Sunday, August 28, 2016

Special Topics Lab 1

This week's lab covers the precision and accuracy.  The first part looked at the precision and accuracy of a GPS unit.  A point was observed and mapped 50 times using the GPS devise.  To determine how accurate or precise the observations were, the average X and Y coordinates were found and a point added.  I performed a buffer around the average point for 1, 2, and 5 meters.

I did a spatial join with the average point and the 50 observation points to find the distance of each point to the average point.  I then found the distance for 50%, 68%, and 95% of the points.  I also then determined the average elevation and found the absolute difference of the average point to the observed points.  Below are the results, along with a map showing the average point and the observed points.

The reference point of the actual location was added to the map.  To see how accurate the average point was, I measured the distance from the reference point to the average point.  I did the same for elevation as well.  This was done to determine how accurate the average point is.  The average point was within 3 meters of the reference point and the elevation was within 6 meters.

The reference point and the average point differ by quite a bit.  The longitude and latitude is off by 3.8 meters from the reference point to the average.  The horizontal precision was 4.4 so it was greater than the true difference.  The elevation is off by 6 meters while the precision showed 3 meters.  Even though 4 meters is not a lot, depending on the need of knowing this location, it can be huge.  GPS units can only be so accurate and the unit puts the point fairly close to the true position.

The horizontal accuracy was 3.8 meters.  This is better than the horizontal precision.  The vertical accuracy is 6 meters which is worse than the vertical precision of 3 meters.  There was no evidence of bias in the results.

The second part of the lab covered calculating the Root Mean Square Error, mean, median, the percentiles, min and max values.  I then used the XY errors to plot a CDF chart.  I compared the chart to the metrics I calculated.  From looking at the chart, it is clear to see certain metrics like the percentiles or the min and maximum number.

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