Christa's GIS Archive

The next Special Topic in GIS for Data Quality is Standards, particularly in regard to positional accuracy! Using two different road datasets in Albuquerque, New Mexico, we gained a better understanding of how to determine and verify the horizontal accuracy of these road networks, based on the National Standard for Spatial Data Accuracy (NSSDA). One of these road networks was from the city of Albuquerque, while the other is from TeleAtlas and ESRI. Orthophotos from 2006 were used to ground these roads to a true reference. Screenshot featuring the 20 Sampling Locations for the New Mexico Study Area. Out of the gate, as the lab prefaced, the city street data already looked visually more accurate to the ortho imagery than the Street Map USA data. As described by Bolstad and Manson (2022, p. 617), the NSSDA consists of 5 steps for calculating horizontal accuracy; here's how I applied them to each step. 1.) Identify test points, which 20 points were created at various road intersections...

With the dawn of the next season, I'm hoping life will be calmer this Fall semester and that I won't be juggling too much on top of classes. We began the Special Topics in GIS course in mid-August, jumping right in with the first lab of Module 1.1: Fundamentals. This first module's lab covered Spatial Data Quality in two parts: precision versus accuracy and how to calculate them, as well as root-mean-square error (RMSE) and the cumulative distribution function (CDF). Precision and accuracy are foundational concepts crucial for distinguishing and properly interpreting data. Refreshers like this one are always welcome in my book. Speaking of books, as described by Bolstad and Manson (2022, p. 612), precision is the degree to which values are uniform and tightly clustered around an average; accuracy, on the other hand, is how close the value(s) are to the true benchmark value. In the first part of the lab, Part A, we used data points near Tampa, Florida, consisting of 50 waypo...