Get started
Work

Constraint-Based Spatial Data Management for Cartographic Representation at Different Scales

Year: 2022
Type: article
Abstract: This article elaborates on map-quality evaluation and assessment as a result of the generalization of geospatial data through the development of a methodology, which incorporates a quality data model including constraints. These constraints are used to guide the generalization process and they operate as requirements in quality controls applied for the quality evaluation and assessment of the resulting cartographic data. The quality model stores the required map specifications compiled as constraints, and provides quality measures along with new techniques for the evaluation and assessment of cartographic data quality. This secures the map composition process in each and every step and for all features involved, at any map scale. The methodology developed results in the creation of a scale-dependent cartographic database that contains exclusively the features to be portrayed on the map, generalized properly according to the map scale. It will reduce cartographers’ need to review each transformation throughout the map-composition process with considerable savings in time and money and, on the other hand, it will secure the quality of the final map. The formulation of the proposed methodology amalgamates generalization theory with the authors’ research in computer-assisted cartography, taking into account the work conducted on the topic by other researchers. In this study, the quality requirements, the measures and the associated techniques together with the results of the application of the proposed methodology for area and line features are described in detail to allow others to replicate and build on the presented results.
Source: Geographies
DOI: 10.3390/geographies2020018
Language: English
Open Access status: gold
Estimated APC paid: $1,047
OpenAlex ID: W4281479787
FWCI: 2.544
Cites: 9
Cited by: 4
Related to: 10