Positional accuracy improvement: lessons learned from regional Victoria, Australia

Cadastral Positioning Accuracy Improvement: A Case Study in Malaysia

“…Since the legacy dataset are less accurate in positioning, the integration between legacy datasets and higher updated accuracy like GNSS is one of the most possible methods to improve the legacy datasets accuracy (Hope et al, 2008). However, in her study, it is found that by simply replacing a sample of legacy dataset with more accurate version will lead to a distortion of the neighbouring geometry (Figure 2).…”

“…The drastic changing and development of satellite based technology in data observation such as Global Navigation Satellite System (GNSS) also make the great possibility of PAI process in transforming the legacy datasets. Furthermore, the availability of high resolution aerial imagery and the popularity of open source application such as Google Earth are leading to predominant usage of imagery as background underlays to spatial dataset (Hope et al, 2008). The imagery which has high quality spatial resolution and absolute accuracy like Quick Bird imagery can be used as a base map to check the discrepancies between the legacy datasets and the satellite imagery.…”

“…For instance, a straight linear feature that spans several triangles may experience considerable distortion because of the inconsistency of the transformation at the triangle vertices. Hence, these local methods, which distort the source dataset to fit the target dataset, might account for this issue when they are used to upgrade the spatial datasets in a global area, within which the geometric characteristics and spatial relationships should be essentially preserved (Hope et al, 2008;Hope, Kealy, & Hunter, 2006;Tong, Shi, & Liu, 2005).…”

“…In the study in PAI in Victoria Australia, an initial 4 parameters of Helmert Transformation is applied to the lower accuracy legacy dataset, so that it is will be aligned to the new coordinate system of survey data (Hope et al, 2008). Yaron A.…”

“…As a result, many countries around the world is modernizing the cadastral database from legacy cadastre or relative cadastre to accurate coordinate based cadastre known as Positional Accuracy Improvement (PAI) (Donnelly & Hannah, 2006;Yaron A. Felus, 2007;Fradkin & Doytsher, 2002;Hesse, Benwell, & Williamson, 1990;Hope, Gordini, & Kealy, 2008;Klebanov & Doytsher, 2009;Morgenstern, Prell, & Riemer, 1989;Tamin, 1995). PAI is classified as a process of improving the position of the geometry coordinates of a feature in a geospatial dataset to better reflect its actual position (Rönsdorf, 2008).…”