Difference between revisions of "Lesson04"
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Latest revision as of 08:08, 4 February 2019
IS415 GeoSpatial Analytics and Applications
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Spatial Autocorrelation and Spatial Weights
Content
- Tobler’s First law of Geography
- Principles of spatial autocorrelation
- Concepts of Spatial Proximity and Spatial Weights
- Measures of Spatial Autocorrelation
- Join count, Moran’s I, Geary’s c
- Moran scatter plot
- Spatial correlogram
- Nonparametric spatial correlogram
Must do
- View
- Lecture on “Spatial Autocorrelation” by Luc Anselin (link to 1hr and 20mins video).
- Read
- O’Sullivan, D., and Unwin, D. (2010) Geographic Information Analysis, Second Edition. John Wiley & Sons Inc., New Jersey, Canada. Chapter 5-6. This is an e-book.
- Bivand, R.S., Pebesma, E. & Gómez-Rubio, V. (2013) Applied Spatial Data Analysis with R, 2nd Edition. Springer, New York. Chapter 9: Modeling Areal Data, pp. 263-284. This is an e-book.
- Complete Hands-on Exercise 4. The handout and data sets are available at course eLearn.
References
Methods
Getis, A., (2010) “B.3 Spatial Autocorrelation” in Fischer, M.M., and Getis, A. 2010 Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications, Springer. This is an e-book.
Anselin, L. (1996) "The Moran Scatterplot as an ESDA Tool to Assess Local Instability in Spatial Association" in Fischer, M., Scholten, H. and Unwin, D., Eds., Spatial Analytical Perspectives on GIS, Taylor and Francis, London, 111-125.
Applications
Celebioglu, F., and Dall’erba, S. (2010) “Spatial disparities across the regions of Turkey: An exploratory spatial data analysis”. The Annals of Regional Science, 45:379–400.
