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Erschienen in:

2013 | OriginalPaper | Buchkapitel

2. Classes for Spatial Data in R

verfasst von : Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-Rubio

Erschienen in: Applied Spatial Data Analysis with R

Verlag: Springer New York

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Abstract

Many disciplines have influenced the representation of spatial data, both in analogue and digital forms. Surveyors, navigators, and military and civil engineers refined the fundamental concepts of mathematical geography, established often centuries ago by some of the founders of science, for example by al-Khwārizmı̄. Digital representations came into being for practical reasons in computational geometry, in computer graphics and hardware-supported gaming, and in computer-assisted design and virtual reality. The use of spatial data as a business vehicle has been spurred early in the present century by consumer wired and mobile broadband penetration and distributed server farms, with examples being Google Earth^TM, Google Maps^TM, and others. There are often interactions between the graphics hardware required and the services offered, in particular for the fast rendering of scene views.

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Vorheriges Kapitel Hello World: Introducing Spatial Data

Nächstes Kapitel Visualising Spatial Data

Free documentation, including the very useful ‘An Introduction to R ’ (Venables et al., 2013), may be downloaded from CRAN.

str can take additional arguments to control its output.

Data downloaded with permission from SEAMAP (Read et al., 2003), data set 105.

http://www.ngdc.noaa.gov/mgg/shorelines/shorelines.html.

http://www.opengeospatial.org/.

Some maptools functions use Gregory R. Warnes’ mixedorder sort from gtools to sort integer-like strings in integer order.

http://www.biostat.umn.edu/~brad/data/state-sat.dat, data here supplemented with variable names and state names as used in maps.

Downloaded from the seamless data distribution system for 3 arcsec ‘Finished’ (90 m) data, http://earthexplorer.usgs.gov/; the data can be downloaded as 1^∘ square tiles.

http://cran.r-project.org/web/packages/raster/index.html.

Adler, J. (2010). R in a Nutshell. O’Reilly, Sebastopol, CA.

Becker, R. A., Chambers, J. M., and Wilks, A. R. (1988). The New S Language. Chapman & Hall, London.MATH

Chambers, J. M. (1998). Programming with Data. Springer, New York.MATHCrossRef

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Dalgaard, P. (2008). Introductory Statistics with R , (second edition). Springer, New York.

Herring, J. R. (2011). OpenGIS®; implementation standard for geographic information - simple feature access - part 1: Common architecture. Technical Report 1.2.1, OGC 06-103r4, Open Geospatial Consortium Inc.

Hijmans, R. J. (2012b). Introduction to the ‘raster’ package. Technical report, raster vignette.

Hijmans, R. J. (2012c). Writing functions with the “raster” package. Technical report, raster vignette.

Kresse, W., Danko, D. M., and Fadaie, K. (2012). Standardization. In Kresse, W. and Danko, D. M., editors, Springer Handbook of Geographic Information, pages 393–565. Springer, Berlin Heidelberg.

Murrell, P. (2011). R Graphics. Chapman & Hall/CRC, Boca Raton.

Murrell, P. (2012). It’s Not What You Draw, It’s What You Don’t Draw. The R Journal, 4(2):13–18.

Nichols, W., Resendiz, A., J.A.Seminoff, and Resendiz, B. (2000). Transpacific migration of a loggerhead turtle monitored by satellite telemetry. Bulletin of Marine Science, 67:937–947.

Read, A. J., Halpin, P. N., Crowder, L. B., Hyrenbach, K. D., Best, B. D., and Freeman, S. A. (2003). OBIS-SEAMAP: mapping marine mammals, birds and turtles. Duke University. World Wide Web electronic publication. http://seamap.env.duke.edu, Accessed on April 01, 2008.

Slocum, T. A., McMaster, R. B., Kessler, F. C., and Howard, H. H. (2005). Thematic Cartography and Geographical Visualization. Pearson Prentice Hall, Upper Saddle River, NJ.

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Wall, M. M. (2004). A close look at the spatial structure implied by the CAR and SAR models. Journal of Statistical Planning and Inference, 121:311–324.MathSciNetMATHCrossRef

Titel: Classes for Spatial Data in R
verfasst von: Roger S. Bivand
Edzer Pebesma
Virgilio Gómez-Rubio
Verlag: Springer New York
Buch: Applied Spatial Data Analysis with R
Print ISBN: 978-1-4614-7617-7

Electronic ISBN: 978-1-4614-7618-4

Copyright-Jahr: 2013
DOI: https://doi.org/10.1007/978-1-4614-7618-4_2

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