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Message:

> Hello aleksandar95,
> 
> > How do sigma b and sigma c depend on the distance between points? 
> 
> I already posted a link to the [link=https://software.applied-geodesy.org/wiki/least-squares-adjustment/observation#nivellement]documentation[/link]. The equation reads
> 
> [tex]\sigma_{\delta h} = \sqrt{\sigma_a^2 + \sigma_b^2 d + (\sigma_c d)^2}[/tex]
> 
> where d is the distance. 
> 
> > For example, if the leveling distances are between 100 and 200 meters, what should be the value of sigma b?
> 
> The value you expect for this type of a-priori uncertainty.
> 
> > For instance, if the instrument’s accuracy is 1mm/km, then sigma b is 1. Is this correct?
> 
> It is a good starting value to define this component of the stochastic model, yes.
> 
> > I am most interested in the value of the sigma a parameter. What should its value be and what does it depend on? 
> 
> Like σb and σc, σa depends on the assumed uncertainty of your measurement procedure.
> 
> > Does sigma a represent an a priori standard deviation or not? 
> 
> Again, like σb and σc, σa is an a-priori uncertainty, too.
> 
> > If it refers to the uncertainty of a single measurement, does that mean it is the expected error value?
> 
> No. It is the assumed distance-independent part of the combined uncertainty of the measurement procedure. However, in case of σb=σc=0, σa defines the assumed a-priori uncertainty of a single observation δh, cf. the equation above.
> 
> Kind regards
> Micha

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