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

Walter Timo de Vries,Cheonjae Lee

doi:10.3390/rs12020255

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.

Highlights

Land tenure data contain geospatial, anthropological and socioeconomic attributes since it builds on both the physical delineation of land and the identification of social relations governing land use, land access and land ownership [1,2]
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
In order to overcome some of these challenges, we propose to use a mix of methods and information fusion to identify proxies that may help derive unknown land tenure relations

Summary

Introduction

Land tenure data contain geospatial, anthropological and socioeconomic attributes since it builds on both the physical delineation of land and the identification of social relations governing land use, land access and land ownership [1,2]. There is a dearth of the methodological reflections in how such geospatial technologies can identify and formalize land tenure relations. What these technologies are currently able to do includes: (1) underpinning land tenure-enabling environments; (2) mining land tenure data; (3) transforming land tenure relations [5]. The quality of all these heavily depends on the completeness and full access of the terrain and the data sources. In many cases these basic criteria cannot be guaranteed, leaving the land tenure information scarce [1]

Objectives

Methods

Findings

Conclusion