Crowd-sourced cadastral geospatial information : defining a workflow from unmanned aerial system (UAS) data to 3D building volumes using opensource applications

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesThe surveying field has been impacted over many decades by new inventions and improvements in technology. This has ensured that the profession remains one of high precision with the employment of sophisticated technologies by Cadastral Experts. The use of Unmanned Aerial Systems (UAS) within surveying is not new. However, the standards, technologies, tools and licenses developed by the open source community of developers, have opened new possibilities of utilising UAS within surveying. UASs are being constantly improved to obtain high quality imagery, so efforts were made to find novel ways to add value to the data. This thesis defines a workflow aimed at deriving Cadastral Geospatial Information (Cadastral GI), as three-dimensional (3D) building volumes from the original inputted UAS imagery. To achieve this, an investigation was done to see how crowd-sourced UAS data can be uploaded to open online repositories, downloaded by Cadastral Experts, and then manipulated using open source applications. The Cadastral Experts had to utilise multiple applications and manipulate the data through many data formats, to obtain the (3D) building volumes as final results. Such a product can potentially improve the management of cadastral data by Cadastral Experts, City Managers and National Mapping Agencies. Additionally, an ideal suite of tools is presented, that can be used store, manipulate and share the 3D building volume data while facilitating the contribution of attribute data from the crowd