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Quaestiones Geographicae

The Journal of Adam Mickiewicz University

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Dynamic Visualization Of Sensor Measurements: Context Based Approach

Radim Stampach
  • Corresponding author
  • Laboratory on Geoinformatics and Cartography, Masaryk University, Brno, Czech Republic
  • Email:
/ Petr Kubicek
  • Laboratory on Geoinformatics and Cartography, Masaryk University, Brno, Czech Republic
/ Lukas Herman
  • Laboratory on Geoinformatics and Cartography, Masaryk University, Brno, Czech Republic
Published Online: 2015-12-30 | DOI: https://doi.org/10.1515/quageo-2015-0020


An amount of data measured with sensors is increasing year to year. Every sensor has a location and sensor data are mostly measured for long time period, so visualization of location and regular updating of visualized value is necessary. Various characteristics (e.g. meteorological conditions) can be automatically read at frequent intervals and those readings can be aggregated into the interactive map visualization. This map must be not only legible but also understandable also for readers that are experts in their specialisation, however, not in cartography. This paper presents possibilities of using and implementation of adaptive cartography and visual seeking principles for interactive visualization and analysis of sensor based data measured in real time. Our solution is described on experimental application for precise farming that we developed during research project Agrisensor.

Keywords: adaptive cartography; visual seeking; interactive map; sensor data; precise farming


  • Andrienko N., Andrienko G., 2006. Exploratory Analysis of Spatial and Temporal Data. Springer Verlag, Berlin–Heidelberg.

  • Andrienko G., Andrienko N., Savinov A., 2001. Choropleth Maps: classification revisited. In: Proceedings of ICC 2001: 6–10 August 2001. Beijing. Edited by Scientific and Technical Program Committee LOC: 1209–1219. Online: http://geoanalytics.net/and/papers/ica01.pdf (accessed 20 May 2014).

  • Beroll H., Berke O., Wilson J., Barker I.K., 2007. Investigating the spatial risk distribution of West Nile virus disease in birds and humans in southern Ontario from 2002 to 2005. Population Health Metrics 5(3). DOI: 10.1186/1478-7954-5-3. [Crossref]

  • Blok C.A., 2005. Dynamic visualization variables in animation to support monitoring of spatial phenomena. Utrecht, Enschede, Universiteit Utrecht, ITC, 2005. ITC Dissertation 119, Nederlandse Geografische Studies = Netherlands Geographical Studies 328. Online: http://www.itc.nl/library/Papers_2005/phd/blok.pdf (accessed 30 April 2014).

  • van Elzakker C.P.J.M., Delikostidis I., van Oosterom P. J.M., 2008. Field-Based Usability Evaluation Methodology for Mobile Geo-Applications. Cartographic Journal 45(2): 140–149. DOI: 10.1179/174327708X305139. [Crossref]

  • Erharuyi N., Fairbairn D., 2005. Task-centred adaptation of geographic information to support disaster management. In: van Oosterom P., Zlatanova S., Fendel E.M. (eds), Geo-Information for Disaster Management. Springer Verlag, Berlin–Heidelberg: 997–1008. DOI: 10.1007/2F3-540-27468-5_70. [Crossref]

  • Geryk E., Dite P., Kozel J., Kubicek P., Konecny M., Stampach R., Pesek M., 2010. Nádorové multiplicity u české populace (Cancer multiplicities in the Czech population). Casopis lekaru ceskych 4: 178–183.

  • Geryk E., Stampach R., Kozel J., Dite P., Konecny M., 2013. Výskyt dalších novotvarů u nemocných s leukemií (The incidence of other neoplasms in patients with leukemia). Onkologie 3: 135–139. Online: http://www.onkologiecs.cz/pdfs/xon/2013/03/08.pdf (accessed 5 May 2014).

  • Griffin A.L., Fabrikant S.I., 2012. More Maps, More Users, More Devices Means More Cartographic Challenges. Cartographic Journal 49(4): 298–301. DOI: 10.1179/0008704112Z.00000000049. [Crossref]

  • Grönlund A., 2005. Methodology for making geographic information relevant to crisis management. In: van Oosterom P., Zlatanova S., Fendel E.M. (eds), Geo-information for disaster management. Springer Verlag, Berlin–Heidelberg: 121–128. DOI: 10.1007/2F3-540-27468-5_9. [Crossref]

  • Herman L., Reznik T., 2013. Web 3D Visualization of Noise Mapping for Extended INSPIRE Buildings Model. In: Hrebicek J., Schimak G., Kubasek M., Rizzoli A.E., Environmental Software Systems. Fostering Information Sharing. Springer Verlag, Berlin–Heidelberg: 414–424, IFIP Advances in Information and Communication Technology. DOI: 10.1007/978-3-642-41151-9_39. [Crossref]

  • Iosifescu I., 2011. Cartographic Web Services. Dissertation, ETH Zurich, Switzerland. Online: http://e-collection.library.ethz.ch/eserv/eth:4541/eth-4541-02.pdf (accessed 30 April 2014).

  • Iosifescu I., Hurni L., 2010. GIS Platform for Interdisciplinary Environmental Research. In: Proceedings of the 7th ICA Mountain Cartography Workshop, 1–5 September 2010, Borsa, Romania. Online: http://www.mountaincartography.org/publications/papers/papers_borsa_10/09_iosifescu.pdf (accessed 2 May 2014).

  • Kozel J., Stampach R., Zboril J., 2009. Adaptive map visualization: from context selection to web service configuration. In: Proceedings of 3rd ISDE DIGITAL EARTH SUMMIT, Nessebar, Bulgaria.

  • Kozel J., Stampach R., Zboril J., 2011. Monitoring weather situation in the field: an approach based on Sensor observation service. In: Jalovecky R., Stefek A., Proceedings of the International Conference on Military Technologies 2011 (ICMT’11). University of Defence, Brno: 1315–1322.

  • Kubicek P., Kozel J., Stampach R., Lukas V., 2013. Prototyping the visualization of geographic and sensor data for agriculture. Computers and Electronics in Agriculture 97: 83–91. DOI: 10.1016/j.compag.2013.07.007. [Crossref] [Web of Science]

  • Lai P.-Ch., Yeh A.G.-O., 2004. Assessing the Effectiveness of Dynamic Symbols in Cartographic Communication. The Cartographic Journal 41(3): 229–244. DOI: 10.1179/000870404X13300. [Crossref]

  • MacEachren A.M., 1995. How Maps Work: Representation, Visualization, and Design. Guilford Press, New York, USA.

  • MacEachren A.M., Kraak M.J., 2001. Research Challenges in Geovisualization. Cartography and Geographic Information Science 1: 3–12. [Web of Science]

  • Medyńska-Gulij B., 2010. Map Compiling, Map Reading, and Cartographic Design in “Pragmatic Pyramid of Thematic Mapping”. Quaestiones Geographicae 29(1): 57–63. DOI: 10.2478/v10117-010-0006-5. [Crossref]

  • Meng L., 2005. Egocentric Design of Map-Based Mobile Services. The Cartographic Journal 42(1): 5–13. DOI: 10.1179/000870405X57275. [Crossref]

  • Mishra K.K., Punia M., Mina H.L., 2007. Adaptive approach to mobile cartography. In: Vettore A., El-Sheimy N. (eds), The 5th International Symposium on Mobile Mapping Technology, MMT ‘07 May 29–31, 2007, Padua, Italy. ISPRS Archives – Volume XXXVI-5/C55, 2007. Online: http://www.isprs.org/proceedings/XXXVI/5-C55/papers/mishra_kamal.pdf (accessed 30 April 2014).

  • Ooms K., 2012. Maps, how do users’ see them. An in depth investigation of the map users’ cognitive processes. Dissertation in Ghent University. Online: http://cartogis.ugent.be/kooms/PhD/PhD_kooms.pdf (accessed 30 May 2014).

  • Opach T., Midtbø T., Nossum A., 2011. A New Concept of Multi-Scenario, Multi-Component Animated Maps for the Visualization of Spatio-Temporal Landscape Evolution. Miscellanea Geographica 1: 215–229. DOI: 10.2478/v10288-012-0013-6. [Crossref]

  • Pickle L.W., 2003. Usability testing of map design. In: Braverman A., Hesterberg T., Minnotte M., Symanzik J., Said Y. (eds), Proceedings of the 35th Symposium on the Interface. Salt Lake City, Utah: 42–56. Online: http://www.interfacesymposia.org/I03/master.pdf (accessed 25 January 2014).

  • Plaisant C., 2004. The challenge of information visualization evaluation. In: Proceedings of the Working Conference on Advanced Visual Interfaces. ACM, New York, NY, USA: 109–116. Online: http://triton.cc.gatech.edu/hci-seminar/uploads/1/The%20Challenge%20of%20Information%20Visualization%20Evaluation.pdf (accessed 15 April 2014).

  • Pravda J., 2003. Mapový jazyk (Map language). Univerzita Komenskeho Bratislava, Prirodovedecka fakulta, Bratislava.

  • Reichenbacher T., 2004. Mobile Cartography – Adaptive Visualisation of Geographic Information on Mobile Devices. Disertation Thesis. Technische Universität München.

  • Richter R., 2009. Visualizing sensor data. Media Informatics Advanced Seminar on Information Visualization. Online: https://www.medien.ifi.lmu.de/lehre/ws0809/hs/docs/richter.pdf (accessed 20 April 2014).

  • Riquelme L., Soto F., Suardiaz J., Sanchez P., Iborra A., Vera J.A., 2009. Wireless sensor networks for precision horticulture in Southern Spain. Computers and Electronics in Agriculture 68: 25–35. DOI: 10.1016/j.compag.2009.04.006. [Crossref]

  • Roberts J.C., Wright M.A.E., 2006. Towards Ubiquitous Brushing for Information Visualization. In: Proceedings of the Information Visualization, 10th International Conference on Information Visualisation, 5–7 July 2006, London, UK. DOI: 10.1109/IV.2006.113. [Crossref]

  • Shneiderman B., 1996. The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings IEEE Symposium on Visual Languages: 336–343. Online: http://www.cs.ubc.ca/~tmm/courses/old533/readings/shneiderman96eyes.pdf (accessed 15 April 2014).

  • Slocum T., 2005. Thematic Cartography and Geographic Visualization. Pearson Education, Upper Saddle River.

  • Stachs C., Jones R., Cornford D., Kiesow M., Williams M., Pebesma E., 2012. Representing Uncertainties in the Sensor Web. In: Proceedings of workshop Sensing a Changing World 2. Online: https://www.wageningenur.nl/en/show/Sensing-a-Changing-World-2.htm (accessed 15 June 2015).

  • Stampach R., Geryk E., 2012. Health statistics in international databases and their cartographic visualization. Quaestiones Geographicae 31(1): 77–88. DOI: 10.2478/v10117-012-0029-1. [Crossref]

  • Stampach R., Geryk E., 2011. Mezinárodní databáze zdravotních statistik a jejich dostupné údaje (International health statistics databases and available data). Casopis lekaru ceskych 7: 384–388.

  • Stanek K., Friedmannova L., Kubicek P., Konecny M., 2010. Selected issues of cartographic communication optimization for emergency centers. International Journal of Digital Earth 4: 316–339. DOI: 10.1080/17538947.2010.484511. [Crossref]

  • Turdukulov U.D., 2007. Visualizing the evolution of image features in timeseries: supporting the exploration of sensor data. Enschede, ITC, 2007. ITC Dissertation 149. Online: http://www.itc.nl/library/papers_2007/phd/turdukulov.pdf (accessed 15 April 2014).

  • Tynklova K., 2012. Vybrané aspekty kartografické vizualizace dat senzorů (Selected aspects of sensor data geovisualization). Master thesis. Masaryk University, Faculty of Science, Brno. Online: http://is.muni.cz/th/212865/prif_m/DP_Tynklova.pdf (accessed 15 March 2014).

  • Vozenilek V., Kanok J., 2011. Metody tematické kartografie: vizualizace prostorových jevů (Methods of thematic cartography: visualization of spatial phenomenon). Univerzita Palackeho v Olomouci, Olomouc.

About the article

Received: 2014-07-07

Revised: 2015-07-24

Published Online: 2015-12-30

Published in Print: 2015-09-01

Citation Information: Quaestiones Geographicae, ISSN (Online) 2081-6383, DOI: https://doi.org/10.1515/quageo-2015-0020. Export Citation

© 2015 Faculty of Geographical and Geological Sciences, Adam Mickiewicz University. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)

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