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Towards a cartography of wildlife moves

Towards a cartography of wildlife moves Elodie Buard PhD began in January 2009 directed by Anne Ruas (COGIT) and Léna Sanders (Géographie-Cités ) « Spatio-temporal dynamics interaction of space and wildlife » Journée cartactive – 5 juin 2009 Outline Context multiple data sources…

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Towards a cartography of wildlife moves

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  1. Towards a cartography of wildlife moves Elodie Buard PhD began in January 2009 directed by Anne Ruas (COGIT) and Léna Sanders (Géographie-Cités) « Spatio-temporal dynamics interaction of space and wildlife » Journée cartactive – 5 juin 2009

  2. Outline • Context • multiple data sources… • …to model the trajectories • …and to cartography wildlife presence • conclusion

  3. Context • Hwange national park, Zimbabwe • In this park, biologists have noticed (Fritz 2007) : • 1- Elephant population increases and moves • => modify the space (empty spaces, not enough water) • 2- Space is changing naturally by seasons or rainfalls • modify wildlife moves What are the interactions between space and wildlife at different scales of time and space ?

  4. Objectives What are the interactions between space and wildlife at different scales of time and space ? • Identifying wildlife moves • at different scales (spatial and temporal) • Cartography wildlife moves • Animated dynamic maps (video) • Or static maps showing moves

  5. Objectives historic data of wildlife and space (since 1970) Cartographic output Static/dynamic Calculations Data mining

  6. Multiple sources

  7. Multiple sources • Data source (space) are various • Aerial photographs • Vegetation maps • DTM

  8. Multiple sources • Observed data are various… in spatial scale

  9. Multiple sources • Observed data are various… in temporal scale Wildlife census on road and water points : - regular data in time - but representative in space

  10. Multiple sources vegetation : exhaustive in space but versionning (only few years) and varying in the season, in fonction of rainfalls

  11. Model the Trajectories • Identify trajectories of animal or groups • Typically: Trajectories = {moves and stops} during a certain period

  12. Model the Trajectories

  13. Model the Trajectories • But: we don’t known them directly -> calculations • From data census on roads • A observer trajectory needs to be done as he is mobile as well! CAR ELEPHANT

  14. Model the Trajectories • Observer follows a path and stops to each observation at a time

  15. Cartography of moves • Bertin: graphic semiology for moves -> Diffusion of phenomena, construction of spatial features -> Moves of individuals

  16. Cartography of moves • Kraak from Minard • Time=3D • Stops = nodes • Size of troups= size of the line

  17. Cartography of wildlife moves • GPS tracking not done on herbivores • so trajectories are constructed from • Calculations and hypothesis • Expert knowledge • Here cartography of individual moves • So far : wildlife presence depending on the observation time

  18. Expert knowledge: elephant move • Aggregation in dry season • Time step: the year

  19. Expert knowledge: zebra move • 2 time steps together: the week and the year • As a result, 2 spatial scales together

  20. Expert knowledge: giraffe move • =>definite translation • Over 30 years • No moves α season => a territory

  21. Expert knowledge: giraffe move To simplify the giraffe move, in one map: The giraffe does not move in relation to rainfall

  22. Maps of wildlife presence • Animated maps, feature by feature • Time step: the year • Spatial scale: the park (macro scale) • Based on water points counting • => Inter-year analysis

  23. Elephants : Maps of wildlife presence

  24. Impalas : Maps of wildlife presence

  25. Conclusion of the work • Maps showing moves are not necessary animated • Animation maps are to be done for roads census as time step is finer • Analyse of data imprecision to emphasis the gaps

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