G.Hudson Mastering GIS

 During this week's module we were introduced to and learned about interpolation. While we were made aware that there are many interpolation techniques available, we went more in depth when learning about Thiessen, Inverse Distance Weighted and Spline techniques. We were then tasked with performing these techniques.  We were required to use a dataset of water quality samples from the Tampa Bay area to show where there were concentrations of the Biochemical Oxygen Demand (BOD). The Thiessen interpolation method was used first and produced a raster on polygons. This was not deemed suitable based on the abrupt changes that take place at the edge of polygons versus the fluid and continuous nature of water. The IDW and Spline methods (regularized and tension) both produced a continuous surface which was more suitable. Additionally the spline method proved to be helpful because it made an anomalous area noticeable. Ultimately, however, I decided that the IDW was most suitable from m...

Continuing on from the first week of GIS5935, this week we were introduced to the more common data quality standards used for cartographic and digital geospatial data. These standards were put in place by organizations, such as the United States Geological Survey (USGS) and the Federal Geographic Data Committee (FGDC), to "provide a common language for reporting accuracy to facilitate the identification of spatial data for geographic applications" (FGDC, 1998). In particular, the lab allowed us to perform our own positional accuracy tests using the National Standard for Spatial Data Accuracy (NSSDA) standards.  The NSSDA standard follows a seven step process which includes the following:      1. Determining if the test should be for horizontal accuracy, vertical accuracy or both.      2. Selecting test points from the data set being evaluated      3. Selecting an independent data set of higher accuracy that corresponds to the data s...

 The first module of GIS 59395 - Special Topics in GIS taught students how to calculate metrics, such as accuracy and precision, as it relates to spatial data quality. We were tasked with calculating the precision and accuracy of waypoints collected using a GPS device. The following image is a map I produced displaying the waypoints and some off my results.  As included in the map, the horizontal precision based on the 68th percentile is 4.6m and the vertical precision based on the 68th percentile is 5.88m. The horizontal accuracy is 3.3 meters, while the vertical accuracy is 5.96m.  For the purpose of this blog I will focus more on the horizontal accuracy and precision. Horizontal precision takes into consideration the distance between the waypoints and the average waypoint, which was determined based on the waypoints. Once the distances are determined, we can determine how many waypoints fall within each percentile. Horizontal accuracy takes into consideration the dista...