GIS5935 Mod1: Fundamentals


 In this lab, we analyzed the accuracy and precision of GPS-collected waypoints using ArcGIS Pro and Excel. Part A focused on determining the horizontal and vertical precision of repeated GPS measurements by calculating the average location and measuring how closely the observed points clustered around it. By creating buffers representing 50%, 68%, and 95% of the observations, we could visually assess the spread of the points and quantify the GPS unit’s precision. We then compared the average location to a surveyed reference point to determine horizontal and vertical accuracy, revealing how close the measurements were to the true location and elevation. Horizontal accuracy measures how close the GPS observations are to the true location, while horizontal precision measures how closely repeated observations cluster together, regardless of the true location.

Part B extended the analysis to a larger dataset, where we calculated the root-mean-square error (RMSE), mean, median, and various percentiles of the horizontal error. A cumulative distribution function (CDF) was created to visualize the full distribution of errors, highlighting patterns and potential outliers that summary metrics alone could not show. This exercise demonstrated the importance of both numeric metrics and visual tools in understanding GPS data quality, showing how precision and accuracy work together to determine the reliability of spatial data.

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