Smith, E.S., Fleet, C., King, S. et al. (3 more authors) (2025) Estimating the density of urban trees in 1890s Leeds and Edinburgh using object detection on historical maps. Computers, Environment and Urban Systems, 115. 102219. ISSN 0198-9715
Abstract
We present a new end-to-end methodology for extracting symbols from historical maps and demonstrate an application of the method to extract details of the urban forests of Leeds and Edinburgh in the UK using Ordnance Survey maps from the 1890s. The methods presented allow tree symbols on 1:500 scale maps to be efficiently extracted, with our object detection model achieving an F1-score of 0.945. The results for each city are presented on the National Library of Scotland website and have been used to generate an estimate of 37 ± 1 tree symbols per hectare for Leeds in 1888–90 and 40 ± 1 tree symbols per hectare for Edinburgh in 1893–94. This is the first time that quantitative data has been obtained for historical urban tree counts in these two cities. The method presented can be expanded to other UK towns and cities and is a valuable tool for learning about the past, and changes to both the natural and built environment over time, aiding decisions on future tree planting. We discuss the process used to automate the generation of training data and to train a machine learning model to extract the symbols, comparing it with other possible models. This discussion provides context on how best to tackle similar problems of symbol extraction from historical maps and the issues that may arise in such automated analysis, alongside factors that must be considered when using historical maps as a data source.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Historical maps; Urban forests; Object detection; Machine learning; Template matching |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) |
Funding Information: | Funder Grant number NERC (Natural Environment Research Council) NE/S015396/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Nov 2024 13:12 |
Last Modified: | 19 Nov 2024 13:12 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.compenvurbsys.2024.102219 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:219758 |