Georeferencing Historic Map Series: An Automated Approach

Georeferencing Historic Map Series: An Automated Approach

Tsipa, Eirini (TU Delft Architecture and the Built Environment)
Iliopoulos, Giorgos (TU Delft Architecture and the Built Environment)
Post, Oliver (TU Delft Architecture and the Built Environment)
Aalders, Rianne (TU Delft Architecture and the Built Environment)

Verbree, E. (mentor)
Schoonman, J.A. (graduation committee)
Meijers, B.M. (graduation committee)

Delft University of Technology

Geomatics

GEO1011 Synthesis Project

2023-11-16

The present report is the end result of the project that was carried out as part of the Geomatics Synthesis Project in cooperation with AllMaps, an open-source platform dedicated to the viewing and georeferencing of historic maps. The main objective of the project was to automatically georeference historic map series curated and digitised by the Dutch National Archive. This was based on the  corner coordinates of the map sheets. The first issue that had to be tackled was the reprojection of the original coordinates which were in Bonne projection
to WGS84 coordinates. To determine the corners of the map content within the sheets two methods were implemented. The first one detects the lines based on HoughLines Probabilistic Transformation and the second one detects lines based on the distribution of black pixels in the rows and columns of the images. In addition to map sheets with corner coordinates, there are two other sets of images which were georeferenced utilising a convolution neural network that performs feature matching. The feature matching was performed by running the two sets of images against the georeferenced sheets with known corner coordinates. To minimise the search space for this process a geocoder was used to determine the approximate location of the image. The implemented methods appear to hold the potential for georeferencing old map series. It is worth noting that the developed algorithms, while effective in many cases, may encounter challenges when dealing with irregularities on map sheets caused by the passage
of time, such as damage. Consequently, there is a great opportunity to further enhance the algorithms to ensure they can consistently and accurately georeference images, even when faced with such irregularities. This ongoing development will lead to improved georeferencing accuracy and user confidence.

Automation
Georeferencing
Map series
Cartography
Historic maps
Allmaps
Open data
Artificial intelligence (AI)
Feature matching
Corner detection
Bonnebladen
TMK
Bonne projection
TU Delft
Synthesis Project

http://resolver.tudelft.nl/uuid:a39e2c3e-640c-4fa5-8abf-1e376d75ae5f

https://github.com/geor-tudelft/iiifmap The code created for and used in this project https://allmaps.org/ The client of our project and the annotation pages we created can be viewed in its viewer

Student theses

student report

© 2023 Eirini Tsipa, Giorgos Iliopoulos, Oliver Post, Rianne Aalders