G.Hudson Mastering GIS

Like the second assignment, this module continues to focus on data quality. More specifically, this week focused on data quality of road networks. As such, we were tasked with performing a comparative assessment to determine the completeness of a street centerline shapefile and a Topologically Integrated Geographic Encoding and Referencing (TIGER) road shapefile for Jackson County, Oregon.  To perform this assessment we utilized a non standard method, based on that used by M. Haklay in the "Comparative Study of OpenStreetMap and Ordinance Survey datasets" in 2010. This included using a grid, which encompasses the study area, to clip the road network into smaller sections. These smaller sections give more detailed insight into areas which may be considered complete or incomplete. Once the roads were clipped to each grid cell/section the lengths were calculated and then compared.  My analysis determined that 134 of the grid cells/sections contained parts of the street cente...

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...