Tracking Animals in a Dynamic Environment: Remote Sensing Image Time Series

  • Mathieu BasilleEmail author
  • Ferdinando Urbano
  • Pierre Racine
  • Valerio Capecchi
  • Francesca Cagnacci


This chapter looks into the spatiotemporal dimension of both animal tracking data sets and the dynamic environmental data that can be associated with them. Typically, these geographic layers derive from remote sensing measurements, commonly those collected by sensors deployed on earth-orbiting satellites, which can be updated on a monthly, weekly or even daily basis. The modelling potential for integrating these two levels of ecological complexity (animal movement and environmental variability) is huge and comes from the possibility to investigate processes as they build up, i.e. in a full dynamic framework. This chapter’s exercise will describe how to integrate dynamic environmental data in the spatial database and join to animal locations one of the most used indices for ecological productivity and phenology, the normalised difference vegetation index (NDVI) derived from MODIS. The exercise is based on the database built so far in  Chaps. 2,  3,  4,  5 and  6.


NDVI Raster time series Spatial database Spatiotemporal intersection 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mathieu Basille
    • 1
    Email author
  • Ferdinando Urbano
    • 2
  • Pierre Racine
    • 3
  • Valerio Capecchi
    • 4
  • Francesca Cagnacci
    • 5
  1. 1.Fort Lauderdale Research and Education CenterUniversity of FloridaFort LauderdaleUSA
  2. 2.Università Iuav di VeneziaVeniceItaly
  3. 3.Centre for Forest ResearchUniversity Laval, Pavillon Abitibi-Price, 2405 de la TerrasseQuebec CityCanada
  4. 4.Istituto di BiometeorologiaConsiglio Nazionale delle RicercheSesto FiorentinoItaly
  5. 5.Biodiversity and Molecular Ecology DepartmentResearch and Innovation CentreS.Michele all’AdigeItaly

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