This page contains references that may interest you if you wish to explore an issue further. None of these is required.

Why prime meridian moved (article in Sci News)

Overview of R packages for spatial analysis (the "R spatial ecosystem"). From Lovelace et al. 2019.

Books on spatial data analysis:
Schabenberger and Gotway, 2005. Statistical Methods for Spatial Data Analysis. has all the details and many derivations of results presented in class. I'll refer to that as S&G in these notes
Webster, R. and Oliver, M.A. 2007. Geostatistics for Environmental Scientists, 2nd 3d. Wiley. This is where I go for advice on practical issues in geostatistics. The authors focus on soil properties. Also the best source of information about sampling to estimate the variogram.
LeSage, J. and Pace, R.K. 2009. Introduction to Spatial Econometrics. CRC Press. Overview of autoregressive approaches to spatial regression and ANOVA (SAR models).
Diggle, P.J. 2014. Statistical Analysis of Spatial and Spatio-Temporal Point Patterns. 3rd ed., CRC Press. The best single volume on spatial point pattern analysis. Sometimes very succinct.
Oliver, M.A. and Webster, R. 2015. Basic Steps in Geostatistics: The Variogram and Kriging. Springer. Concise summary of the basics with a lot of practical advice. Examples are primarily soil sampling. Updates Webster and Oliver 2007.
Brundson, C. and Comber, L. 2015. An Introduction to R for Spatial Analysis and Mapping. Sage Publications. Quick intro to many topics with R code. Emphasis on using R as a GIS.
Baddeley, A., Rubak, E., and Turner, R. 2016. Spatial Point Patterns: Methodology and Applications with R. CRC/Chapman and Hall. A more detailed exposition than Diggle, with lots of R code.
Lovelace, R., Nowosad, J., and Muenchow, J. 2019. Geocomputation with R. CRC/Chapman and Hall. Emphasizes the sf package.