Journal cover Journal topic
Proceedings of the ICA
Journal topic
Volume 1
Proc. Int. Cartogr. Assoc., 1, 93, 2018
https://doi.org/10.5194/ica-proc-1-93-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Proc. Int. Cartogr. Assoc., 1, 93, 2018
https://doi.org/10.5194/ica-proc-1-93-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  16 May 2018

16 May 2018

Visualization on the Web of 20 Years of Crop Rotation and Wildlife Co-Evolutions

Christine Plumejeaud-Perreau1, Cyril Poitevin1, and Vincent Bretagnolle2 Christine Plumejeaud-Perreau et al.
  • 1LIENSs, UMR 7266 CNRS, 17000 La Rochelle, France
  • 2CEBC, UMR 7372 CNRS, 79360 Villiers-en-Bois, France

Keywords: Interactive data visualization, environmental data, spatio-temporal analysis

Abstract. The accumulation of evidences of the effects of intensive agricultural practices against wildlife fauna and flora, and biodiversity in general, has been largely published in scientific papers (Tildman, 1999). However, data serving as sup-port to their conclusions are often kept hidden behind research institutions. This paper presents a data visualization sys-tem opened on the Web allowing citizens to get a comprehensive access to data issued from such kind of research institution, collected for more than 20 years. The Web Information System has been thought in order to ease the comparison of data issues from various databases describing the same object, the agricultural landscape, at different scales and through different observation devices. An interactive visualization is proposed in order to check co-evolution of fauna and flora together with agricultural practices. It mixes aerial orthoimagery produced since 1950 with vectorial data showing the evolutions of agricultural parcels with those of a few sentinel species such as the Montagu's harrier. This is made through a composition of maps, charts and time lines, and specific tools for comparison. A particular concern is given to the observation effort bias in order to show meaningful statistical aggregates.

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