Spatial Statistics: Applications

Course Description

Nowadays spatial statistics become an important branch of statistics that used to explore and analysis observed data. Techniques of spatial analysis are involved and applied in various fields such as geography, spatial epidemiology and etc.

This course aims to consider topics in spatial statistics and providing necessary background to investigate geographical data. The course will focus on geostatistical computing methods that highly related to spatial data analysis. As software application, R programming language will be involved to analysis spatial data. Hence part of the covered topics in the course will contain an introduction to various R packages for the analysis of spatial data. This will include data import/export, data management and visualization, and other necessary R tutorial that serve the course. Below the main subjects that will be covered by the course. Moreover, ArcGIS is also going to be used and focusing on the spatial analyst ToolBox. It worth to mentioned that each theoretical lesson will have two hours of practical lesson, and will involve 3 – 4 hours as a workload.

Lectures and Materials

#	Lect.	Labs
01	Introduction to Spatial Statistics Course	R-Code, R & RStudio Software, Introduction to R.
02	Introduction & Overview: What is Spatial Statistics;Spatial Statistical Computing	Preparing the computing environment, Using the R Environment for Statistical Computing
03	Exploring and visualizing spatial data	Supplement Lab: ggplot2 graphics
04	Modelling spatial structure from point samples -I	Visualizing spatial structure
05	Modelling spatial structure from point samples -II	Modelling spatial structure from point samples
06	Introduction to GIS	Fundamental of ArcGIS - I Data (Lab)
07	GIS Databases	Fundamental of ArcGIS - II Data
08	GIS Databases: Projections and Geo-Positioning	Projections and Geo-Positioning Data
09	GIS Databases: Map Symbology and Attribute Table	Map Symbology and Attribute Table Data
10	Satellite-based Positioning	Field Work Session: Example Application
11	Build a GIS	Learning how to build a GIS
12	Raster Operations, Spatial Analysis	Interpolation techniques within GIS
13	Construct & Manipulate DEMs using ArcGIS	Construct & Manipulate DEMs using ArcGIS
14	Exercise: Exe01_Instructions	Exe01: Creating a Map
15	Exercise: Exe02_Instructions, Idw_cadmium.pdf example	Exe02: Spatial Interpolation

References & Textbooks

The most useful textbooks on spatial data analysis with R and ArcGIS are:

Bivand, R., Pebesma, E. J., & Gómez-Rubio, V. (2008). Applied spatial data analysis with R. New York: Springer.
O. Schabenberger and C. A Gotway (2005). Statistical Methods for Spatial Data Analysis, Chapman & Hall.
Rossiter, D. G. (2012). Introduction to the R Project for Statistical Computing for use at ITC. International Institute for Geo-information Science & Earth Observation (ITC), Enschede (NL), 3, 3-6.
Venables, W. N., Smith, D. M., & R Development Core Team. (2004). An introduction to R.
Development Core Team at ITC. (2013). GI science and earth observation : a process - based approach : also as e-book. (2010). Enschede: University of Twente Faculty of Geo-Information and Earth Observation ITC.
de By, R. A., Knippers, R. A., Weir, M. J. C., Georgiadou, Y., Kraak, M. J., Westen, C. J. V., et al. (2004). Principles of Geographical Information Systems: An introductory textbook (3 rd ed. Vol. 1). Enschede: ITC.

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