Abstract
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.
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Basille, M., Urbano, F., Racine, P., Capecchi, V., Cagnacci, F. (2014). Tracking Animals in a Dynamic Environment: Remote Sensing Image Time Series. In: Urbano, F., Cagnacci, F. (eds) Spatial Database for GPS Wildlife Tracking Data. Springer, Cham. https://doi.org/10.1007/978-3-319-03743-1_7
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