Introduction to spatial statistics
This in-depth topic is presented by Dr. Phuong N. Truong, from the Faculty ITC, University of Twente. We acknowledge the inspiring contributions of Dr. Nicholas Hamm who was the previous lecturer of this in-depth topic.
Spatial statistics is statistical analysis applied to spatial data. Spatial data have an attribute and a location. This attribute could be an environmental variable like rainfall or air pollution concentration. It could also be disease incidence, prevalence or rate.
In Geohealth, we are concerned with both because environmental epidemiology studies the link between health outcomes and the environment (Hamm et al., 2015).
Spatial statistics and its application to Geohealth is a big subject and we can only introduce some core ideas here. You will learn three key concepts:
- Spatial dependence.
- Using the variogram to explore and model spatial dependence.
- Using the variogram for interpolation and mapping.
These concepts are addressed in the next step and in two further articles (one on spatial dependence and one on the variogram) that you will find next. We will use examples from environment and health.
References: Hamm, N. A. S., R. J. Soares Magalhães and A. C. A. Clements (2015). Earth Observation, Spatial Data Quality and Neglected Tropical Disesases. PLoS Neglected Tropical Diseases 9(12): e0004164. DOI: 10.1371/journal.pntd.0004164.
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