I attended a talk on recent developments in spatial statistics and while most of the talk was over my head, I did not some resources in the introduction that might be helpful for someone like me who is just learning about this approach.
The two books mentioned were
Sudipto Banerjee, Bradley P. Carlin, Alan E. Gelfand. Hierarchical Modeling and Analysis for Spatial Data, 2nd edition, Chapman and Hall/CRC. The pulisher’s website has a nice description.
Noel Cressie, Christopher K. Wikle. Statistics for Spatio-Temporal Data, Wiley. Again, there is a nice description on the publisher’s website.
Edzer Pebesma, Marius Appel, and Daniel Nüst have a nice blog, r-spatial, for those interested in learning how to do spatial analysis using R.
Lu Zhang. Nearest Neighbor Gaussian Processes (NNGP) based models in Stan (2018, Jan), is a nicely worked out example of spatial analysis using the Bayesian package, Stan.
https://www.amstat.org/asa/files/pdfs/POL-Statistics-as-a-Scientific-Discipline.pdf https://med.virginia.edu/phs/wp-content/uploads/sites/188/2021/05/TRAppS-Biostat-effort-benchmarks-Apr2021.pdf https://health.ucdavis.edu/ctsc/area/biostatistics/Documents/UCD_Biostat_Effort_Guidelines.pdf