Georeference in the analysis of the geometric content of early maps

TLDR

GIS is increasingly used to manage and analyze diachronic spatial data, yet early maps—rich in spatial and temporal information—are difficult to integrate into conventional GIS because of scarce geometric referencing and missing projective details. The study aims to recover the metric content of 15th‑ and 16th‑century historical maps, such as portolan charts and town views, by developing quantitative analysis methods. The authors employ both global and local transformation techniques—projective, affine, similarity, polynomial, finite‑element, point‑based, and feature‑based warping—to reconstruct and analyze the geometric content of these maps.

Abstract

Summary The use of geographic information systems (GIS) for the management and the analy- sis of diachronic geographical and territorial spatial distributed data is the main con- cern of this paper. This process of obtaining historical information through the read- ing of spatial changes as depicted in early maps and historical mapping in general is of main importance in cartographic heritage approach. In the study of the develop- ment of a territory, historical cartography plays an important role. Maps are offering valuable information related not only to spatial reference but also with respect to the time they are referred. In most cases, due to the scarcity of the geometric referencing and the lack of other relevant information concerning their projective properties, early maps are rather difficult to be inserted into routine GIS at least in a conven- tional sense. The aim of this research is to show how the metrical content of histori- cal maps (particularly portolan charts, isolarii, and perspective views of towns from the 15 th and 16 th century) can be recovered using analyses, which lead to definitions of some efficient methodologies for their quantitative analysis. This implies the use procedures, which are based on the use of transformations known in modern mapping sciences, which are distinguished as global (projective, affine, similarity, polynomial) or as local (finite element, point based or feature based warping).