Zahl, Michael Stuart (2013) RTK GNSS in cadastral surveying. [USQ Project]
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Abstract
Real Time Kinematic Global Navigation Satellite System observations have become an increasing prevalent method of surveying in all forms of the surveying and spatial science industry. One area where the use of RTK raises particular concern is for cadastral surveying, where it has been realised by many parties that clarification is needed with regards to how RTK technology is to be used. These concerns stem from a lack of understanding about the capabilities and limitations of RTK and also how it should be used in regards to best practice recommendations. The aim of this dissertation is to substantiate the Surveyors Board of Queensland guideline regarding the use of RTK for cadastral surveys. This dissertation will aim to augment several key areas of the guideline; short line observation, referencing and minimum backsight lengths with empirically tested data that will determine how and when RTK is applicable for these applications and recommend the best practices to achieve these. The aims of the testing are to determine what is the minimum length of a short line RTK is capable of accurately observing, what is the minimum observable length of a backsight line to accurately orientate a survey and at what lengths can RTK be used to accurately observe reference marks. Testing of these elements will be conducted with regard to the survey standards’ accuracy referenced in the guideline and also compare the accuracy results to the capabilities of a total station (as the conventional method of cadastral surveying). Because the best practices for the observation of these three elements is yet unknown, various methods will be employed to ascertain which method yields the most accurate and precise results.
The results of the testing conducted found answers to meet the aims of this dissertation but it also served to identify the impact errors and inaccuracies can have on the observations. It was found that observation bias in the RTK measurements significantly affected the results of the observations and caused these to appear potentially far worse than the results may actually be. Moreover it was found that RTK is not an appropriate means of referencing; the errors in the distance led to errors in the bearing of the line that were too great to accept based on the 95% confidence interval. The minimum backsight length required for an RTK observation to meet TS bearing accuracy was identified as 180m which is slightly shorter than the recommendations of the SBQ. It was found though that in difficult circumstances where accuracy may allowably be reduced for the use of RTK, the minimum backsight length was determined to be 120m, which is slightly longer than the SBQ recommendations. Both of these minimum lengths were only found to be possible when using the most rigorous observation methods where anything less would not suit. Finally it was found that RTK observations of significantly shorter lengths than recommended by the survey standards’ (640m) and adopted by some jurisdictions (120m) could still achieve the survey standards’ accuracy; it was found that the length fell to just 40m. This was found to be observable when using only moderately rigorous methods and would be easily repeatable. Considering the effect observation bias had on the results, several recommendations were made regarding how best to minimise this impact, as well as the recommendation that a 99% confidence interval should be used when analysing the capability of RTK as the standard 95% confidence interval potentially allows for too great a degree of uncertainty. The conclusion of this dissertation found that the aims were met and the instances where RTK is applicable for short line and referencing observations and the minimum observable backsight length was established.
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| Item Type: | USQ Project |
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| Item Status: | Live Archive |
| Additional Information: | Bachelor of Spatial Science (BSpSc) Surveying project. |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | Gibbings, Peter |
| Date Deposited: | 24 Jun 2014 01:33 |
| Last Modified: | 19 Jul 2018 00:22 |
| Uncontrolled Keywords: | rtk gnss; cadastral surveying; spatial science |
| Fields of Research (2008): | 09 Engineering > 0909 Geomatic Engineering > 090906 Surveying (incl. Hydrographic Surveying) |
| Fields of Research (2020): | 40 ENGINEERING > 4013 Geomatic engineering > 401306 Surveying (incl. hydrographic surveying) |
| URI: | https://sear.unisq.edu.au/id/eprint/24707 |
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