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SmartSkeMa: Scalable Documentation for Community and Customary Land Tenure

Author

Listed:
  • Malumbo C. Chipofya

    (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, 7514 AE Enschede, The Netherlands)

  • Sahib Jan

    (Institute for Geoinformatics, Westfälische Wilhelms-Universität Münster, Heisenbergstrasse 2, 48149 Münster, Germany)

  • Angela Schwering

    (Institute for Geoinformatics, Westfälische Wilhelms-Universität Münster, Heisenbergstrasse 2, 48149 Münster, Germany)

Abstract

According to the online database landmarkmap, up to an estimated 50% or more of the world’s habitable land is held by indigenous peoples and communities. While legal and procedural provisions are being made for bureaucratically managing the many different types of tenure relations in this domain, there continues to be a lack of tools and expertise needed to quickly and accurately document customary and indigenous land rights. Software and hardware tools that have been designed for documenting land tenure through communities continue to assume a parcel-based model of land as well as categories of land relations (RRR) largely dimensionally similar to statutory land rights categories. The SmartSkeMa approach to land tenure documentation combines sketching by hand with aerial imagery and an ontology-based model of local rules regulating land tenure relations to produce a system specifically designed to allow accurate documentation of land tenure from a local perspective. In addition, the SmartSkeMa adaptor which is an OWL-DL based set of rules for translating local land related concepts to the LADM concepts provides a more high-level view of the data collected (i.e., what does this concept relate to within the national LADM profile?) In this paper we present the core functionalities of SmartSkeMa using examples from Kenya and Ethiopia. Based on an expert survey and focus groups held in Kenya, we also analyze how the approach fairs on the Fit-for-Purpose Land Administration tools scale. The results indicate that the approach could be beneficial in scaling up mapping of community and customary lands as well as help reduce conflict through its participatory nature.

Suggested Citation

  • Malumbo C. Chipofya & Sahib Jan & Angela Schwering, 2021. "SmartSkeMa: Scalable Documentation for Community and Customary Land Tenure," Land, MDPI, vol. 10(7), pages 1-20, June.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:7:p:662-:d:579938
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    References listed on IDEAS

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    1. Mila Koeva & Mohammed Imaduddin Humayun & Christian Timm & Claudia Stöcker & Sophie Crommelinck & Malumbo Chipofya & Rohan Bennett & Jaap Zevenbergen, 2021. "Geospatial Tool and Geocloud Platform Innovations: A Fit-for-Purpose Land Administration Assessment," Land, MDPI, vol. 10(6), pages 1-23, May.
    2. Chipofya, Malumbo & Karamesouti, Mina & Schultz, Carl & Schwering, Angela, 2020. "Local Domain Models for Land Tenure Documentation and their Interpretation into the LADM," Land Use Policy, Elsevier, vol. 99(C).
    3. Rahmatizadeh, Shima & Rajabifard, Abbas & Kalantari, Mohsen & Ho, Serene, 2018. "A framework for selecting a fit-for-purpose data collection method in land administration," Land Use Policy, Elsevier, vol. 70(C), pages 162-171.
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    Cited by:

    1. Stig Enemark & Robin McLaren & Christiaan Lemmen, 2021. "Fit-for-Purpose Land Administration—Providing Secure Land Rights at Scale," Land, MDPI, vol. 10(9), pages 1-12, September.
    2. Ho, Serene & Choudhury, Pranab R. & Joshi, Richa, 2023. "Community participation for inclusive land administration: A case study of the Odisha urban slum formalization project," Land Use Policy, Elsevier, vol. 125(C).
    3. Simon Hull & Harold Liversage & Maria Paola Rizzo & Vladimir Evtimov, 2022. "An Overview of Frontier Technologies for Land Tenure: How to Avoid the Hype and Focus on What Matters," Land, MDPI, vol. 11(11), pages 1-15, October.
    4. Naghavi, Mohammad & Alesheikh, Ali A. & Hakimpour, Farshad & Vahidnia, Mohammad H. & Vafaeinejad, Alireza, 2022. "VGI-based spatial data infrastructure for land administration," Land Use Policy, Elsevier, vol. 114(C).

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