A traverse is adjusted, or balanced, to distribute remaining random errors back into the measurements. There are a number of ways to accomplish this differing in how the errors are modeled and computation complexity. The Comapss Rule demonstrated here works well for simple traverses having minimal redunant measurements. As traverses become more complex with additional measurements added, particularly with mixed quality, a least sqaures adjustment is the best to employ.
The examples used in this chapter are all closed loop traverses. A later chapter will show how to perform traverse computations, including adjustments, on closed link traverses.
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