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From Points to Habitat: Relating Environmental Information to GPS Positions

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Spatial Database for GPS Wildlife Tracking Data

Abstract

Animals move in and interact with complex environments that can be characterised by a set of spatial layers containing environmental data. Spatial databases can manage these different data sets in a unified framework, defining spatial and non-spatial relationships that simplify the analysis of the interaction between animals and their habitat. A large set of analyses can be performed directly in the database with no need for dedicated GIS or statistical software. Such an approach moves the information content managed in the database from a ‘geographical space’ to an ‘animal’s ecological space’. This more comprehensive model of the animals’ movement ecology reduces the distance between physical reality and the way data are structured in the database, filling the semantic gap between the scientist’s view of biological systems and its implementation in the information system. This chapter shows how vector and raster layers can be included in the database and how you can handle them using (spatial) SQL. The database built so far in Chaps. 2, 3, 4 and 5 is extended with environmental ancillary data sets and with an automated procedure to intersect these layers with GPS positions.

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Notes

  1. 1.

    Provincia autonoma di Trento—Servizio Prevenzione Rischi—Ufficio Previsioni e pianifi-cazione, http://www.meteotrentino.it.

  2. 2.

    http://www.openstreetmap.org.

  3. 3.

    http://www.istat.it/it/strumenti/cartografia.

  4. 4.

    http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-clc2006-100-m-version-12-2009.

  5. 5.

    http://srtm.csi.cgiar.org/.

  6. 6.

    http://www.postgresql.org/docs/9.2/static/app-psql.html.

  7. 7.

    http://postgis.net/docs/manual-2.0/using_raster.xml.html#RT_Raster_Loader.

  8. 8.

    http://www.gdal.org/.

  9. 9.

    http://www.gdal.org/gdalinfo.html.

  10. 10.

    http://www.gdal.org/gdal_translate.html.

  11. 11.

    http://www.gdal.org/gdalwarp.html.

  12. 12.

    http://www.eea.europa.eu/publications/COR0-landcover.

  13. 13.

    http://www.postgresql.org/docs/9.2/static/tutorial-window.html.

  14. 14.

    You can skip this step and speedup the process by simply calculating the environmental attributes with an update query.

References

  • Jarvis A, Reuter HI, Nelson A, Guevara E (2008) Hole-filled seamless SRTM data V4. International centre for tropical agriculture (CIAT)

    Google Scholar 

  • Obe OR, Hsu LS (2011) PostGIS in action. Manning Publications Company, Greenwich

    Google Scholar 

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Correspondence to Ferdinando Urbano .

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Urbano, F., Basille, M., Racine, P. (2014). From Points to Habitat: Relating Environmental Information to GPS Positions. 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_6

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