Module 1.1: Calculating Metrics for Spatial Data Quality

 Module 1.1: Calculating Metrics for Spatial Data Quality

In this weeks lab we looked at data that was collected by GPS coordinates to see the precision and accuracy of that data. This is important to know because when using data you need to make sure you are paying attention to what is being given to you and not just accepting it. It is important to note that when looking at the data one needs to aggregate data for both precision and accuracy. 

In the first portion of this module we took the data points and made an average data point. This is necessary because it helps show where the data should be compared to the rest of the area. Then we needed to project the waypoints and the average waypoint to the correct projecting so the data could be used in feet or meters better than decimal degrees. Having a lot of data it is important to do the Batch geoprocessing tool. This makes sure to get all your data in the correct projection without doing it one at a time. Also, you can do multiple feature classes to make sure all the data is projected correctly. Next we need to use the Spatial Join tool to help with the distance that falls within the different percentages (50th, 68th, and 95th). This makes sure your data is correct without having to guess the different buffer zones and is much more accurate than a visual inspection. The map below is a visual representation of the horizontal accuracy and precision of the waypoints that were given from the GPS unit.

After getting all the data to make the map the next step was getting the horizontal accuracy. There was a reference point that was put in the data to help measure the distance between the average location of the waypoints and the reference point. Then we measured the distance in meters to see how far apart they were from each other to see the accuracy of the point. The following numbers were the numerical results of the horizontal accuracy and precision. The horizontal accuracy is low accuracy because everything is slightly offset from the reference point. This compares to the horizontal precision which is high because it is only 1.6 meters off from the reference point. Lastly, the way that horizontal accuracy is measured by using the average point and comparing it to the reference point that was taken in the field. On the other hand, the way the horizontal precision is measured by looking for the standard deviation of the points such as the different percentiles that were shown in the map above.