni­ver­si­ty station.

The H-Bahn is one of the hallmarks of TU Dort­mund University. There are two stations on Campus Nord. One ("Dort­mund Uni­ver­si­tät S") is directly located at the suburban train stop, which connects the uni­ver­si­ty directly with the city of Dort­mund and the rest of the Ruhr Area. Also from this station, there are connections to the "Technologiepark" and (via Campus Süd) Eichlinghofen. The other station is located at the dining hall at Campus Nord and offers a direct connection to Campus Süd every five minutes.

The facilities of TU Dort­mund University are spread over two campuses, the larger Campus North and the smaller Campus South. Additionally, some areas of the uni­ver­si­ty are located in the adjacent "Technologiepark".

Site Map of TU Dort­mund University (Second Page in English)