Cadastral Mapping with Earth Observation Technology

Konecny, G.

doi:10.1007/978-1-4419-0050-0_15

Cited by 8 publications

(8 citation statements)

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“…Literature shows applications ranging from environmental and regional studies to economics, and peace and conflict research, for example [6][7][8][9]. More specific to the interest of this paper, there is growing body of literature on methods to extract and map cadastral boundaries using EO data [10][11][12][13][14][15][16][17][18][19]. However, this literature rarely effectively bridges the knowledge gap between social land tenure and spatial descriptions of boundaries.…”

mentioning

confidence: 99%

Bridging the Semantic Gap between Land Tenure and EO Data: Conceptual and Methodological Underpinnings for a Geospatially Informed Analysis

Lee

Vries

2020

Remote Sensing

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When spatial land tenure relations are not available, the only effective alternative data method is to rely on the agricultural census at the regional or national scale, based on household surveys and a participatory mapping at the local scale. However, what if even these are not available, which is typical for conflict-affected countries, administrations suffering from a lack of data and resources, or agencies that produce a sub-standard quality. Would it, under such circumstances, be possible to rely on remotely sensed Earth Observation (EO) data? We hypothesize that it is possible to qualify and quantify certain types of unknown land tenure relations based on EO data. Therefore, this study aims to standardize the identification and categorization of certain objects, environments, and semantics visible in EO data that can (re-)interpret land tenure relations. The context of this study is the opportunity to mine data on North Korean land tenure, which would be needed in case of a Korean (re-)unification. Synthesizing land tenure data in conjunction with EO data would align land administration practices in the respective parts and could also derive reliable land tenure and governance variables. There are still many unanswered questions about workable EO data proxies, which can derive information about land tenure relations. However, this first exploration provides a relevant contribution to bridging the semantic gap between land tenure and EO data.

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confidence: 99%

Bridging the Semantic Gap between Land Tenure and EO Data: Conceptual and Methodological Underpinnings for a Geospatially Informed Analysis

Lee

Vries

2020

Remote Sensing

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“…This becomes a challenge especially for developing countries including Ethiopia where existing cadastres are often incomplete, or even decaying (Gelder, 2010;Kombe and Kreibich, 2000). They may have a historical lack of cadastral experience (Fekade, 2000), lack coherent institutional frameworks (Shabane et al, 2011;Vries et al, 2014), may be poorly administered (Roy, 2005;Larsson, 1991), and exhibit a shortage of financial resources (Konecny, 2009). These limitations impede the improvement of existing cadastres or the introduction of modern cadastral theories.…”

Section: A Background To Urban Land Cadastres and Land Governancementioning

confidence: 98%

Evolving urban cadastres in Ethiopia: The impacts on urban land governance

Alemie¹,

Bennett²,

Zevenbergen³

2015

Land Use Policy

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“…In these countries, cadastral mapping is often based on partly outdated maps or satellite images of low-resolution, which might include areas covered by clouds. Numerous studies have investigated cadastral mapping based on orthoimages derived from satellite imagery [22,[31][32][33][34][35][36][37] or aerial photography [38]. The definition of boundary lines is often conducted in a collaborative process among members of the communities, governments and aid organizations, which is referred to as "Community Mapping" [39], "Participatory Mapping" [22] or "Participatory GIS" [31].…”

Section: Application Of Uav-based Cadastral Mappingmentioning

confidence: 99%

“…Common in many approaches is the linearity of extracted features. This might be due to the fact that some countries do not accept curved cadastral boundaries [33]. Even if a curved river marks the cadastral boundary, the boundary line is approximated by a polygon [32].…”

Section: Cadastral Boundary Characteristicsmentioning

confidence: 99%

Review of Automatic Feature Extraction from High-Resolution Optical Sensor Data for UAV-Based Cadastral Mapping

et al. 2016

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Unmanned Aerial Vehicles (UAVs) have emerged as a rapid, low-cost and flexible acquisition system that appears feasible for application in cadastral mapping: high-resolution imagery, acquired using UAVs, enables a new approach for defining property boundaries. However, UAV-derived data are arguably not exploited to its full potential: based on UAV data, cadastral boundaries are visually detected and manually digitized. A workflow that automatically extracts boundary features from UAV data could increase the pace of current mapping procedures. This review introduces a workflow considered applicable for automated boundary delineation from UAV data. This is done by reviewing approaches for feature extraction from various application fields and synthesizing these into a hypothetical generalized cadastral workflow. The workflow consists of preprocessing, image segmentation, line extraction, contour generation and postprocessing. The review lists example methods per workflow step-including a description, trialed implementation, and a list of case studies applying individual methods. Furthermore, accuracy assessment methods are outlined. Advantages and drawbacks of each approach are discussed in terms of their applicability on UAV data. This review can serve as a basis for future work on the implementation of most suitable methods in a UAV-based cadastral mapping workflow.

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Cadastral Mapping with Earth Observation Technology

Cited by 8 publications

References 1 publication

Bridging the Semantic Gap between Land Tenure and EO Data: Conceptual and Methodological Underpinnings for a Geospatially Informed Analysis

Bridging the Semantic Gap between Land Tenure and EO Data: Conceptual and Methodological Underpinnings for a Geospatially Informed Analysis

Evolving urban cadastres in Ethiopia: The impacts on urban land governance

Review of Automatic Feature Extraction from High-Resolution Optical Sensor Data for UAV-Based Cadastral Mapping

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