Crowdsourcing the Cadastre: The Applicability of Crowdsourced Geospatial Information to the New Zealand Cadastre

Abstract

<p>Crowdsourcing has transformed how geographic information is collected, stored, disseminated, analysed, visualised and used (Sui et al., 2013b). Yet, crowdsourcing has had little impact on core government geospatial data. This ‘authoritative data’ is often tightly controlled with a focus on data quality and security for protection from unauthorised change (Rice et al., 2012). Opportunities for consumers, users and existing data producers to contribute their skills and information to enhance authoritative government geospatial data has been limited. The adoption, or use, of crowdsourcing by Government has been slow (Haklay et al., 2014). The New Zealand Cadastre, managed by Land Information New Zealand (LINZ) is an example of a core government geospatial system that has collated and managed data for over a century. Despite data meeting the contemporary acceptance standards when it was integrated into the cadastre, data quality is often questioned by users as inaccuracies or discrepancies are identified (Opus, 2013). Web 2.0 technologies and easy to use mobile devices enabled geospatial capability and a user skill base to an increased acceptance of crowdsourcing as a means to build and maintain geospatial datasets (Kostanski, 2012, McLaren, 2011, Rice et al., 2012). Accordingly, if cadastral data is to be maintained and enhanced to meet modern expectations for multiple use (LINZ, 2013a, Cadastre Ltd, 2003), one option is the use of crowdsourcing (Grant et al., 2014, LINZ, 2013a). This thesis examines the potential applicability of Volunteered Geographic Information (VGI) as a specific form of crowdsourcing within an authoritative database - the New Zealand Cadastre. Using a two phase quantitative and qualitative methodology, the perspectives of users, data providers and administrators are explored to ascertain the applicability of VGI to the New Zealand Cadastre. This thesis finds that crowdsourcing concepts could enable users to contribute data or information, re-conceptualise the role of the existing data providers (predominately licensed cadastral surveyors) and enable the reuse of cadastral related work. Cadastral VGI can provide advances in data collection and maintenance processes; if users, data producers and administrators change their perception of what crowdsourcing is, and what it can provide. However, the importance of user perception in the quality of the dataset will need to be strongly considered in any integration of VGI into the cadastre or other authoritative datasets.</p>

A Prototype Machine Learning Tool Aiming to Support 3D Crowdsourced Cadastral Surveying of Self-Made Cities

“…It is now accepted that a cadastral system may be comprised of various datasets of variable quality integrated together in a fit-for-purpose whole [43]. In recent years, data collection methods such as VGI and crowdsourcing techniques have claimed a place as a reliable cadastral data source, strengthening their role in the process for the initial implementation of 2D and 3D cadastre in both the developing and the developed world [25,36,37,40,41,[43][44][45][46][47][48][49][50]. To date, much research has been carried out trying to manage the 3D aspect of the physical objects and introduce crowdsourcing in 3D cadastral surveying procedures.…”