Innovative Geospatial Solutions for Land Tenure Mapping

Koeva, Mila; Stöcker, Claudia; Crommelinck, Sophie; Chipofya, Malumbo; Kundert, Kaspar; Schwering, Angela; Jan, Sahib; Zein, T.; Timm, Christian; Humayun, Mohammed Imaduddin; Crompvoets, Joep; Tan, Evrim; Casiano, Cesar; Nkerabigwi, Placide

doi:10.4314/rjeste.v3i1.3s

Cited by 7 publications

(8 citation statements)

References 13 publications

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“…Spatial information is extracted via the object detection techniques. An example of the workflow and its implementation can be found in [15,16].…”

Section: Smartskemamentioning

confidence: 99%

“…Numerous examples on the application of the tool have been shared for Kenya and Rwanda in [28][29][30]. A detailed explanation of the sequence of the work, with the individual tools integrated into the platform, for a case study in Ethiopia, is explained in [15].…”

Section: Boundary Delineatormentioning

confidence: 99%

“…In response to the need for innovative solutions based on FFP principles, the "its4land" H2020 project was initiated [15,16]. The project aimed to develop technologies that consider the needs and readiness of the users that are implementable and scalable.…”

mentioning

confidence: 99%

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Geospatial Tool and Geocloud Platform Innovations: A Fit-for-Purpose Land Administration Assessment

Koeva

Humayun²,

Timm³

et al. 2021

Land

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The well-recognized and extensive task of mapping unrecorded land rights across sub-Saharan Africa demands innovative solutions. In response, the consortia of “its4land”, a European Commission Horizon 2020 project, developed, adapted, and tested innovative geospatial tools including (1) software underpinned by the smart Sketch maps concept, called SmartSkeMa; (2) a workflow for applying unmanned aerial vehicles (UAV); and (3) a boundary delineator tool based on the UAV images. Additionally, the consortium developed (4) a platform called Publish and Share (PaS), enabling integration of all the outputs of tool sharing and publishing of land information through geocloud web services. The individual tools were developed, tested, and demonstrated based on requirements from Rwanda, Kenya, Ethiopia, and Zanzibar. The platform was further tested by key informants and experts in a workshop in Rwanda after the AfricaGIS conference in 2019. With the project concluding in 2020, this paper seeks to undertake an assessment of the tools and the PaS platform against the elements of fit-for-purpose land administration. The results show that while the tools can function and deliver outputs independently and reliably, PaS enables interoperability by allowing them to be combined and integrated into land administration workflows. This feature is useful for tailoring approaches for specific country contexts. In this regard, developers of technical approaches tackling land administration issues are further encouraged to include interoperability and the use of recognized standards in designs.

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“…Spatial information is extracted via the object detection techniques. An example of the workflow and its implementation can be found in [15,16].…”

Section: Smartskemamentioning

confidence: 99%

Section: Boundary Delineatormentioning

confidence: 99%

See 1 more Smart Citation

Geospatial Tool and Geocloud Platform Innovations: A Fit-for-Purpose Land Administration Assessment

Koeva

Humayun²,

Timm³

et al. 2021

Land

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“…It has taken decades for the cadastre to be complete in these countries, where conventional techniques such as ground-based surveying techniques or analogue aerial photogrammetry have typically been used [10]. Both methods are considered labour intensive and time-consuming [11,12]. The result was the creation of analogue cadastral maps and land records that later had to be digitised and integrated into a geographic information system (GIS) or broader land information systems.…”

Section: Introductionmentioning

confidence: 99%

Revising Cadastral Data on Land Boundaries Using Deep Learning in Image-Based Mapping

Fetai

Grigillo

Lisec

2022

IJGI

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One of the main concerns of land administration in developed countries is to keep the cadastral system up to date. The goal of this research was to develop an approach to detect visible land boundaries and revise existing cadastral data using deep learning. The convolutional neural network (CNN), based on a modified architecture, was trained using the Berkeley segmentation data set 500 (BSDS500) available online. This dataset is known for edge and boundary detection. The model was tested in two rural areas in Slovenia. The results were evaluated using recall, precision, and the F1 score—as a more appropriate method for unbalanced classes. In terms of detection quality, balanced recall and precision resulted in F1 scores of 0.60 and 0.54 for Ponova vas and Odranci, respectively. With lower recall (completeness), the model was able to predict the boundaries with a precision (correctness) of 0.71 and 0.61. When the cadastral data were revised, the low values were interpreted to mean that the lower the recall, the greater the need to update the existing cadastral data. In the case of Ponova vas, the recall value was less than 0.1, which means that the boundaries did not overlap. In Odranci, 21% of the predicted and cadastral boundaries overlapped. Since the direction of the lines was not a problem, the low recall value (0.21) was mainly due to overly fragmented plots. Overall, the automatic methods are faster (once the model is trained) but less accurate than the manual methods. For a rapid revision of existing cadastral boundaries, an automatic approach is certainly desirable for many national mapping and cadastral agencies, especially in developed countries.

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“…It is possible, for example, to infer that an individual's right to use a particular piece of land under either or both the customary and legal regimes using information about the social relations in which she participates (e.g., marriage, living in a particular community, etc.) SmartSkeMa was developed as part of the "its4land" H2020 project [4,5]. The its4land project developed four technological solutions for land tenure data acquisition.…”

Section: Introductionmentioning

confidence: 99%

SmartSkeMa: Scalable Documentation for Community and Customary Land Tenure

Chipofya

Jan

Schwering

2021

Land

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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.

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Innovative Geospatial Solutions for Land Tenure Mapping

Cited by 7 publications

References 13 publications

Geospatial Tool and Geocloud Platform Innovations: A Fit-for-Purpose Land Administration Assessment

Geospatial Tool and Geocloud Platform Innovations: A Fit-for-Purpose Land Administration Assessment

Revising Cadastral Data on Land Boundaries Using Deep Learning in Image-Based Mapping

SmartSkeMa: Scalable Documentation for Community and Customary Land Tenure

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