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Showing posts from August, 2023

Data Quality: Standards

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This week in GIS 5935 we continued our study of data quality in GIS with a focus on standards.  This included metrics for assessing positional accuracy via standards such as the National Map Accuracy Standards (NMAS) and the National Standards for Spatial Data Accuracy (NSSDA). Positional accuracy is one of the five components of data quality with the others being attribute accuracy, logical consistency, completeness, and lineage. For this module's lab assignment, I assessed positional (horizontal) accuracy for two different polyline layers of streets in a section of Albuquerque, New Mexico. This included a shapefile of road centerlines from the City of Albuquerque and another file of a sample of the same study area from StreetMap USA, a TeleAtlas product distributed by ESRI with ArcGIS. For the assignment, I created three different point shapefiles. Two were directly produced from a sample of 20 different intersections of streets in the previously mentioned polyline files.  The th

Data Quality: Fundamentals

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This week, I completed the first assignment in the Special Topics in GIS (GIS 5935) class.  Here we learned about calculating metrics for spatial data quality in GIS, specifically understanding the difference between assessments of precision and accuracy. According to Boldstad and Manson (2022:610), "accuracy is most reliably determined by a comparison of true values to the values represented in a spatial data set." Precision, in contrast refers to "the consistency of a measurement method" (2022:612). Unlike accuracy, precision does not use a reference value but instead assesses the variance of values in the data set. In the first part of the lab, horizontal accuracy was determined from 50 waypoints mapped with a Garmin GPSMAP 76 unit , which according to the manufacturer, this device is "accurate to within 15 meters (49 feet) 95% of the time" where "users will see accuracy within 5 to 10 meters (16 to 33 feet) under normal conditions." For the