No abstract

Despite the significant and explicit focus on the United Nations Sustainable Development Goals (SDGs), much of the world's land rights remain unrecorded and outside formal government systems. Blame is often placed on land administration processes that are considered slow, expensive, and expertise-dependent. Fit-For-Purpose Land Administration (FFPLA) has been suggested as an alternative, time and cost-effective approach. Likewise, the UN endorsed Framework for Effective Land Administration (FELA) demands attention to worldwide tenure insecurity by directly linking it to responsible land administration. Implementation of FFPLA and FELA is country-context dependent, and there are now many lessons of execution from various jurisdictions. Undertaken in 2022, this study synthesizes a review of experiences to provide a further update on the best global FFPLA implementation practices and inform approaches for future FFPLA projects. A systematic review is adopted as the research methodology, and contemporary articles from the internationally recognized land administration discourse are examined. The studies focus on FFPLA implementation practices and innovative approaches for delivering land tenure security. A checklist is developed, based on the FELA strategic pathways and the FFPLA fundamental framework principles and characteristic elements, to identify best implementation practices. Success stories across the globe show that the FFPLA characteristic elements and the FELA pathway goals are achieved through effective execution of the FFPLA framework key principles. As a result, the study identified successful FFPLA implementation practices in Asia and Africa, which can be synthesized and extended to realize tenure security in rapidly urbanizing areas. However, further study is necessary to determine the efficacy, practicability, innovativeness, and transferability of the best practices to other land administration scenarios.

Fit-for-purpose land administration (FFPLA) seeks to simplify cadastral mapping via lowering the costs and time associated with conventional surveying methods. The approach can be applied to both initial establishment and on-going maintenance of system. In Ethiopia, cadastral maintenance remains an on-going challenge, especially in rapidly urbanizing peri-urban areas, where farmers' land rights and tenure security are often jeopardized. Automatic Feature Extraction (AFE) is an emerging FFPLA approach, proposed as an alternative for mapping and updating cadastral boundaries. This study explores the role of the AFE approach for updating cadastral boundaries in the vibrant peri-urban areas of Addis Ababa. Open-source software solutions are utilized to assess the (semi-) automatic extraction of cadastral boundaries from orthophotos (segmentation), designation of 'boundary' and 'non-boundary' outlines (classification), and delimitation of cadastral boundaries (interactive delineation). Both qualitative and quantitative assessments of the achieved results (validation) are undertaken. A high-resolution orthophoto of the study area and a reference cadastral boundary shape file are used, respectively, for extracting the parcel boundaries and validating the interactive delineation results. Qualitative (visual) assessment verified the completed extraction of newly constructed cadastral boundaries in the study area, although non-boundary outlines such as footpaths and artefacts are also retrieved. For the buffer overlay analysis, the interactively delineated boundary lines and the reference cadastre were buffered within the spatial accuracy limits for urban and rural cadasters. As a result, the quantitative assessment delivered 52% correctness and 32% completeness for a buffer width of 0.4m and 0.6m, respectively, for the interactively delineated and reference boundaries. The study further demonstrated the potentially significant role AFE could assist in delivering fast, affordable, and reliable cadastral mapping. Further investigation, based on user input and expertise evaluation, could help to improve the approach and apply it to a real-world setting.