Currently, 2D-based analogue building subdivision plans are used to represent the spatial extent of private, public and communal property ownership rights. These plans are recognized as posing a range of challenges in terms of communicating the spatial complexity of ownership spaces within multi-storey buildings. In response to these challenges, three-dimensional (3D) digital data environments are being investigated as a potential approach for managing complex, vertically stratified ownership arrangements. The argument presented in this article is that Building Information Modelling (BIM) can be adopted for 3D digital management of data related to complex ownership spaces. BIM provides a common and 3D digital data sharing space, underpinning a reliable basis for facilitating collaboration and decision-making over the lifecycle of buildings. However, ownership attributes and the spatial structure of ownership arrangements inside buildings are yet to be accommodated within the BIM data environment. In this article, we present a range of required data elements for managing complex ownership spaces, which have been elicited by investigating current practices pertaining to subdivision of ownership spaces within multi-storey buildings in Melbourne, Australia. An open data model in the BIM domain is extended with these data elements and a prototype model for a real multi-storey building is implemented to demonstrate the viability of the extended data model for 3D digital management and visualization of data related to complex ownership arrangements.

There exists a demand for effective land administration systems that can support the protection of unrecorded land rights, thereby assisting to reduce poverty and support national development—in alignment with target 1.4 of UN Sustainable Development Goals (SDGs). It is estimated that only 30% of the world’s population has documented land rights recorded within a formal land administration system. In response, we developed, adapted, applied, and tested innovative remote sensing methodologies to support land rights mapping, including (1) a unique ontological analysis approach using smart sketch maps (SmartSkeMa); (2) unmanned aerial vehicle application (UAV); and (3) automatic boundary extraction (ABE) techniques, based on the acquired UAV images. To assess the applicability of the remote sensing methodologies several aspects were studied: (1) user needs, (2) the proposed methodologies responses to those needs, and (3) examine broader governance implications related to scaling the suggested approaches. The case location of Kajiado, Kenya is selected. A combination of quantitative and qualitative results resulted from fieldwork and workshops, taking into account both social and technical aspects. The results show that SmartSkeMa was potentially a versatile and community-responsive land data acquisition tool requiring little expertise to be used, UAVs were identified as having a high potential for creating up-to-date base maps able to support the current land administration system, and automatic boundary extraction is an effective method to demarcate physical and visible boundaries compared to traditional methodologies and manual delineation for land tenure mapping activities.