New Tools for the Classification and Filtering of Historical Maps

Stefano Gobbi,Nicola La Porta,Duccio Rocchini,Clara Tattoni,Paolo Zatelli,Marco Ciolli

doi:10.3390/ijgi8100455

Abstract

Historical maps constitute an essential information for investigating the ecological and landscape features of a region over time. The integration of heritage maps in GIS models requires their digitalization and classification. This paper presents a semi-automatic procedure for the digitalization of heritage maps and the successive filtering of undesirable features such as text, symbols and boundary lines. The digitalization step is carried out using Object-based Image Analysis (OBIA) in GRASS GIS and R, combining image segmentation and machine-learning classification. The filtering step is performed by two GRASS GIS modules developed during this study and made available as GRASS GIS add-ons. The first module evaluates the size of the filter window needed for the removal of text, symbols and lines; the second module replaces the values of pixels of the category to be removed with values of the surrounding pixels. The procedure has been tested on three maps with different characteristics, the “Historical Cadaster Map for the Province of Trento” (1859), the “Italian Kingdom Forest Map” (1926) and the “Map of the potential limit of the forest in Trentino” (1992), with an average classification accuracy of 97%. These results improve the performance of classification of heritage maps compared to more classical methods, making the proposed procedure that can be applied to heterogeneous sets of maps, a viable approach.

Highlights

Historical maps are available in many nations and regions of the world, and represent an invaluable source of information in many fields [1,2].Depending on the purpose for which the maps were conceived, historical maps are typically reliable in terms of precision and spatial accuracy, they can usually be compared to modern maps to make qualitative assessments and to quantify the changes that have occurred in the past [3,4]
This paper presents new map classification and filtering procedures based on Object-based Image Analysis (OBIA) that have been implemented using GRASS GIS [26], developing new techniques and software modules for text and symbol removal
The minsize parameter values have been chosen to match the different sizes of text and symbols that have to be removed after the classification on each map

Summary

Introduction

Historical maps are available in many nations and regions of the world, and represent an invaluable source of information in many fields [1,2].Depending on the purpose for which the maps were conceived, historical maps are typically reliable in terms of precision and spatial accuracy, they can usually be compared to modern maps to make qualitative assessments and to quantify the changes that have occurred in the past [3,4]. In ecological studies, it is widely recognized that past land use affects present biodiversity distribution and status [5,6,7,8], ecosystem service provision [9] and traditional ecological knowledge [10]. The present structure and the ecological dynamics of the landscape in an area can be understood only having a profound knowledge of the land use changes previously occurred in the region [4]. The interpretation of many of the results of contemporary ecological analyses, including those obtained with field sampling, is more robust if considered in a framework that includes past landscapes, underlining the importance of historical maps [11]. The same concepts can be applied to many other disciplines or study areas like urban studies [12], geomorphology [13], planning [14], social science and economic studies [15], anticipation [16] and history [17]

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Results

Conclusion