Accuracy Issues for Spatial Update of Digital Cadastral Maps
Bibliographic Data
| ID | 22034679 |
|---|---|
| Authors | David Pullar (0000-0002-8334-8701, The University of Queensland, corresponding author), Stephen Donaldson (Geolocarta, Brisbane City, QLD 4000, Australia), Stephen H Donaldson (0000-0001-7091-0075) |
| Year | 2022 |
| Volume | 11 |
| Issue | 4 |
| Pages | 221 |
| Publication date | 2022-03-24 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi11040221 |
| OpenAlex | W4220911564 |
| Language | EN |
| Citations received | 3 |
| References cited | 19 |
All geospatial data are updated periodically. Cadastral parcel mapping, however, has special update requirements that set it apart from other geospatial data. Mapped boundaries change continuously to fit with new survey plans. Additionally, new parcels have to be fitted and aligned with adjoining parcels to merge them into existing cadastral mapping. This is preferably performed by a spatial adjustment approach to systematically improve its accuracy over time. This paper adapts methods for analysis and adjustment of survey networks to improve the accuracy of cadastral mapping with better coordinate positioning and survey plan dimensions. Case studies for both hypothetical and real cadastral mapping are used to illustrate the issues and spatially resolve errors. Adjustment results achieve an accuracy consistent with other GIS layers and boundary features visible in high-resolution orthoimagery. Graphical charts based on stress–strain relationships provide a simplified means to interpret post-adjustment results to identify and fix potential errors
Cadastre · Cartography · Data mining · Geography · Geoinformatics · Geospatial analysis · Information retrieval · Orthophoto · Remote sensing · 3D Modeling in Geospatial Applications · Computer Science · Geographic Information Systems Studies · Remote Sensing and LiDAR Applications · Artificial Intelligence
| Citations per year | 1 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |