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Context-aware Movement Analysis (CAMA+)

Applicant Laube Patrick Olivier
Number 149705
Funding scheme Project funding
Research institution Geographisches Institut Universität Zürich
Institution of higher education University of Zurich - ZH
Main discipline Other disciplines of Environmental Sciences
Start/End 01.01.2014 - 31.12.2014
Approved amount 57'430.00
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All Disciplines (2)

Discipline
Other disciplines of Environmental Sciences
Other disciplines of Engineering Sciences

Keywords (6)

urban mobility; context-awareness; movement analysis; behavioral ecology; trajectory data; Geographic Information Science

Lay Summary (German)

Lead
Das Projekt CAMA+ und sein Vorläufer CAMA befassen sich mit der Entwicklung und Anwendung von neuartigen Methoden der geographischen Informationsverarbeitung, welche die quantitative Analyse der vielfältigen Beziehungen zwischen Bewegungspfaden und ihrem geographischen Kontext ermöglichen.
Lay summary

Durch rasante Fortschritte in der Kommunikations- und Lokalisationstechnologie wird es immer einfacher, die Bewegung von Menschen, Tieren oder Fahrzeugen im geographischen Raum aufzuzeichnen. Dabei entstehen sehr grosse Mengen von Bewegungsdaten, deren geographische Analyse unser Verständnis von Bewegungsprozessen aller Art verbessern kann. Derartige Analysen finden z. B. in der Wildtierforschung, der Verkehrsplanung oder zur Steuerung von Menschenmassen bei Grossanlässen Anwendung. Das Projekt CAMA+ und sein Vorläufer CAMA befassen sich dabei mit der Entwicklung und Anwendung von neuartigen Methoden der geographischen Informationsanalyse, welche speziell die Einbettung von Bewegungspfaden in ihren räumlichen Kontext untersuchen.

Während die Form von Bewegungspfaden und deren räumliche Anordnung bereits intensiv beforscht werden, erfährt die Einbettung der Pfade in den geographischen Kontext erstaunlich wenig Aufmerksamkeit. Seinen es nun Hirsche im Engadin, Pendler im Stau oder Raver an der Street Parade, die Bewegung von Individuen und Gruppen ist zugleich begünstigt als auch eingeschränkt durch den Charakter des Raumes in den die Bewegung eingebettet ist. CAMA+ entwickelt Methoden der Geographischen Informationsanalyse, welche es erlauben, die vielfältigen Beziehungen zwischen Bewegungspfaden und dem geographischen Raum in den die Bewegung eingebettet ist, quantitativ zu beschreiben.

Unsere Arbeit liefert Methoden zur Bewältigung der grossen Menge raum-zeitlicher Information die unsere Informations- und Kommunikationsgesellschaft anhäuft. Die Ergebnisse werden es z.B. Planern ermöglichen, effizientere Verkehrsnetze zu planen oder sichere Anlagen für Massenveranstaltungen zu entwerfen. In der biologischen Grundlagenforschung dienen unsere Ergebnisse dazu, das Verhalten von Tieren besser im Kontext ihres Lebensraumes zu verstehen und können damit zur Erhaltung bedrohter Lebensräume beitragen. 

Direct link to Lay Summary Last update: 08.11.2013

Responsible applicant and co-applicants

Employees

Name Institute

Publications

Publication
Computational Movement Analysis
Laube Patrick (2014), Computational Movement Analysis, Springer, Berlin Heidelberg.
Scale Effects in Relating Movement to Geographic Context
Gschwend Christian, Laube Patrick (2014), Scale Effects in Relating Movement to Geographic Context, in Proceedings of the 8th International Conference on Geographic Information Science, Vienna, A.

Collaboration

Group / person Country
Types of collaboration
Emiel van Loon, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam Netherlands (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Matt Duckham, Infrastructure Engineering, The University of Melbourne Australia (Oceania)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Ross Purves, Department of Geography, University of Zurich Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Research Infrastructure

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
8th International Conference on Geographic Information Science GIScience 2014 Talk given at a conference Scale Effects in Relating Movement to Geographic Context 23.09.2014 Wien, Austria Gschwend Christian;
Analysis of Movement Data, GIScience Workshop 2014 Talk given at a conference The low hanging fruit is gone – Achievements and Challenges of Computational Movement Analysis 23.09.2014 Wien, Austria Laube Patrick Olivier;
Dagstuhl Seminar 14132: Interaction and Collective Movement Processing Talk given at a conference Computational Movement Analysis - My take on GIScience’s contribution to a better understanding of movement processes 25.03.2014 Schloss Dagstuhl, Germany Laube Patrick Olivier;


Associated projects

Number Title Start Funding scheme
129963 Context-aware Movement Analysis (CAMA) 01.01.2011 Project funding

Abstract

In this proposal we propose a continuation of the SNF project CAMA (No. 200021_129963). The requested continuation aims at providing a seamless extension for the PhD student working on the pro-ject, allowing consolidating existing result. The proposed additional research will take advantage of two recent developments in the field: (i) The emergence of a new type of multi-sensor data describing the activity of moving objects. (ii) The arrival increased accessibility of statistical tools explicitly working the spatiotemporal footprint of movement data.The projects CAMA and CAMA+ both contribute to the current discussion on movement analysis in geographic information science. Whereas most work in the area focuses on geo-metric properties and arrangement patterns of movement traces (trajectories), much less attention is giv-en to the embedding of the movement in its environment enabling and constraining that movement. Hence, the overall research question of CAMA and its continuation CAMA+ can be stated as follows: How can data capturing the movement of individuals be quantitatively related to the spatial characteris-tics of the natural and built geocontext embedding, hence enabling and constraining that movement?Within the project so far we have built up both the theoretical underpinnings and a practical workbench, as well as an extensive suite of case studies allowing us to tackle the proposed re-search questions. Our research has contributed to the theory of movement in two ways. Firstly, a list of specific movement analysis tasks explicitly integrating geocontext emerged extensive applied work on a set of case studies. Secondly, we developed a formal intersection model categorizing the interrelation of conceptual models of movement and the embedding context. The intersection model prompted interest-ing movement and context combinations for which adequate methods were developed and evaluated. Work has been presented at several conference and workshops (GISRUK 2012, AGILE 2012, MODAP clinic Delft 2012) and a journal article is close to completion to be submitted to a special issue of the In-ternational Journal of Geographical Information Science.Work in the project extension will focus on three issues: Firstly, we will develop a method for combining the field-based movement representation of Brownian bridges with land use data. Secondly, we will take advantage of access to a data set representing a new form of multi-sensor activity data, here monitoring sea birds. Such activity data not only offers location fixes but also additional sen-sor readings describing characteristics of the mobile agent. We’ll develop a method allowing the integra-tion of location, additional sensor data and geocontext for labeling different behaviors of the observed birds. Finally and thirdly, we will also benefit from an ongoing collaboration with the University of Mel-bourne, where we will contribute a tailored analysis method supporting a data mining project searching for causal relations between fish movement and environmental factors.The project will be hosted at the GIScience Center at the Department of Geography, University of Zurich. The project is embedded in and supported by the movement research group at GIScience center and will continue to benefit from ongoing international collaborations (initiated during the COST Action MOVE IC0903 “Knowledge Discovery from Moving Objects” and arising through the ARC project “sense+know”).
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