Dataset of building locations in Poland in the 1970s and 1980s.

The aim of this study was to create a dataset of building locations in Poland from the 1970s-1980s. The source information was the historical 1:10 000 Polish topographic map. Building footprints were detected and extracted from approximately 8,500 scanned map sheets using the Mask R-CNN model implemented in Esri ArcGIS Pro software, and converted to point building locations. The dataset of building locations covers the entire country and contains approximately 11 million points representing buildings. The accuracy of the dataset was assessed manually on randomly selected map sheets. The overall accuracy is 95% (F1 = 0.98). The dataset may be used in conjunction with various contemporary land use, land cover and cadastral datasets in a broad range of applications related to long-term changes in rural and urban areas, including urban sprawl and its environmental and social consequences. It can also serve as a highly reliable reference dataset for regional or global settlement products derived, e.g., from early Landsat data.

The global wildland-urban interface.

The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle1,2. It is where human-environmental conflicts and risks can be concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation and the spread of zoonotic diseases3. However, a global analysis of the WUI has been lacking. Here, we present a global map of the 2020 WUI at 10 m resolution using a globally consistent and validated approach based on remote sensing-derived datasets of building area4 and wildland vegetation5. We show that the WUI is a global phenomenon, identify many previously undocumented WUI hotspots and highlight the wide range of population density, land cover types and biomass levels in different parts of the global WUI. The WUI covers only 4.7% of the land surface but is home to nearly half its population (3.5 billion). The WUI is especially widespread in Europe (15% of the land area) and the temperate broadleaf and mixed forests biome (18%). Of all people living near 2003-2020 wildfires (0.4 billion), two thirds have their home in the WUI, most of them in Africa (150 million). Given that wildfire activity is predicted to increase because of climate change in many regions6, there is a need to understand housing growth and vegetation patterns as drivers of WUI change.

Animal-vehicle collisions during the COVID-19 lockdown in early 2020 in the Krakow metropolitan region, Poland.

The interrelations between human activity and animal populations are of increasing interest due to the emergence of the novel COVID-19 and the consequent pandemic across the world. Anthropogenic impacts of the pandemic on animals in urban-suburban environments are largely unknown. In this study, the temporal and spatial patterns of urban animal response to the COVID-19 lockdown were assessed using animal-vehicle collisions (AVC) data. We collected AVC data over two 6-month periods in 2019 and 2020 (January to June) from the largest metropolis in southern Poland, which included lockdown months. Furthermore, we used traffic data to understand the impact of lockdown on AVC in the urban area. Our analysis of 1063 AVC incidents revealed that COVID-19 related lockdown decreased AVC rates in suburban areas. However, in the urban area, even though traffic volume had significantly reduced, AVC did not decrease significantly, suggesting that lockdown did not influence the collision rates in the urban area. Our results suggest that there is a need to focus on understanding the effects of changes in traffic volume on both human behaviour and wildlife space use on the resulting impacts on AVC in the urban area.

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

In this article, 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. The data was obtained as a result of manual vectorisation from 162 map sheets at scales of 1:115,200 and 1:100,000, according to the map legends. We found 4022 mill locations for 1880 and 3588 for the 1920s-1930s. We present them as vector points in shapefile, GML, GeoJSON, KML formats 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. 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.

Historical dataset of administrative units with social-economic attributes for Austrian Silesia 1837-1910.

Scientists from many disciplines need historical administrative boundaries in order to analyse socio-economic data in space and time. In this paper, we present a set of historical data consisting of administrative unit boundaries and exemplary socio-economic attributes for Austrian Silesia, an historical region located in modern Czechia and Poland. The dataset covers nearly 700 administrative unit boundaries on the level of cadastral or political communes and their subparts and was acquired through manual vectorisation of historical maps (1:28,800) from the period 1837-1841. The local-level units can be easily joined into higher-level divisions such as court or political districts for the period 1837-1910. The data can then be combined with statistical data collected approximately every 10 years for a similar period. Within the quality assessment, the relations between cartographic and census data and their credibility are analysed. The present dataset provides many possibilities for joining a wide range of historical statistical data to better understand various demographic and economic processes based on advanced analyses, e.g., by using GIS.

Mid-19th century road network dataset for Galicia and Austrian Silesia, Habsburg Empire.

In this paper, we present the vector dataset of the historical road network of Galicia and Austrian Silesia (>80 000 km2) in the mid-19th century - two regions of the former Habsburg Empire, located in Central Europe. The data were acquired manually from 455 map sheets of the Austrian second military survey map (1:28,800) for the four main road categories, according to the map legend. All the road categories present the roads passable at any time of the year, which was strategic information from the military point of view and build a network of 15 461 km. Currently, the data can be used by various researchers studying migrations, regional development, but also human impact on the environment, like land use change, invasive species introduction or landscape fragmentation. The dataset presents the times just before the most dynamic economic changes of the 19th century, which had a great impact on the region. On the other hand, the road network presented here was developed in the conditions of one country, the Habsburg Empire, which collapsed after the First World War, triggering the rise of new states and remodelling the transport network connections in Central Europe. Additionally, the data are accompanied by the layer of towns and villages with more than 2000 inhabitants, based on the 1857 Austrian census data.