When you talk about localization, are you talking about shifting from grid to ground or are you shifting to an even more accurate "local system"? Speaking of grid to ground, how is that done with the LS?
Localization solves the best fit rotation, translation and scale from one coordinate system to another. It's useful for determining the geodetic relationship of a coordinate system when the geodetic relationship of a survey is unknown. For instance, a total station survey that was made under an assumed bearing relation (record call) and assumed coordinate basis (5000,5000). You can survey a few points from the 5000,5000 survey with the LS and use localization to determine how that 5000,5000 system connects to planet Earth. There are several moving parts to a localization and it isn't something I would recommend to a new user. Unfortunately, the allure of 5000,5000 is like a siren to many surveyors who may be intimidated by projections (like State Plane).
Regarding Grid to Ground, there are many opinions on how to resolve this issue. For most surveyors, we can't consider grid inverses equivalent to ground distances. The scale distortion is too great. The most common remedies are to
- scale measured distances from a total station (or record call) to grid
- scale the grid system to an estimated ground system (modified State Plane)
- create new coordinate system that has lower scale distortion - so called LDP
Each has its merits. The first (scaling distances to Grid) is the proper technical way to work in State Plane. The coordinates developed from this are true State Plane, much simpler to provide metadata. The downside is that a simple inverse of grid coordinates reflects a measurement along an imaginary surface rather than at the surface of the Earth. The difference between the grid and the ground is reflected in the Combined Factor. This leaves surveyors with some decisions when it comes time to draw up the plat of the property. Do you simply annotate the distance as the grid distance or do you scale the grid annotations to surface?
The scaled system removes the need for scaling individual measurements by scaling the entire system one time. The advantage is that inverses are near ground surface measurements. The downside is that it isn't really State Plane Coordinates anymore. If you scale from 0,0, then the coordinates can be a few hundred feet from truth. If you scale from some point on the project site, the coordinates are much closer to State Plane, but you now have more details to include in the metadata.
The LDP is my personal favorite. Users create a coordinate system similar to State Plane but create it such that the projection surface is near to the Earth surface, thus grid inverses are near Earth surface. In many places this can be done for county wide or larger areas. Bearings are much closer to true North, typically, as the distance to the central meridian is typically shorter for LDP users than for SPC users. The downside is that additional metadata must accompany the coordinates.
Nate's method is a modification of the second option. He's scaling the SPC and then subtracting a value from the SPC to give the coordinates a different appearance. His bearings are State Plane Grid, but his coordinates are arbitrary. This is helpful because a user looking at his modified coordinates will not suppose them to be true State Plane.
