Least squares for land surveyors is a statistical method that provides the most probable set of coordinates by minimizing the sum of the squares of the residuals (adjustments) between the measured values and the adjusted values. It's a powerful tool for network adjustment because it accounts for the quality of individual observations, identifies blunders, and provides confidence intervals for the final results. By applying this rigorous approach, surveyors can achieve a more accurate and reliable final survey network compared to traditional methods.

Least squares adjustment is not a new development. It is commonly used when adjusting GNSS rapid static networks. However, adjusting combined GNSS rapid static and terrestrial data can appear complex and difficult to understand the varying methodology. Surveyors may be reluctant to utilize this tool on data that includes GNSS rapid static, total station measurements, and level measurements.

Least squares methodology will be briefly covered. However, this course will focus on practical and real-world comparisons of varying adjustment methodology. Traditional adjustment methods such as the compass rule will be applied to total station measurements and line adjustment by distance will be applied to level measurements. These results will be compared to least squares adjustment methods on the same data. Additionally, GNSS rapid static and terrestrial data will be combined and adjusted by various methodologies and final coordinates will be compared. Some of these methods will include utilizing 3D, 2D, and 1D data at various milestones when adjusting the data. Several datasets will be used to provide empirical results for better understanding the of least squares adjustments.