Difference between revisions of "Lesson04"

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<font size="6">'''Spatial Autocorrelation and Spatial Weights'''</font>
  
 
=Content=
 
=Content=
* What is geospatial analytics?
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* Tobler’s First law of Geography
* Motivation of promoting geospatial analytics
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* Principles of spatial autocorrelation
* Case study
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* Concepts of Spatial Proximity and Spatial Weights
* An overview of Geographic Information Systems (GIS)
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* Measures of Spatial Autocorrelation
* GIS versus Geospatial Analytics
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** Join count, Moran’s I, Geary’s c
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** Moran scatter plot
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** Spatial correlogram
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** Nonparametric spatial correlogram
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=Must do=
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* View
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** Lecture on “[https://www.youtube.com/watch?v=Z8DvG-Wd00Y Spatial Autocorrelation]” by Luc Anselin (link to 1hr and 20mins video).
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* Read
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** 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.
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** 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. 
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*Complete Hands-on Exercise 4. The handout and data sets are available at course eLearn.
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=References=
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=Methods=
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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.
  
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Anselin, L. (1996) "[https://dces.wisc.edu/wp-content/uploads/sites/128/2013/08/W4_Anselin1996.pdf 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.
  
=Lesson competencies=
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==Applications==
  
=Technical References=
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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.
  
  
=Application References=
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=Lesson competencies=

Latest revision as of 08:08, 4 February 2019

Claraview.png IS415 GeoSpatial Analytics and Applications

About

Weekly Session

Take-home Exercises

Geospatial Analytics Project

Course Resources

 


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

  • 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.


Lesson competencies