Degree: Ph.D or M.Sc (by research)

Key-words: Laser scanning, deformation monitoring, calibration

Entry: BSc(Hons), preferably 1st class, or MSc, in Engineering, Mathematics, Photogrammetry, Geodesy or Physics.

Supervisor(s): Dr Derek Lichti and Dr Mike Stewart

Project Funding: Curtin University of Technology

Student Funding: Student required to win ASA, IPRS or other scholarship

Resources: Department-owned ground-based laser scanner, scanner software

Starting Date: Unrestricted

Existing techniques (e.g., surveying, GPS) used to monitor large structures such as buildings, dams and bridges, while very accurate, are greatly hindered by their low point density. Data acquisition time limits monitoring to only a few samples located at strategic points on the structure. Ground-based laser scanning is a new technology that allows rapid, remote measurement of millions of points, thus providing an unprecedented amount of spatial information. This in turn permits more accurate prediction of the forces acting on a structure. As an emerging technology though, several issues concerning instrument calibration, sensitivity analysis, data processing and data filtering techniques require investigation.

The proposed project will involve research into one or more of the following:

1. The accuracy of structural monitoring with laser scanning is critically dependent upon rigorous instrument calibration. Systematic effects such as electrical centre offset and scale errors must be properly modeled so as not to bias monitoring results. Resolution, precision and accuracy of both point measurements and modeled surfaces must also be rigorously quantified to gain a sound understanding of scanner sensitivity. Preliminary research (Lichti et al., 2000) has shown that existing methods of calibrating geodetic and photogrammetric instrumentation cannot be directly applied to scanners, thus necessitating development of new calibration and procedures and models.

 

2. Laser scanners offer a wealth of information about a structure’s surface in the form of a dense set of three-dimensional point measurements coupled with the return pulse strength. Invariably, scenes are partly occluded by objects not related to the structure, such as trees and vehicles, which must be removed from the scanner imagery. This project will focus on the development of automated filtering and classification algorithms that exploit both the range and return signal intensity data to remove unwanted features from scanner imagery.

 

3. Laser scanners acquire measurements in a uniform sampling pattern. This operation is different to that of surveying instruments, which are considered pointable and thus allow measurement of the same point at different epochs in time. Since scanners are non-pointable, the same point can not be re-measured and therefore compared from one epoch to the next for possible deformation. To circumvent the problem, scanner data can be reduced to a surface representation (e.g., a finite element mesh), the nodes of which constitute the "virtual" points compared for deformation. This aspect of the project will be an investigation into different surface modeling methods, determination of optimal node spacing and error and sensitivity analysis for deformation monitoring.

Baltsavias, E P (1999a). A comparison between photogrammetry and laser scanning, ISPRS Journal of Photogrammetry and Remote Sensing, 54 (2-3): 83-94.

Baltsavias, E P (1999b). Airborne laser scanning: basic relations and formulas. ISPRS Journal of Photogrammetry and Remote Sensing, 54 (2-3): 199-214.

Lichti, D D, M P Stewart, M Tsakiri, A Snow (2000). Benchmark tests on a three-dimensional laser scanning system. Geomatics Research Australasia, no. 72 (June 2000). (download in pdf format)

Wehr, A. and U. Lohr, 1999. Airborne laser scanning – an introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54 (2-3): 68-82.