Abstract This paper analyses the role of sensescapes in tourism planning, focusing on smart surveys and GIS mapping and analysis for pilgrimage tourism. A mixed methods approach and primary and secondary sources were used. A methodology was developed to collect and analyse territorial sensorial characteristics across the five main senses by using three main characteristics. A smart survey and GIS desktop and online tools were used to create a heat map. This is one of the first studies using a methodology based on smart surveys to collect sensory data, then using GIS to map and analyse it. By utilizing GIS for data collection and combining all sensory data, this study aims to bridge a gap in the previous research. This paper enhances tourism theory and practice by outlining the current and prospective use of emerging technologies, including smart surveys and GIS heat maps, in the tourism industry.

Abstract In this study, we explore the use of Big Data to dynamically optimize ambulance availability and response times in emergency medical services (EMS). Integrating Big Data principles with the Open Source Routing Machine (OSRM) routing engine, a novel algorithm was used to calculate travel times across an irregular grid, creating real-time, colour-coded time-accessibility maps. In contrast with traditional static models, this approach updates dynamically, accounting for road conditions, accidents and other disruptions to minimize delays. By excluding unusable segments from calculations, the algorithm ensures rapid recalculations, maintaining EMS coverage in evolving conditions. Testing showed significant improvements in response time estimation and resource allocation, particularly in urban environments with complex road networks. This real-time mapping tool offers EMS dispatchers an enhanced decision-support system, potentially saving lives by reducing ambulance response times and improving service availability across diverse areas.

Abstract An analysis of tram track conditions in Wrocław was conducted, focusing on the locations and causes of unplanned tram stoppages. Records of such incidents are not maintained in a standardized manner. In 2019, a total of 1,084 incidents were reported and described using over 100 distinct terms. The description of the location of these events was often limited to the street name. Of these incidents, 109 stoppages were attributed to track damage. In approximately 10% of these unplanned stoppages, the condition of the railhead played a crucial role – an area over which infrastructure managers have significant influence. To assess the spatial distribution of these stoppages, a map illustrating their occurrence was developed. Cumulative diagrams for each street were plotted on this map and overlaid with track condition data. The application of spatial data analysis provided valuable insights into the patterns and determinants of unplanned tram stoppages.

Abstract Accurate air quality prediction is essential for sustainable urban development. This study evaluates the performance of machine learning models, including DLinear and XGBoost, in comparison with the traditional Autoregressive Integrated Moving Average (ARIMA) method for predicting fine particulate matter (PM 2.5 ) concentrations in Kraków, Poland. A dense network of low-cost sensors was used to generate high-resolution spatial and temporal data. Prediction errors were analysed using the Getis-Ord Gi* spatial statistics method during both extreme pollution events and low pollution days. The results indicate that DLinear achieved the lowest root mean square error (RMSE = 3.8 µg/m 3 ), followed by XGBoost (RMSE = 6.7 µg/m 3 ) and ARIMA (RMSE = 9.2 µg/m 3 ). The spatial distribution of errors highlights the influence of environmental factors, such as humidity and proximity to water bodies, on model accuracy. These findings show the limitations of current prediction models and emphasize the need for spatially adaptive approaches to improve pollution.

Abstract This concise introduction discusses the proceedings of the 1st Warsaw Geographical Conference, held in September 2024 at the Faculty of Geography and Regional Studies at the University of Warsaw. Among the most significant scientific outcomes of this event are the seven papers published in this volume of Miscellanea Geographica – Regional Studies on Development . The research findings contained therein are briefly discussed below. They demonstrate the broad scope of recent geographical research in Poland, the multitude of topics addressed by researchers, and the relevance and strong standing of Polish geography.

Abstract Cartographic generalization reduces map detail to ensure clarity and accuracy at smaller scales. This study reviews road selection methods for multiscale mapping, covering scales from 1:10,000 to 1:1,000,000. The applied methodology was inspired by the PRISMA search model and based on searches in the Web of Science and Scopus databases, supported by the ResearchRabbit platform. As a result, five categories of approaches: semantic-based, stroke-based, mesh-based, graph-based, and machine learning-based, were identified and analyzed in terms of their strengths and limitations. Emphasis was placed on automation and the importance of selecting appropriate generalization techniques based on map scale and purpose. The literature review also revealed a variety of quality evaluation metrics used in the analyzed approaches, with a predominance of quantitative measures such as accuracy and F1-score, complemented by qualitative expert visual assessments.

Abstract The study focuses on predicting cycle path development for the year 2030 in Lublin by integrating land cover data with key factors such as demographic trends, cycling path design guidelines, and topographic features. The authors propose a novel method for identifying optimal locations for new bike paths, emphasizing the prioritization of routes, based on a demographic index across Lublin’s districts and on land cover forecasts for 2030. This forward-looking approach ensures that the proposed network aligns with future urban development and population distribution patterns, creating a cycling infrastructure that is both adaptable and responsive to the city’s evolving needs. As a result, the study designates areas of approximately 30 km 2 for the development of cycle tracks, creating a comprehensive and flexible cycle infrastructure that adapts to projected changes in land use.

Abstract This text analyses the anthropogeographical and ethnographic clues about the Forest Germans [Głusi Niemcy, Głuchoniemcy] in the Carpathian Foothills by the Enlightenment scholar and priest, Franciszek Siarczyński. In his description of Galicia at the dawn of the 19th century, the author explored the phenomenon of descendants of German-speaking settlers brought to the former Polish–Ruthenian frontier by King Kazimierz the Great in the 14th century. Siarczyński created an account that reflected the processes of describing the rural populations, their culture, and their history in the context of the space they inhabited that were characteristic of the late Polish Enlightenment. Among other things, he devoted considerable attention to the etymology of the term ‘Forest Germans’, and conducted field observations in the village of Markowa, near Łańcut, where he recorded old songs and elements of the local language, indicating that the residents spoke a distorted form of German. The materials collected by Siarczyński are likely the most detailed among existing studies on the Forest Germans in Polish literature. Furthermore, they provide an insight into the beginning of history of the scientific discourse that has developed around this phenomenon since the turn of the 18th and 19t centuries.

Abstract The central argument of this article is that the underlying theme of the five reports entitled Cities & Names in Italo Calvino's Invisible Cities is the fundamental inadequacy of names to signify cities. By challenging the taken-for-granted, common-sense idea that a name of a city corresponds to a well-defined urban entity, Calvino implicitly suggests that different cities cohabitate under the same name and that fundamentally names of cities are semiotically incorrect. The article is divided into two parts. The first expands on ideas about the correctness of proper names that since being presented in Plato's dialogue Cratylus have prevailed in western thought. The second part consists of five commentaries on the deceptive conflation between a city and its name that runs through the five reports included in Cities and Names.

Abstract This paper reflects on Malaysia’s twin capital cities – Kuala Lumpur and Putrajaya – drawing on diverse insights about cities, images, absence and memory from Calvino’s Invisible Cities. The paper examines the contrasting spaces, aesthetics and symbolism of Malaysia’s two adjacent capitals. It explores how Malaysian identity and memory are framed within these cities’ historical, cultural and geographical contexts: their landscape settings of jungle and water; their translation of particular architectural and urbanistic styles; and their cemeteries. It examines how Kuala Lumpur’s commemorative sites have been displaced and transformed over time. Kuala Lumpur and Putrajaya are explored as an illustration of Calvino’s idea of ‘Twofold Cities’: places that are described, and function, in relation to their twin, their opposite, or their bifurcation. Malaysia’s capital cities are also used to illustrate two themes that frame Calvino’s dialogue between Marco Polo and Kublai Khan: Cities and Empire, and Cities and the Orient.