Spatial Sampling, Uncertainty, & Ethics
This module will discuss techniques for spatial sampling and interpolation, followed by a broad discussion on types of uncertainty in GIS, both quantifiable errors and other issues that can be harder to explicitly define. Then we will close out the term with a discussion of ethical practices in GIS.
Learning Outcomes
- Gain Experience with Raster Overlay Methods
- More Practice with Model Builder
Spatial Sampling and Interpolation
Collecting spatial data, reading between the lines, and filling in the blanks.
Uncertainty in GIS
What are the components of uncertainty in GIS and how does it compound as you work through an analysis?
Ethic in GIS
Moral principals guiding your practice of GIS.
Working Examples
Sampling and Interpolation
This Example Project chow we can create random points in Arc and use them collect samples. It also shows how we can run inverse distance weighting and highlights the influence of sample size and sampling method.
Data Resolution
This Example Project shows how we can create lines and polygons from points in Arc and illustrates the concept of vector resolution. It also shows how we can create rasters from vector features (points, lines, or polygons), illustrates the concept of raster resolution, and shows how errors can cascade when converting between data models.
The Atomistic Fallacy
This Example Project helps to explain the atomistic fallacy.