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This module is about local measures of precision and accuracy of coordinates in spatial and geospatial networks. It covers the following:
- An intuitive review of precision vs. accuracy
- The notion of using variance-covariance functions to predict the precision of a network
- An introduction to correlation and it’s calculated (from data and from the variance-covariance matrix)
- Standard 1D, 2D, and 3D measures of precision (from the variance-covariance matrix)
- Measures of precision for often-used levels of confidence in 1D, 2D, and 3D (from the variance-covariance matrix)
- Calculating measures of accuracy
My own notes
I’m still assuming that you’re building your own “perfect set of notes” as you go through this material – to make sure you have a succinct reference to help you be efficient on a test or in your future work. So, I’m sharing my own notes here with you to help with that.
The self-assessment problems
My usual practice in a course like this is to share some problems with you so you can assess your understanding of the material. These are embedded after the lessons below.
So, dig into these problems either after you’ve finished looking at the material or as you go. Hustle to figure out the answers. Leave no stone unturned. Get help if you need it. Like the notes, I’m going to assume you’re building the “perfect set of reference problems” to help you be efficient in a test or to look back at in practice.
If you’re taking this course from me as part of a university class then these are a great way to study. I can’t ask exactly the same questions on a test, of course, but I do generally design the problems in a way that you can expect to do as well in the formal assessments as you can do on these self-assessment questions.
And there’s also a lab that integrates quite closely with this material – especially the parts on scaling to the required confidence level and on error ellipses. It’s called: Preanalysis and ‘brute force’ iterative design of a trilateration network. I recommend doing this as you go through this module.
Okay, now get started by clicking through the lessons below!
