research-article

An exploratory visualization tool for mapping the relationships between animal movement and the environment

Authors:

Somayeh DodgeAuthors Info & Claims

MapInteract '14: Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Interacting with Maps

Pages 36 - 42

https://doi.org/10.1145/2677068.2677071

Published: 04 November 2014 Publication History

Abstract

Movement ecologists and environmental scientists are increasingly utilizing large volumes of spatiotemporal data collected from animal tracking and remote sensing of the environment to explore the environmental drivers of animal movements and long distance migrations. For scientists, the visual exploration and mapping of animal tracks in space and time and in relation to their environment is key to the generation of new hypotheses and investigation of dependencies. Effective visualization of such multidimensional data is a time consuming and challenging process. Creating professional, interactive, and fluid looking animations for public outreach and presentation purposes is similarly arduous. We present a new exploratory visualization tool for the analysis of animal movement datasets enriched with environmental variables and other miscellaneous data. This interactive visualization tool is designed to be effective and intuitive for users from biology and ecology disciplines, who are rather unfamiliar with GIS and mapping software. The tool is able to illustrate how environmental factors influence movement patterns of animals by offering to the user a variety of visual variables that can be combined in novel ways. We demonstrate the capabilities of this new visualization tool by analyzing the movement data of nine Galapagos Albatrosses and one Turkey Vulture migration track.

References

[1]

G. Andrienko, N. Andrienko, P. Bak, D. A. Keim, and S. Wrobel. Visual Analytics of Movement. Springer, 2013.

Digital Library

[2]

G. Andrienko, N. Andrienko, J. Dykes, S. I. Fabrikant, and M. Wachowicz. Geovisualization of dynamics, movement and change: key issues and developing approaches in visualization research. Information Visualization,. Information Visualization, 7(3--4): 173--180, 2008.

Digital Library

[3]

G. Andrienko, N. Andrienko, and S. Wrobel. Visual analytics tools for analysis of movement data. ACM SIGKDD Explorations Newsletter, 9(2): 38--46, 2007.

Digital Library

[4]

A. Colubri and B. Fry. Introducing processing 2.0. In ACM SIGGRAPH 2012 Talks, SIGGRAPH '12, pages 12:1--12:1, New York, NY, USA, 2012. ACM.

Digital Library

[5]

U. Demšar and K. Virrantaus. Space-time density of trajectories: exploring spatio-temporal patterns in movement data. International Journal of Geographical Information Science, 24(10): 1527--1542, 2010.

Digital Library

[6]

S. Dodge, G. Bohrer, K. Bildstein, S. C. Davidson, R. Weinzierl, M. J. Bechard, D. Barber, R. Kays, D. Brandes, J. Han, and M. Wikelski. Environmental drivers of variability in the movement ecology of turkey vultures (Cathartes aura) in North and South America. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 369(1643): 20130195, Jan. 2014.

[7]

S. Dodge, G. Bohrer, R. Weinzierl, S. C. Davidson, R. Kays, D. Douglas, S. Cruz, J. Han, D. Brandes, and M. Wikelski. The environmental-data automated track annotation (Env-DATA) system: linking animal tracks with environmental data. Movement Ecology, 1(1): 3, 2013.

[8]

M. A. Harrower and C. A. Brewer. Colorbrewer.org: An online tool for selecting color schemes for maps. The Cartographic Journal, 40: 27--37, 2003.

[9]

M.-J. Kraak. The space-time cube revisited from a geovisualization perspective. In Proc. 21st International Cartographic Conference, pages 1988--1996, 2003.

[10]

B. Kranstauber, A. Cameron, R. Weinzerl, T. Fountain, S. Tilak, M. Wikelski, and R. Kays. The Movebank data model for animal tracking. Environmental Modelling & Software, 26(6): 834--835, June 2011.

Digital Library

[11]

A.-K. Lautenschütz. Assessing the relevance of context for visualizations of movement trajectories. PhD thesis, 2011.

[12]

T. Nagel, F. Heidmann, E. Duval, J. Klerkx, and A. V. Moere. Unfolding - A Simple Library for Interactive Maps and Geovisualizations in Processing. GeoViz Workshop, March 2013.

[13]

T. F. Shipley, S. I. Fabrikant, and A.-K. Lautenschütz. Creating perceptually salient animated displays of spatiotemporal coordination in events. In Cognitive and Linguistic Aspects of Geographic Space, pages 259--270. Springer, 2013.

[14]

A. Slingsby, J. Dykes, and J. Wood. Using treemaps for variable selection in spatio-temporal visualisation. Information Visualization, 7(3--4): 210--224, 2008.

Digital Library

[15]

A. Slingsby, J. Strachan, J. Dykes, J. Wood, and P.-L. Vidale. Designing interactive graphics for validating and interpreting storm track model outputs. GeoViz Workshop, March 2011.

[16]

N. Willems, H. van de Wetering, and J. J. van Wijk. Visualization of vessel movements. Computer Graphics Forum, 28(3): 959--966, 2009.

Digital Library

[17]

O. Wood, J. Visualizing, J. Wood, A. Slingsby, and J. Dykes. City Research Online Visualizing the Dynamics of London's Bicycle Hire Scheme. Cartographica, 46(4): 239--251, 2011.

[18]

Q. Zhang, a. Slingsby, J. Dykes, J. Wood, M.-J. Kraak, C. a. Blok, and R. Ahas. Visual analysis design to support research into movement and use of space in Tallinn: A case study. Information Visualization, 13(3): 213--231, 2013.

Cited By

Onuki TMisue K(2023)Development of a Visual Analysis Tool for Seabird Behavior2023 Intelligent Methods, Systems, and Applications (IMSA)10.1109/IMSA58542.2023.10217617(112-117)Online publication date: 15-Jul-2023
https://doi.org/10.1109/IMSA58542.2023.10217617
Onuki TMisue K(2022)Visualization Tool for Comparative Analysis of Seabird Movement Data2022 26th International Conference Information Visualisation (IV)10.1109/IV56949.2022.00055(280-286)Online publication date: Jul-2022
https://doi.org/10.1109/IV56949.2022.00055
Dodge SToka MBae C(2021)DynamoVis 1.0: an exploratory data visualization software for mapping movement in relation to internal and external factorsMovement Ecology10.1186/s40462-021-00291-59:1Online publication date: 4-Nov-2021
https://doi.org/10.1186/s40462-021-00291-5
Show More Cited By

Index Terms

An exploratory visualization tool for mapping the relationships between animal movement and the environment
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Graphical user interfaces

Recommendations

Exploratory visualization of animal kinematics using instantaneous helical axes
EuroVis'08: Proceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization

We present novel visual and interactive techniques for exploratory visualization of animal kinematics using instantaneous helical axes (IHAs). The helical axis has been used in orthopedics, biomechanics, and structural mechanics as a construct for ...
Interactive exploration of movement data: a case study of geovisual analytics for fishing vessel analysis

The analysis of large movement datasets is a challenging task, because of their size and spatial complexity. This paper presents an interactive geovisual analytics approach named Hybrid Spatio-Temporal Filtering that integrates filtering of multiple ...
Incremental exploratory visualization of relationships in large codebases for program comprehension
OOPSLA '05: Companion to the 20th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications

As software systems grow in size and use more third-party libraries and frameworks, the need for developers to understand unfamiliar large codebases is rapidly increasing. In this demonstration, we present a tool, Relo that supports users' understanding ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

MapInteract '14: Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Interacting with Maps

November 2014

56 pages

ISBN:9781450331418

DOI:10.1145/2677068

Program Chairs:
Falko Schmid
University of Bremen, Germany
,
Chris Kray
University of Muenster, Germany
,
Holger Fritze
University of Muenster, Germany

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGSPATIAL: ACM Special Interest Group on Spatial Information

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 November 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

SIGSPATIAL '14

Sponsor:

SIGSPATIAL

SIGSPATIAL '14: 22nd SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 4, 2014

Texas, Dallas/Fort Worth

Acceptance Rates

Overall Acceptance Rate 17 of 20 submissions, 85%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

11
Total Citations
View Citations
339
Total Downloads

Downloads (Last 12 months)18
Downloads (Last 6 weeks)2

Reflects downloads up to 25 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Onuki TMisue K(2023)Development of a Visual Analysis Tool for Seabird Behavior2023 Intelligent Methods, Systems, and Applications (IMSA)10.1109/IMSA58542.2023.10217617(112-117)Online publication date: 15-Jul-2023
https://doi.org/10.1109/IMSA58542.2023.10217617
Onuki TMisue K(2022)Visualization Tool for Comparative Analysis of Seabird Movement Data2022 26th International Conference Information Visualisation (IV)10.1109/IV56949.2022.00055(280-286)Online publication date: Jul-2022
https://doi.org/10.1109/IV56949.2022.00055
Dodge SToka MBae C(2021)DynamoVis 1.0: an exploratory data visualization software for mapping movement in relation to internal and external factorsMovement Ecology10.1186/s40462-021-00291-59:1Online publication date: 4-Nov-2021
https://doi.org/10.1186/s40462-021-00291-5
Dodge SNoi E(2021)Mapping trajectories and flows: facilitating a human-centered approach to movement data analyticsCartography and Geographic Information Science10.1080/15230406.2021.1913763(1-23)Online publication date: 21-May-2021
https://doi.org/10.1080/15230406.2021.1913763
Storm‐Furru SBruckner S(2020)VA‐TRAC: Geospatial Trajectory Analysis for Monitoring, Identification, and Verification in Fishing Vessel OperationsComputer Graphics Forum10.1111/cgf.1396639:3(101-114)Online publication date: 18-Jul-2020
https://doi.org/10.1111/cgf.13966
Zhou YHe HRong JCheng YLi YZhong WJiang F(2020)Visual Analysis and Exploration of COVID-19 Based on Multi-source Heterogeneous Data2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00029(62-69)Online publication date: Nov-2020
https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00029
Williams HTaylor LBenhamou SBijleveld AClay Tde Grissac SDemšar UEnglish HFranconi NGómez‐Laich AGriffiths RKay WMorales JPotts JRogerson KRutz CSpelt ATrevail AWilson RBörger L(2019)Optimizing the use of biologgers for movement ecology researchJournal of Animal Ecology10.1111/1365-2656.1309489:1(186-206)Online publication date: Oct-2019
https://doi.org/10.1111/1365-2656.13094
Palleschi ACrielesi M(2019)A Visual Analytics System of Data Gathered from Colonial Seabirds2019 23rd International Conference Information Visualisation (IV)10.1109/IV.2019.00045(224-227)Online publication date: Jul-2019
https://doi.org/10.1109/IV.2019.00045
De Groeve JCagnacci FRanc NBonnot NGehr BHeurich MHewison AKroeschel MLinnell JMorellet NMysterud ASandfort RVan De Weghe N(2019)Individual Movement - Sequence Analysis Method (IM-SAM): characterizing spatio-temporal patterns of animal habitat use across landscapesInternational Journal of Geographical Information Science10.1080/13658816.2019.159482234:8(1530-1551)Online publication date: 5-Apr-2019
https://doi.org/10.1080/13658816.2019.1594822
Miller HDodge SMiller JBohrer G(2019)Towards an integrated science of movement: converging research on animal movement ecology and human mobility scienceInternational Journal of Geographical Information Science10.1080/13658816.2018.156431733:5(855-876)Online publication date: 15-Jan-2019
https://doi.org/10.1080/13658816.2018.1564317
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten