Historical dataset of mills for Galicia in the Austro-Hungarian Empire/southern Poland from 1880 to the 1930s.

Published: 20 August 2021| Version 1 | DOI: 10.17632/8h9295v4t3.1


We present the dataset of mills from 1880 and 1920s-1930s in the area of the former Galicia (78,500 km2), now in Ukraine and Poland. We found 4,022 mill locations for 1880 and 3,588 for the 1920s-1930s. We present them as vector points in shapefile format with attributes for seven types of mills for 1880 and ten types of mills for 1920s-1930s, and mills counted in a 10 km grid. Our data contains two point layers and six grid layers (10 km side squares). All data is available in an open shapefile format, commonly used in Geographic Information Systems. Point layers contain the following attributes for each of the mills: auto-numbered numeric identifier (ID), type (Type), map sheet date (Map_year), longitude (Long), and latitude (Lat). According to the legend of these maps and explanations, the following types of mills can be distinguished for 1880: 1 – Gristmill (ger. Fruchtmühle), 2 – Sawmill (ger. Sägemühle), 3 – Paper mill (ger. Papiermühle), 4 – Powder mill (ger. Pulvermühle), 5 – Fulling mill (ger. Walkmühle), 6 – Windmill (ger. Windmühle), 7 – Ship mill, (ger. Schiffmühle). For the 1920s-1930s, the following types of mills were distinguished according to the legend of these maps and explanations. 1 – Watermill 2 – Steam mill 3 – Sawmill 4 – Sawmill with water wheel 5 – Motor sawmill 6 – Steam sawmill 7 – Steam mill 8 – Windmill 9 – Wind turbine 10 – Ship mill A reference grid designed by the European Environment Agency (EEA) in the ETRS 1989 LAEA projection (EPSG 9820) was used to create the grid layers, consisting of cells with sides of 10 km. In the set we provide, it contains the following attributes: auto-numbered numeric identifier of the cell (FID), cell code (CellCode), cell start coordinates (EofOrigin), (NofOrigin), and an attribute (Count) in which aggregated mill types are counted for each cell: gristmills, sawmills, windmills The data can be used in economic, demographic and environmental reconstructions, e.g. to estimate historical anthropopressure related to settlement, agriculture and forestry. Mills are often associated with river structures such as floodgates, dams, and millraces and therefore they are a good example of human interference in river ecosystems. They can also be one criteria for identifying areas where the local population used traditional environmental knowledge. It can be useful for a contemporary assessment of the environment’s suitability for devices using renewable energy sources. Finally, the data on the remains of former mills is suitable for the protection of cultural heritage sites that are technical monuments related to traditional food processing and industry. This research was funded by the Ministry of Science and Higher Education, Republic of Poland under the frame of “National Programme for the Development of Humanities” 2015–2021, as a part of the GASID project (Galicia and Austrian Silesia Interactive Database 1857–1910, 1aH 15 0324 83)


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Manual vectorisation of the mills on the computer screen was carried out using the ArcMap 10.8 software (“Edit” tool). At the points of the main cartographic symbols, a dot was placed indicating the mill location. In cases where there was only an inscription denoting the mill, a dot was placed on the inscription, or, if the inscription clearly referred to the building, the dot was placed on the building. A screen zoom of 1:4,000 – 1:10,000 was used. We used two sets of historical maps. The first is an administrative map covering the Kingdom of Galicia and Lodomeria together with the Grand Duchy of Kraków and the Duchy of Oświęcim, Zator and Bukovina (ger. Administrativ-Karte von den Königreichen Galizien und Lodomerien mit dem Grossherzogthume Krakau und den Herzogthümern Auschwitz, Zator und Bukowina in 60 Blättern), 1:115,200 scale from 1880. It is a version of the map from 1855 updated on the basis of the maps of the Military Geographical Institute in Vienna. Scans with a resolution of 600 dpi were obtained from the University of Vienna in TIFF format, without georeferencing. The maps were georeferenced by us to the ETRS 1989 LAEA projection in ArcMap 10.8 (“Georeferenced” tools). Maps of the Second Military Survey in the scale 1:28,800 served as the basis for the georeferencing. For 53 map sheets covering Galicia, 2,498 control points were used and the RMS error was 87.01 m. The second source for the reconstruction of how mills were distributed is the topographic map of the Military Geographical Institute (Tactical Map of Poland) in a scale of 1:100,000. The area of Galicia is covered by 109 sheets. It was made in independent Poland, mainly in the 1930s, but sheets from the 1920s are also available for some areas. The map sheets were obtained from the website mapywig.org, which identifies the following sources of scans: the Jagiellonian Digital Library (for 103 sheets), Library of Congress (for five sheets), and the Map Storehouse of the Earth Sciences Library of the University of Silesia (one sheet). The scans of the maps had a resolution of 600 dpi and were in .jpeg format. We have georeferenced all the sheets based on Polish topographic maps at a scale of 1:25,000 from the 1970s and 1980s, and modern World Imagery high-resolution satellite images, especially helpful for the area of Ukraine. The LAEA, ETRS 1989 mapping was adopted as the reference system. 5,167 checkpoints were used, and the RMS error was 25.24 m. The grid layers were developed by us to allow comparing the mills’ locations for both periods due to different RMS errors. The grid layer, designed by the European Environment Agency (EEA), was trimmed to the administrative boundaries of Galicia and joined spatially (Join Data based on spatial location) with the point layers of the mill locations. The Count option was used, counting points within each cell (a square with sides of 10 km)


Uniwersytet Jagiellonski w Krakowie Instytut Geografii i Gospodarki Przestrzennej


History, Engineering, Geography, Historical Geography, Heritage, Historical Ecology