1.6 Exercises

• Think about the terms ‘GIS’, ‘GDS’ and ‘geocomputation’ described above. Which (if any) best describes the work you would like to do using geo* methods and software and why?

• Provide three reasons for using a scriptable language such as R for geocomputation instead of using an established GIS program such as QGIS.

• Name two advantages and two disadvantages of using mature vs recent packages for geographic data analysis (for example sp vs sf).

References

Eddelbuettel, Dirk, and James Joseph Balamuta. 2018. “Extending R with C++: A Brief Introduction to Rcpp.” The American Statistician 72 (1): 28–36. https://doi.org/10.1080/00031305.2017.1375990.

Pebesma, Edzer, Daniel Nüst, and Roger Bivand. 2012. “The R Software Environment in Reproducible Geoscientific Research.” Eos, Transactions American Geophysical Union 93 (16): 163–63. https://doi.org/10.1029/2012EO160003.

Longley, Paul A., Sue M. Brooks, Rachael McDonnell, and Bill MacMillan, eds. 1998. Geocomputation: A Primer. Chichester, Eng. ; New York: Wiley.

Openshaw, Stan, and Robert J. Abrahart, eds. 2000. Geocomputation. London ; New York: CRC Press.

Longley, Paul. 2015. Geographic Information Science & Systems. Fourth edition. Hoboken, NJ: Wiley.

Talbert, Richard J. A. 2014. Ancient Perspectives: Maps and Their Place in Mesopotamia, Egypt, Greece, and Rome. University of Chicago Press.

Neteler, Markus, and Helena Mitasova. 2008. Open Source GIS: A GRASS GIS Approach. Third. New York, NY: Springer.

Coppock, J Terry, and David W Rhind. 1991. “The History of GIS.” Geographical Information Systems: Principles and Applications, Vol. 1. 1 (1): 21–43.

Wulf, Andrea. 2015. The Invention of Nature: Alexander von Humboldt’s New World. New York: Alfred A. Knopf.

Livingstone, David N. 1992. The Geographical Tradition: Episodes in the History of a Contested Enterprise. Oxford, UK ; Cambridge, USA: John Wiley & Sons Ltd.

Bivand, Roger, Edzer J Pebesma, and Virgilio Gómez-Rubio. 2013. Applied Spatial Data Analysis with R. Vol. 747248717. Springer.

The Economist. 2016. “The Autonomous Car’s Reality Check.” The Economist.

Wickham, Hadley. 2014a. Advanced R. CRC Press.

Chambers, John M. 2016. Extending R. CRC Press.

Brzustowicz, Michael R. 2017. Data Science with Java: [Practical Methods for Scientists and Engineers]. First. Beijing Boston Farnham: OReilly.

Garrard, Chris. 2016. Geoprocessing with Python. Shelter Island, NY: Manning Publications.

Bivand, Roger, and Albrecht Gebhardt. 2000. “Implementing Functions for Spatial Statistical Analysis Using the Language.” Journal of Geographical Systems 2 (3): 307–17.

Bivand, Roger, and Markus Neteler. 2000. “Open Source Geocomputation: Using the R Data Analysis Language Integrated with GRASS GIS and PostgreSQL Data Base Systems.” In Proceedings of the 5th International Conference on GeoComputation, edited by Markus Neteler and Roger S. Bivand.

Rowlingson, B. S, and P. J Diggle. 1993. “Splancs: Spatial Point Pattern Analysis Code in S-Plus.” Computers & Geosciences 19 (5): 627–55. https://doi.org/10.1016/0098-3004(93)90099-Q90099-Q).

Rowlingson, Barry, and Peter Diggle. 2017. Splancs: Spatial and Space-Time Point Pattern Analysis.

Venables, W. N., and B. D. Ripley. 2002. Modern Applied Statistics with S. Fourth. New York: Springer.

Majure, James J., and Albrecht Gebhardt. 2016. Sgeostat: An Object-Oriented Framework for Geostatistical Modeling in S+.

Ripley, Brian D. 2001. “Spatial Statistics in R.” R News 1 (2): 14–15.

Akima, Hiroshi, and Albrecht Gebhardt. 2016. Akima: Interpolation of Irregularly and Regularly Spaced Data.

Jr, Paulo J. Ribeiro, and Peter J. Diggle. 2016. geoR: Analysis of Geostatistical Data.

Baddeley, Adrian, Ege Rubak, and Rolf Turner. 2015. Spatial Point Patterns: Methodology and Applications with R. CRC Press.

Bivand, Roger. 2001. “More on Spatial Data Analysis.” R News 1 (3): 13–17.

Bivand, Roger. 2017. Spdep: Spatial Dependence: Weighting Schemes, Statistics and Models.

Bivand, Roger, and Nicholas Lewin-Koh. 2017. Maptools: Tools for Reading and Handling Spatial Objects.

Bivand, Roger. 2003. “Approaches to Classes for Spatial Data in R.” In Proceedings of DSC, edited by Kurt Hornik, Friedrich Leisch, and Achim Zeileis.

Rowlingson, Barry, Adrian Baddeley, Rolf Turner, and Peter Diggle. 2003. “Rasp: A Package for Spatial Statistics.” In Proceedings of the 3rd International Workshop on Distributed Statistical Computing, edited by Kurt Hornik.

Pebesma, Edzer J, and Roger S Bivand. 2005. “Classes and Methods for Spatial Data in R.” R News 5 (2): 9–13.

Pebesma, Edzer, and Benedikt Graeler. 2018. Gstat: Spatial and Spatio-Temporal Geostatistical Modelling, Prediction and Simulation. https://CRAN.R-project.org/package=gstat.

Calenge, C. 2006. “The Package Adehabitat for the R Software: Tool for the Analysis of Space and Habitat Use by Animals.” Ecological Modelling 197: 1035.

Hijmans, Robert J. 2016. Geosphere: Spherical Trigonometry.

Bivand, Roger, and Colin Rundel. 2018. Rgeos: Interface to Geometry Engine - Open Source (’Geos’). https://CRAN.R-project.org/package=rgeos.

Hijmans, Robert J. 2017. Raster: Geographic Data Analysis and Modeling. https://CRAN.R-project.org/package=raster.

Bivand, Roger S. 2000. “Using the R Statistical Data Analysis Language on GRASS 5.0 GIS Database Files.” Computers & Geosciences 26 (9): 1043–52.

Bivand, Roger. 2016a. Rgrass7: Interface Between GRASS 7 Geographical Information System and R.

Bivand, Roger. 2016b. Spgrass6: Interface Between GRASS 6 and R.

Brenning, Alexander, Donovan Bangs, and Marc Becker. 2018. RSAGA: SAGA Geoprocessing and Terrain Analysis. https://CRAN.R-project.org/package=RSAGA.

Brenning, Alexander. 2012a. ArcGIS Geoprocessing in R via Python.

Muenchow, Jannes, Patrick Schratz, and Alexander Brenning. 2017. “RQGIS: Integrating R with QGIS for Statistical Geocomputing.” The R Journal 9 (2): 409–28.

Kahle, D, and Hadley Wickham. 2013. “Ggmap: Spatial Visualization with Ggplot2.” The R Journal 5: 144–61.

Lamigueiro, Oscar Perpinan. 2018. Displaying Time Series, Spatial, and Space-Time Data with R. Second. Boca Raton: Chapman and Hall/CRC.

• The conference took place at the University of Leeds, where one of the authors (Robin) is currently based.The 21st GeoComputation conference was also hosted at the University of Leeds, during which Robin and Jakub presented, led a workshop on ‘tidy’ spatial data analysis and collaborated on the book (see www.geocomputation.org for more on the conference series, and papers/presentations spanning two decades).↩

• A laptop with 4GB running a modern operating system such as Ubuntu 16.04 onward should also be able to reproduce the contents of this book.A laptop with this specification or above can be acquired second-hand for ~US$100 in many countries nowadays, reducing the financial/hardware barrier to geocomputation far below the levels in operation in the early 2000s, when high-performance computers were unaffordable for most people.↩

• Python modules providing access to geoalgorithms include grass.script for GRASS,saga-python for SAGA-GIS,processing for QGIS and arcpy for ArcGIS.↩

• An overview of R’s spatial ecosystem can be found in the CRAN Task View on the Analysis of Spatial Data(see https://cran.r-project.org/web/views/Spatial.html).↩