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Innovative remote sensing methodologies for Kenyan land tenure mapping

Domain:

geospatialsocioeconomic

Record type:

software
Creator:
MilClaSopSer
Host:avatar
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.

Visit

figshare.com

Tasks

computer vision

Tags

Land use and environmental planningCadastreFeature extractionFit-for-purposeLand administrationLand tenureNeeds assessmentUAV

Licenses

CC BY 4.0