More and more private citizens collect and publish environmental data via web-based geographic information systems. These systems face two challenges: The user interface must be intuitive and the processing of geographic information must account for cognitive impact. We propose to use sketch maps as the medium for interaction, because they reflect a person's spatial knowledge. Information from sketch maps is distorted, schematized, incomplete, and generalized and metric maps are not. This article employs qualitative representations for the alignment of sketch and metric maps. We suggest a set of cognitively oriented aspects in sketch maps stably computed by people and evaluate qualitative representations to formalize these aspects. This allows us to align and integrate geographic information from sketch maps.

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.

No abstract

No abstract

Sketch maps are externalizations of cognitive maps which are typically distorted, schematized, incomplete, and generalized. Processing spatial information from sketch maps automatically requires reliable formalizations which are not subject to schematization, distortion or other cognitive effects in sketch maps. Based on previous empirical work, we identified diff erent sketch aspects such as ordering, topology and orientation to align and integrate information from sketch maps with metric maps qualitatively. This research addresses the question how these qualitative sketch aspects can be formalized for a computational approach for sketch map alignment.In this study, we focus on the ordering aspect: ordering of landmarks and street segments along routes and around junctions. We first investigate diff erent qualitative representations and propose suitable representations to formalize these aspects. The proposed representations capture qualitative relations between spatial objects in the form of qualitative constraints networks. We then evaluate the proposed representations by testing the accuracy of qualitative constraints between sketched objects and their corresponding objects in a metric map. Results of the evaluation show that the proposed representations are suitable for the alignment of spatial objects from sketch maps with metric maps.