Abstract
Abstract. This article presents a method to estimate the capture scale of a geographical database based on the characterization of its level of detail. This contribution fits in a larger research, dealing with the development of a general model to estimate the imprecision of length and area measurements computed from the geometry of objects of weakly informed geographical databases. In order to parameterize automatically a digitizing error simulation model, the characteristic capture scale is required. Thus, after a definition of the different notions of scales in geographical databases, the proposed method is presented. The goal of the method is to model the relation between the level of detail of a geographical database, by exploring inter-vertices distances, and its characteristic capture scale. To calibrate the model, a digitizing test experiment is provided, showing a clear relation between median intervertices distance and characteristic capture scale. The proposed knowledge extraction method proves to be the usefull in order to parameterize the measurement imprecision estimation model, and more generally to inform the database user when the capture scale is unknown. Nevertheless, further experiments need to be provided to improve the method, and model the relation between level of detail and capture scale with more efficiency.
Highlights
1.1 Context of the studyDespite a large number of contributions during the last decades (Devillers et al, 2010), or range of indicators proposed by standardization organizations (ISO 19157, 2013), the communication of the impact of spatial data quality to the final user remains a major issue
This contribution fits in a larger research, dealing with the development of a general model to estimate the imprecision of length and area measurements computed from the geometry of objects of weakly informed geographical databases
This article proposed a method to estimate the characteristic capture scale of a geographical database, in order to parameterize automatically a digitizing error simulation model used to assess the imprecision of measurements computed from the geometry of vector objects
Summary
1.1 Context of the studyDespite a large number of contributions during the last decades (Devillers et al, 2010), or range of indicators proposed by standardization organizations (ISO 19157, 2013), the communication of the impact of spatial data quality to the final user remains a major issue. The estimation of geometric measurements imprecision requires to identify all the potential causes affecting geometric measurements, and model their impacts In this context, the goal of this research deals with the development of a general model to allow a user of geographical data to estimate the imprecision of geometric measurements computed from weakly informed databases, without any reference data (Girres, 2011b). The goal of this research deals with the development of a general model to allow a user of geographical data to estimate the imprecision of geometric measurements computed from weakly informed databases, without any reference data (Girres, 2011b) It supposes to (a) identify all the potential causes affecting geometric measurements, (b) develop models to estimate these impacts on measurements, (c) communicate measurement imprecision to the final user. The avalaibility of these information is not systematic, espacially when the database is poorly informed (e.g. absence of metadata)
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