Lesson 1: Spatial Weights and Applications

Overview

Computing spatial weight is an essential step toward measuring the strength of the spatial relationships between objects. In this lesson, the basic concept of spatial weight will be introduced. This is followed by a discussion of methods to compute spatial weights.

Content

• Tobler’s First law of Geography
• Principles of Spatial Autocorrelation
• Concepts of Spatial Proximity and Spatial Weights
  • Contiguity-Based Spatial Weights: Rook’s & Queen’s
  • Distance-Band Spatial Weights: fixed and adaptive
• Applications of Spatial Weights
  • Global measures of spatial autocorrelation
  • Correlogram

Hands-on Exercise

• Geospatial Data Wrangling with R
• Choropleth Mapping with R

Self-reading Before Meet-up

To read before class:

• Chapter 2. Codifying the neighbourhood structure of Handbook of Spatial Analysis: Theory and Application with R.

Alternatively

• Chapter 9: Modelling Areal Data of Applied Spatial Data Analysis with R (2nd Edition). This book is available in smu digital library. Until section 9.3.1.

References

• François Bavaud (2010) “Models for Spatial Weights: A Systematic Look” Geographical Analysis, Vol. 30, No.2, pp 153-171.

• Tony H. Grubesic and Andrea L. Rosso (2014) “The Use of Spatially Lagged Explanatory Variables for Modeling Neighborhood Amenities and Mobility in Older Adults”, Cityscape, Vol. 16, No. 2, pp. 205-214.

All About R

• spdep package
  • dnearneigh()
  • knearneigh()