Leveraging machine learning and spectroscopic techniques towards estimating paper map scale levels
Nikolaos Merlemis, Anastasios L. Kesidis, Loukas-Moysis Misthos, Vassilios Krassanakis · Abstracts of the ICA · 2024
Map visual complexity has been a significant area of focus in cartographic research.Current methodologies provide a variety of techniques and metrics that can be used to objectively assess both the effectiveness and the efficiency of maps (e.g., Schnur et al., 2018;Liao et al., 2019;Tzelepis et al., 2020).Notably, the scale of a map seems to have a substantial impact as it correlates with the precision and volume of information conveyed by a cartographic product (Dumont et al., 2020).However, the scale information may not always be available.For instance, in historical paper maps, the scale information might be corrupted or inadequately represented.