GIS Colloquium – Talks (Winter Term 2015/16)

Detection, modelling and visualisation of space-related emotions from user-generated content

Dr.-Ing. Eva Hauthal - Tue, Oct 27, 2015, 4.15 pm, Hörsaal Berliner Straße 48

The presented research deals with the extraction of georeferenced emotions from the written language in the metadata of Flickr and Panoramio photos, thus from user-generated content, as well as with their modelling and visualisation. The algorithm that was developed for the extraction of these emotions applies different approaches from the field of computer linguistics and considers grammatical special cases like the amplification or negation of words. The algorithm was applied to a dataset of Flickr and Panoramio photos of Dresden (Germany). The results are an emotional characterisation of space which makes it possible to assess and investigate specific features of georeferenced emotions. These features are especially related to the temporal dependence and the temporal reference of emotions on one hand; on the other hand collectively and individually perceived emotions have to be distinguished. As a consequence, a place does not necessarily have to be connected with merely one emotion but possibly also with several. The analysis was carried out with the help of different cartographic visualisations.

Mobile Mapping with SLAM

Prof. Dr. Andreas Nüchter - Thu, Nov 12, 2015, 4.15 pm, Hörsaal Berliner Straße 48

Mobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. In this talk, we present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors including vehicle odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithm that corrects the vehicle position at every point in time along its trajectory, while simultaneously improving the quality and precision of the entire acquired point cloud. Using this algorithm from the robotics community the temporary failure of accurate external positioning systems or the lack thereof can be compensated for.
We demonstrate the capabilities of the proposed algorithms on a wide variety of data sets, including a backpack mounted mobile mapping system and a sensor skid for digitizing production lines.

Fachaustausch Geoinformation

Prof. Gerd Buziek (ESRI Deutschland): Geoinformationen – Rohstoff für die Digitale Gesellschaft
Dr. Gotthard Meinel (Leibniz-Institut für ökologische Raumentwicklung): Geoinformation als Grundlage für die Siedlungs- und Freiraumentwicklung (vorläufiger Titel)
Lars Behrens (Kommission für Geoinformationswirtschaft): GeoBusiness und Datenschutz
Preisverleihung Baden-Württemberg Challenge 2015 im Rahmen der European Satellite Navigation Competition
Session 1 „Virtuelles Gebäude“
Session 2 „Geoinformation für nachhaltige Energiesysteme und Klimaschutz“
Session 3 „Kleinräumige Statistik für die Kommunal- und Regionalplanung“
Wed, Nov 25, 2015, 10am, Print Media Academy Heidelberg

CrowdAnalyser Workshop 2015

The provenance and use of geospatial Big Data

Prof. Dr. Paul Longley - Fri, Nov 27, 2015, 10-11am, Seminar room, Insitute of Geography, Berliner Str. 48, 2nd floor

This presentation reports on the research activities of the Consumer Data Research Centre (CDRC), which is one of the UK’s current ‘Big Data’ investments funded by the Economic and Social Research Council (ESRC). Established in 2014, the CDRC’s mission is to bring sharper focus to the deployment and use of business and social media data, in support of decision-making across a widening spectrum of applications. After describing the three tier service structure of the CDRC, this presentation sets out the range of applications that are under development, the researcher and user interfaces that have been devised, and the ways in which business data may be evaluated and linked to conventional social survey sources. The presentation then focuses upon issues of establishing the provenance of business and social media data, and the wider implications of Big Data for the practice of social science. It also discusses some practical ways in which the value of new data sources may be reliably assessed.
Prof. Paul Longley is a lead scientist at University College of London (UCL).

Small area profiling through geodemographics

Guy Lansley - Fri, Nov 27, 2015 11-12am, Seminar room, Insitute of Geography, Berliner Str. 48, 2nd floor

Guy Lansley will present research results from an extended case study of the use of address register and Twitter geo-temporal demographics to understand the activity patterns of different ethnic groups in London. These patterns are linked to the geography of residence as depicted using conventional data sources such as the UK Census of Population.
Guy Lansley is a research associate at University College of London (UCL).

From TomoSAR Point Clouds To Objects

Muhammad Shahzad, PhD Candidate - Thu, Dec 17, 2015 4.15 pm, Hörsaal Berliner Straße 48

Synthetic aperture radar (SAR) projects a 3-D scene onto two naive coordinates i.e., range and azimuth. In order to fully localize a point in 3-D, advanced interferometric SAR (InSAR) techniques are required that process stack(s) of complex-valued SAR images to retrieve the lost third dimension (i.e., the elevation coordinate). Among other InSAR methods, SAR tomography (TomoSAR) is the most advanced 3-D imaging technique. By exploiting stack(s) of SAR images taken from slightly different positions, it builds up a synthetic aperture in the elevation direction that enables retrieval of precise 3-D position of dominant scatterers within one azimuth-range SAR image pixel. Geocoding these 3-D scatterer positions from SAR geometry to world (UTM) coordinates provide 3-D/4-D point clouds of the illuminated area with point density of around 1 million points/km2. Taking into consideration special characteristics associated to these point clouds e.g., low positioning accuracy, high number of outliers, gaps in the data and rich façade information due to side looking geometry, this presentation will demonstrate the object reconstruction potential of these point clouds using data acquired from both spaceborne and airborne platforms. Experimental results highlighting 3-D reconstruction of two object categories i.e., buildings and individual trees will be presented.
We demonstrate the capabilities of the proposed algorithms on a wide variety of data sets, including a backpack mounted mobile mapping system and a sensor skid for digitizing production lines.

Evaluating Travel Impedance Agreement among Online Road Network Data Providers & Visualizing the dynamics of health-related tweets: opportunities and computational challenges

Dr. Eric Delmelle, Associate Professor - Wed, Feb 17, 2016 4.15 pm, Hörsaal Berliner Straße 48

Evaluating Travel Impedance Agreement among Online Road Network Data Providers

Online mapping providers offer unprecedented access to spatial data and analytical tools; however the number of analytical queries that can be requested is usually limited. As such, providers using Volunteered Geographic Information (VGI) offer a viable alternative, given that the quality of the underlying spatial data is adequate. In this presentation, I will present results of an analysis aimed at assessing the agreement in travel distance estimates between Mapquest Open–which embraces OpenStreetMap (OSM) data, a VGI dataset-, and two other popular commercial providers, namely Google Maps™ and ArcGIS™ Online. We use a routing service Application Program Interface (API), to estimate travel impedance and the average number of OSM contributors. Origin-destination pairs are simulated for the state of North Carolina, U.S.A., and travel estimates reported for each of the providers. Results suggest (1) a strong correlation among all three road network providers, (2) agreement improves with increasing route distances and (3) decreases in areas with denser road network as providers may select different routes from a larger number of potential paths. Most importantly, travel estimates from Mapquest Open exhibit stronger similarity with both commercial providers when the average number of OSM contributors along the selected path is larger.

Visualizing the dynamics of health-related tweets: opportunities and computational challenges

Twitter, a form of social media, provides endless opportunities for public health. Information on disease symptoms, generated by twitter users, may alert health officials on the risk posed by a certain disease before it can be detected and officially confirmed in a lab. Certain tweets are georeferenced, and coupled with their temporal stamps, they have the potential to be used for space-time monitoring of diseases. This is particularly important to better understand disease dynamics, such as seasonality, direction, intensity and risk of diffusion to new regions. In this presentation, I will focus on the computational challenges associated to infer meaningful information from twitter related data, with an application to pollen-related tweets. I will then discuss a space-time framework to visualize the intensity of collected tweets in both space and time. I will discuss the impact of positional, temporal and attribute accuracy on the detection of space-time clusters from health-related tweets.

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