Ogilvie, Heath Stewart (2018) An Investigation Aimed at Improving Subsidence Monitoring by Combining LiDAR with Traditional Survey Methodologies. [USQ Project]
Abstract
This research paper investigates the degree of correlation between LiDAR results validated by minimal field surveying and traditional surveyed data over surface areas affected by mine subsidence. The objective is to determine whether it is possible to construct a model that can achieve an acceptable degree of accuracy, using primarily ALS results combined with minimal traditionally surveyed data. Optimising the cost, time and safety of subsidence surveying compared to using only traditional surveying methods.
Determining whether it is possible to create a model based predominantly on ALS data, validated by a small subset of traditionally obtained data, that would provide similar or better accuracy than traditional subsidence surveying methods, is the outcome that would set this research apart from similar previous studies.
While it is disappointing that no such definitive model was able to be determined as a result of a combination of: • The random output from ALS in circumstances where inputs and conditions were consistent, and; • The number of geological and geotechnical variations that can alter mine subsidence.
There were indications that the hypothesis may have validity by virtue of correlation between some datasets. However other data did not behave with the same consistency indicating that further work is necessary to achieve the ultimate desired outcome.
Studies were carried out on a limited area of three swamps all located above the same longwall, within the same catchment area and covered by similar vegetation. Monitoring was conducted pre and post longwall mining using ALS data, as well as traditional survey and GPS techniques. This research aimed to test whether the hypothesised methodology would give a similar or better degree of understanding of the impacts of mining on the surface above the longwall without having to devote the time and resources needed to survey in the field in the traditional manner. The accuracy of the results obtained by the hypothetical method, and the accuracies mining companies require and currently obtain from traditional surveying methods, did not align sufficiently in this research. This requires companies to undertake the same manual effort to predict ground movement over much wider areas with the necessary degree of precision.
If further research aimed at: • The use of a higher level point density scanner, creating a surface model and obtaining exact points rather than the closest point. • Graduating from a lightly to more densely foliated environments with less obstacles to light penetration as the model is developed, to remove this as a potential source of ‘noise’ and error. • Using drones to fly lower over more targeted areas more thoroughly rather than aircraft covering areas well in excess of that necessary much less densely.
If further research in these areas was to be undertaken, it is considered that the level of correlation between the hypothetical and traditional methodologies would almost certainly improve. Potentially to a point where the method proposed represented a valid and cost-effective alternative to mining companies in the measurement of surface subsidence in much less time than advances in ALS technology are likely to occur.
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| Item Type: | USQ Project |
|---|---|
| Item Status: | Live Archive |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | Campbell, Glenn |
| Qualification: | Bachelor of Spatial Science (Honours) (Surveying) |
| Date Deposited: | 30 Aug 2022 05:35 |
| Last Modified: | 29 Jun 2023 02:24 |
| Uncontrolled Keywords: | LiDAR results; traditional surveying methods |
| URI: | https://sear.unisq.edu.au/id/eprint/40698 |
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