Aims

The module aims to develop the essential mathematical skills for understanding and undertaking observation processing and analysis. Students will be provided with an in-depth understanding of the reasons for inaccuracy in survey measurements and shown how to achieve and guarantee survey results adequate for their purpose by processes of pre-analysis, estimation and post-analysis. Knowledge of the basic concepts will be related to the computation of 1D, 2D and 3D survey control schemes but the universality of methods for the handling of measurement data will be emphasised with several case studies.

Outline Of Syllabus

Maths for observation processing (linearisation using Taylor series, partial differentiation, matrix algebra); measurement errors and their propagation; least squares using observation equations; network analysis; covariance analysis; pre- and post-adjustment analysis.

Teaching Rationale And Relationship

Early lectures introduce essential mathematical concepts for the statistical analysis of measurement data. Later lectures discuss least squares estimation and post-analysis. The theoretical concepts presented in lectures are demonstrated through case studies. Practical sessions allow students to apply the underlying theory with the aid of both a spreadsheet application and a specialised software package. Extensive time is allocated to independent study, which includes background reading.
Alternatives will be offered to students unable to be present-in-person due to the prevailing C-19 circumstances.
Student’s should consult their individual timetable for up-to-date delivery information.

Assessment Rationale And Relationship

Assessment exercises assesses students' computational accuracy and presentation of detailed computations.