New Tools for the Classification and Filtering of Historical Maps
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Department of Civil, Environmental and Mechanical Engineering, University of Trento, Via Mesiano 77, 38123 Trento, Italy
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Fondazione Edmund Mach, Research and Innovation Centre, Centro di Ricerca e Innovazione, Via E. Mach 1, 38010 S. Michele all’Adige (TN), Italy
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The EFI Project Centre on Mountain Forests (MOUNTFOR), Edmund Mach Foundation, Via E. Mach 1, 38010 S. Michele all’Adige (TN), Italy
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C3A, Center Agriculture Food Environment, University of Trento, Via E. Mach 1, 38010 S. Michele all’Adige (TN), Italy
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Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Via Sommarive, 9, 38123 Povo (TN), Italy
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Fondazione Edmund Mach, Research and Innovation Centre, Department of Biodiversity and Molecular Ecology, Via E. Mach 1, 38010 S. Michele all’Adige (TN), Italy
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Department of Applied Geoinformatics and Spatial Planning, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16500 Praha - Suchdol, Czech Republic
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Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(10), 455; https://doi.org/10.3390/ijgi8100455
Received: 7 August 2019
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Revised: 9 September 2019
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Accepted: 10 October 2019
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Published: 14 October 2019
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.
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Keywords:
heritage maps; image classification; OBIA; map filtering; GRASS GIS
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MDPI and ACS Style
Gobbi, S.; Ciolli, M.; La Porta, N.; Rocchini, D.; Tattoni, C.; Zatelli, P. New Tools for the Classification and Filtering of Historical Maps. ISPRS Int. J. Geo-Inf. 2019, 8, 455. https://doi.org/10.3390/ijgi8100455
AMA Style
Gobbi S, Ciolli M, La Porta N, Rocchini D, Tattoni C, Zatelli P. New Tools for the Classification and Filtering of Historical Maps. ISPRS International Journal of Geo-Information. 2019; 8(10):455. https://doi.org/10.3390/ijgi8100455
Chicago/Turabian StyleGobbi, Stefano, Marco Ciolli, Nicola La Porta, Duccio Rocchini, Clara Tattoni, and Paolo Zatelli. 2019. "New Tools for the Classification and Filtering of Historical Maps" ISPRS International Journal of Geo-Information 8, no. 10: 455. https://doi.org/10.3390/ijgi8100455
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