The principal aim of this paper is to present the capabilities of newly developed GIS tools for measurement analysis of urban spatial layouts, using the square grid method. The study of urban morphology and metrology is a multistage process, which involves the metrological analysis of town plans. The main research step is the determination of measurement modules of town layouts, using the square grid. By using GIS software, the authors developed a new tool, named HGIS Tools, which allow to create any number of modular grids with the selected cell size that corresponds to urban units of distance and surface area. When investigating a large number of towns and cities, this offers a significant improvement of the research procedure. The paper presents a test of the tool’s potential on the example of regular medieval towns from the area of the former Teutonic Order state (currently the territory of Poland), diversified in terms of size, genesis and morphometrics. The obtained results confirmed that HGIS Tools allowed to determine the hypothetical measurement module of the layout of the cities studied. The results were consistent with the analyses of other authors carried out with the traditional grid-square methods. The test of the HGIS Tools showed their significant potential in conducting morphometric analyses of spatial arrangements of urban spatial layout on a larger scale.

The main goal of the paper is to verify the impact of the absorption of European Union (EU) grants on land cover changes in Polish municipalities in the years 2012–2018. The selection of the research area was justified by the fact that Poland is the largest and significantly spatially differentiated transition economy in Central-Eastern Europe, recognised as a substantial beneficiary of EU accession in 2004. The time range of analysis was set as the result of a comparison of data availability in Corine Land Cover (CLC) and Statistics Poland. The CLC dataset referring to land cover and land use changes between 2012 and 2018 was used. The focus on modifications taking place within one of the main land cover groups at level 3 of detail was applied in this research. These changes were analysed as percentages referring to the area of the municipality and to the total area of changes in the investigated period. Two categories of EU grants were considered: total and infrastructural (granted under EU Operational Programme “Infrastructure and Environment”). Moreover, some control economic, social, demographic, institutional, infrastructural, and environmental variables were applied to better explain land cover changes. Moran’s local statistic was employed to detect spatial hot-spots of EU grants absorption, as well as hot-spots of land cover changes. Then, a collection of various variables related to determinants of land cover changes was set. Economic factors, including EU grants absorption, as well as factors related to accessibility, agrarian structure, demography, environment, and spatial planning were investigated. Principal Component Analysis (PCA) was employed to convert the set of all considered variables into a set of few uncorrelated predictors. Finally, Geographically Weighted Regression (GWR) was applied to describe the spatially varied impact of investigated determinants, including EU grants, represented by estimated principal components on land cover changes.

Agricultural land covers more than half the area of metropolitan areas in Poland, and is therefore particularly prone to the influences of the processes associated with their development. The aim of the study was to analyse changes in agricultural land cover within the metropolitan areas of Poland for the years 1990–2012; and to capture their dynamics, types and directions. The percentage share of the total study area, for each of the forms of agricultural land cover and their changes were traced, with the spatial distribution of the changes also being determined. The results of the study show that in metropolitan areas, agricultural land cover is undergoing transformations that do not result in the loss of agricultural lands, or that involve a decrease in surface area due to their change into anthropogenic forms of land cover. The greatest transitions occurred between 2000 and 2006 and were observed in the outer zones of metropolitan areas.

The goal of the study is to explore the co-evolution of the tourism and industrial sectors. This paper addresses the concept of inter-path dependency as the theoretical framework for this study. The case study of Bełchatów industrial district is applied to discuss the co-evolution of tourism and heavy industries. Tourism and heavy industries are usually seen as mutually exclusive. However, in the case of the Bełchatów industrial district, tourism (starting from social tourism, through business tourism and educational tourism) is confirmed as being complementary to the industrial path shaped by triggering events (launch of radical industrialisation, and economic transition). Recently, implementation of the Just Transition Mechanism was planned and includes development of leisure tourism in the case study area. Some doubts of that intersectoral linkages are discussed in the paper – mainly in the context of the expected sustainable development of the Bełchatów industrial district – and followed by policy recommendations.

Small cities are an important part of the settlement system, a link between rural areas and large cities. Although they perform important functions, research focuses on large cities and metropolises while marginalizing small cities, the study of which is of great importance to progress in social sciences, geography, and urban planning. The main goal of this paper was to verify the impact of selected socio-economic factors on the share of built-up areas in 665 small Polish cities in 2019. Data from the Database of Topographic Objects (BDOT), Sentinel-2 satellite imagery from 2015 and 2019, and Local Data Bank by Statistics Poland form 2019 were used in the research. A machine learning segmentation procedure was used to obtain the data on the occurrence of built-up areas. Hot Spot (Getis-Ord Gi*) analysis and geographically weighted regression (GWR) was applied to explain spatially varying impact of factors related to population, spatial and economic development, and living standards on the share of built-up areas in the area of small cities. Significant association was found between the population density and the share of built-up areas in the area of the cities studied. The influence of the other socio-economic factors examined, related to the spatial and economic development of the cities and the quality of life of the inhabitants, showed great regional variation. The results also indicated that the share of built-up areas in the area of the cities under study is a result of the conditions under which they were established and developed throughout their existence, and not only of the socio-economic factors affecting them at present.

This paper investigates the social, demographic, and economic factors determining differences between forest identification based on remote sensing techniques and land registry. The Database of Topographic Objects and Sentinel-2 satellite imagery data from 2018 were used to train a forest detection supervised machine learning model. Results aggregated to communes (NUTS-5 units) were compared to data from land registry delivered in Local Data Bank by Statistics Poland. The differences identified between above mentioned sources were defined as errors of land registry. Then, geographically weighted regression was applied to explain spatially varying impact of investigated errors’ determinants: Urbanization processes, civic society development, education, land ownership, and culture and quality of spatial planning. The research area covers the entirety of Poland. It was confirmed that in less developed areas, local development policy stimulating urbanization processes does not respect land use planning principles, including the accuracy of land registry. A high education level of the society leads to protective measures before the further increase of the investigated forest cover’s overestimation of the land registry in substantially urbanized areas. Finally, higher coverage by valid local spatial development plans stimulate protection against forest classification errors in the land registry.