Quality impact on geospatial data
Historically, high-fidelity geospatial data has been challenging to acquire and use. In theory, everyone would agree that the highest-quality data is ideal. In practice, data transfer bandwidth and other technical limitations often handicap initiatives from using the highest-quality geospatial data. An important mindset that should be adopted when using geospatial data in the cloud is that you do not need to sacrifice data quality to keep your projects within budget. Throughout this book, we will show ways in which you can have it all: massive amounts of high-quality geospatial data and a reasonable, controllable cost profile.
A common scenario where data quality can be tainted is a loss of precision in coordinate values. Whether done intentionally to save bytes or accidentally due to repeated transformation, latitude and longitude data tends to become less accurate the more it is used and shared. Using five decimal points of precision instead of...
