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

Abstract

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.

Remote Sensing for Land Administration

“…Third, Lee and de Vries [34] seek to bridge the semantic gap between land tenure concepts and remotely sensed or earth observation (EO) data. Specifically, they investigate the circumstances where it is possible to rely on EO data to inform land administration applications, such as cadastral mapping and land use change monitoring.…”

Testing and Validating the Suitability of Geospatially Informed Proxies on Land Tenure in North Korea for Korean (Re-)Unification

“…Along with the growth of remote sensing applications in SES, there has been growing recognition and evidence of the vital links between remote sensing and land administration [12][13][14][15][16][17][18][19]. Geospatial data has emerged as powerful source of information for enabling both socio-technical assessment [20] and socio-legal analysis [21] in land administration sphere. Moreover, recent advancements have led to a renewed interest in identifying socio-spatial footprints of land boundaries and associated land rights through integration of different sets of geospatial and socio-economic data and informative interpretation [12,21].…”

“…Geospatial data has emerged as powerful source of information for enabling both socio-technical assessment [20] and socio-legal analysis [21] in land administration sphere. Moreover, recent advancements have led to a renewed interest in identifying socio-spatial footprints of land boundaries and associated land rights through integration of different sets of geospatial and socio-economic data and informative interpretation [12,21]. Thus, a novel approach to land administration sheds a contemporary light on grounded theories and practices of land tenure, use, value, development, and governance.…”

“…To date, however, there is a notable paucity of evidence-based literature describing and investigating how to identify unknown land tenure relations in North Korea due to the obvious difficulties in obtaining and analyzing empirical data. Several ways of overcoming these barriers to capturing the relationship between land tenure and governance and Korean (re-)unification process have recently been suggested that involve understanding and suggesting methods and solutions to problems [21,39,40]. Drawing upon both land administrative and geospatial engineering approaches, these enabled to provide reasonably consistent evidence and knowledge-base of an association between land tenure/land governance and (re-)unification of which relatively little is known.…”

Post-disaster recovery assessment using remote sensing image analysis and agent-based modeling

“…However, by increasing the spatial, spectral, and temporal resolutions of the remote sensing images as well as new tools to acquire data, the available objects and features for solving the puzzles will increase and lead to developing robust proxies. Already the results of this review were used by researchers to address the identified gaps (Castañeda-Garza et al 2019;Hodicky et al 2020) and develop new remote sensing-based proxies or combine them to address DRM (Derakhshan et al 2020), and even using the term "proxy" as defined in this study in other domains rather than DRM (Lee and De Vries 2020). The proposed conceptual framework in Chapter 3 comprehensively addresses the aim of recovery assessment based on remote sensing data.…”