Learning Spatial Statistics?

Spatial statistics, like most statistical methods, is a large topic. If you would like spatial statistical theory presented in a statistical/mathematical framework my favorite is Cressie's book "Statistics for Spatial Data".

Since Diggle's point process book is out of print, A good alternative, specific to point pattern analysis, is "Statistical Analysis and Modelling of Spatial Point Patterns".

A great overview of spatial statistics in ecology is Fortin & Dale's "Spatial Analysis: A Guide for Ecologists.

For implementation of spatial Hierarchical Bayesian Modelling there is "Hierarchical Modeling and Analysis for Spatial Data".

I really like Gilks "Markov Chain Monte Carlo in Practice" for an introduction of Monte Carlo approaches.

For an introduction to geostatistics the standard is Isaaks & Srivastava's "An Introduction to Applied Geostatistics"

This is by no means a comprehensive list but are some of the books that I refer graduate students to.

You can start by checking the Geospatial Analysis - A comprehensive guide.

The entire book is online: http://www.spatialanalysisonline.com/

Since spatial statistics are very often implemented in R, my go-to book is Applied Spatial Data Analysis by Bivand et al. 2008. This book is great in describing how to tie together spatial data with spatial statistics. For example, how do you go from a collection of XY coordinates describing tree locations to determining whether or not they are clustered, random or uniformly distributed? There are many books that describe the intricacies of spatial statistics, yet few of those actually describe how to implement these statistics.