Esta es mi lista de libros tipo bookdown para trabajar en ciencia de datos espaciales con R, enfocado en referencias para hacer analisis con estadistica espacial. Aqui no inclui referencias solo dedicadas a mapeo con R, imagenes satelitales o analisis de redes, ni viñetas de paquetes. El año corresponde al de la última actualización. This is my list of bookdowns, gitbooks or similar for working in spatial data science with R, particularly including spatial statistics. Lots of references focused on with just mapping, visualization, satellite imagery or network analisis are not included. The year corresponds to the last update.

1. Robin Lovelace, Jakub Nowosad, Jannes Muenchow. 2022. Geocomputation with R
2. Edzer Pebesma, Roger Bivand. 2022. Spatial Data Science with applications in R
3. Jose I Pareja, Yazid A Barhoush and Wendy P Tori. 2021. Applications and Spatial Analysis using R: Environmental and Conservation Science (Parece no estar accesible ahora)
4. Taro Mieno. 2020. R as GIS for Economists
5. Brunsdon C., Comber L. 2022. Code for An Introduction to Spatial Analysis and Mapping in R 2nd edition
6. Claudia A Engel. 2019. Using Spatial Data with R
7. Paula Moraga. 2019. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny
8. Michel Dorman. 2022. Introduction to Spatial Data Programming with R
9. Francisco Rowe and Dani Arribas-Bel. 2022. Spatial Modelling for Data Scientists
10. Tom Hengl and Robert A. MacMillan. 2019. Predictive Soil Mapping with R
11. Robert Hijman. 2021. Spatial Data Science with R
12. Michael C. Wimberly. 2022. Geospatial Data Science With R: Applications in Environmental Geography
13. Jerry Davis. 2022. Introduction to Environmental Data Science
14. Elias T. Krainski, Virgilio Gómez-Rubio, Haakon Bakka, Amanda Lenzi, Daniela Castro-Camilo, Daniel Simpson, Finn Lindgren and Håvard Rue. 2021. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
15. Duke University Libraries. 2021. R: Mapping and Geospatial. Geospatial applications using the R programming language
16. Chris J. Brown et al 2020. Data wrangling for spatial analysis: R Workshop
17. Manuel Gimond. 2022. Intro to GIS and Spatial Analysis
18. Mariano Córdoba, Pablo Paccioretti, Franca Giannini Kurina, Cecilia Bruno y Mónica Balzarini. 2019.Guía para el análisis de datos espaciales. Aplicaciones en agricultura
19. Nico Hahn. 2020. Making Maps with R
20. Rolf Simoes, Gilberto Camara, Felipe Souza, Lorena Santos, Pedro R. Andrade, Charlotte Peletier, Alexandre Carvalho, Karine Ferreira, Gilberto Queiroz y Victor Maus. 2021.sits: Data Analysis and Machine Learning on Earth Observation Data Cubes with Satellite Image Time Series
21. Marc Becker, Martin Binder, Bernd Bischl, Michel Lang, Florian Pfisterer, Nicholas G. Reich, Jakob Richter, Patrick Schratz, Raphael Sonabend. 2022, mlr3 book
22. Antonio Paez. 2022. An Introduction to Spatial Data Analysis and Statistics: A Course in R
23. Ken Steif. 2021. Public Policy Analytics: Code & Context for Data Science in Government
24. Ben Best. 2017. R Advanced Spatial Lessons
25. Reka Solymosi and Juanjo Medina. 2022. Crime Mapping in R
26. Adrian Baddeley, Ege Rubak and Rolf Turner. 2016. Website companion to Spatial Point Patterns: Methodology and Applications with R
27. Alec L. Robitaille, Juliana Baluffi-Fry, Quinn M.R. Webber, Julie W. Turner, Isabella C. Richmond, Christina M. Prokopenko, Katrien A. Kingdon. 2021. Wildlife Evolutionary Ecology Lab - WEEL Guide
28. Victor Morales-Oñate. 2022.Econometría Espacial - Notas de clase
29. Stefano De Sabatta. 2022. R for Geographic Data Science