Geographies

This study integrates the price-to-income ratio (PIR) with Pareto distribution characteristics to provide a novel approach for evaluating home affordability across U.S. counties. The methodology offers a new lens for the analysis of home affordability by capturing both the extreme values and central tendencies of PIR. The study normalizes the resulting Pareto parameters to a common scale and integrates data from the Zillow Home Value Index and the U.S. Department of Commerce’s SAIPE program to create a single affordability index. The findings point to significant regional differences: coastal and urban regions, such as California and New York, face significant affordability challenges, whereas the Midwest, especially Kansas, has higher affordability. The results highlight the significance of targeted policy interventions and are consistent with the body of research on systemic risk and housing market dynamics. This study also opens new avenues for future research, including the impact of economic factors on affordability and cross-regional comparative studies. The suggested approach encourages more equitable access to housing by providing policymakers with a useful tool to track and manage challenges related to housing affordability. Full article

Vulnerability is often analysed as a static condition of residents at a location, exposed to disaster and other risks. Studies on individual aspects of mobility and vulnerability exist, but comprehensive studies or guiding frameworks are lacking. The paper’s unique contribution compared to existing vulnerability models lies in emphasising vulnerability not only at fixed places, but also during transit, movement, and temporary phases. This paper highlights the current state of research on mobility vulnerability within disaster risk contexts. Through a systematic literature review, the study discovers a lack of research analysing specific vulnerabilities during mobility. Additionally, existing vulnerability frameworks are improved by incorporating (i) disaster risk and impact scenarios, (ii) different types of movements and mobilities linked to disaster risk situations, (iii) multiple localities, modalities, and temporalities, as well as multiple risks during sequences of movement and stationary phases, (iv) daily and occasional hazards, and (v) emic and etic perspectives on vulnerability. The findings of this study aim to inform future research on risk and vulnerability, supporting more effective responses amidst the changing dynamics of disaster situations. Full article

This study evaluates the impact of different territorial contexts on academic mobility within the framework of the Erasmus Programme, using data on Key Action 1 exchanges between 2015 and 2023. Using official EU datasets and a gravity model framework, the research investigates how economic performance, geographical distance, EU membership, AUF (Agence Universitaire de la Francophonie) regional affiliation, and state contiguity shape international academic flows. The research developed two gravity models: one aimed to measure the potential barriers to academic flows through a residuals analysis, and the second integrated territorial delineations as predictors. In both models, the core of the explanatory variable is formed by indicators describing the economic performance of states and the distance between countries. When applied, the models converge in emphasizing that the inclusion of states in different territorial configurations has a strong effect on the structuring of academic flows. This suggests that the Erasmus Programme exhibits trends of overconcentration of flows in a limited number of countries, questioning the need for a more polycentric strategy and a reshaping of the funding mechanisms. Even if the gravity models behave well, given the limited number of predictors, further studies may need to incorporate qualitative indicators for a more comprehensive evaluation of the interactions. Full article

Europe has experienced a growing divergence in trends of population change across the urban hierarchy. A key driver of this divergence is internal migration, which underpins the efficient functioning of the economy by enhancing labor market flexibility and allowing people to choose the most desired locations. Internal migration in Latvia is of increasing importance, as the propensity to change residence within national borders has become the primary mechanism of demographic change, shaping population redistribution across regions and the urban hierarchy. We used Latvia as a case study, exemplified by the monocentric urban system with Riga City at its center, as well as a relatively dense network of small towns spread across all regions. Small towns in Latvia, although not characterized by high levels of internal migration, exhibit notable changes in their demographic and socioeconomic composition. Our analysis uses administrative data on registered migration for each year from 2011 to 2021 to characterize migration patterns, as well as data from the 2011 and 2021 census rounds on 1-year migration to analyze the composition of the migrant population. The results showed sociodemographic variations in the characteristics of individuals migrating to small towns. Understanding the temporal and spatial dynamics of internal migration patterns and compositional effects is vital for effective local and regional development policies to plan essential services and infrastructure. Full article

The Sohodol Gorges has become a location of interest for tourists seeking ecological experiences and outdoor activities. The main purpose of the present study is to evaluate the attitudes of Romanian tourists toward the development of geotourism in this region following the COVID-19 pandemic. In conjunction with the research questions, hypotheses, variables, and research methodology, the following research objectives were emphasized in this study of the Oltenia region: (1) investigate how certain socio-demographic variables, such as age, gender, level of education, and occupation, influence tourists’ perceptions of the various aspects of geotourism development in the Sohodol Gorges; (2) analyze the different dimensions of geotourism, including its economic, ecological, and socio-cultural impacts, thus contributing to a deeper understanding of how geotourism is perceived in the study area in the post-pandemic context. For a qualitative evaluation of the information presented in this study, the authors used a qualitative survey with open questions and closed questions as a data collection method. For data processing and analysis, the EViews version 12.0 software package was used, enabling complex statistical analyses such as multiple regressions and correlation coefficient determination. These techniques were essential for identifying and interpreting the relationships between demographic variables and tourist perceptions. The research results provide a detailed picture of the influence that demographic and behavioral factors have on tourists’ perceptions in the context of post-COVID-19 geotourism development in the Sohodol Gorges of Romania. Education level and age play a significant role in shaping economic and environmental perceptions, indicating that tourists with higher education levels are more aware of the economic and ecological impact of tourism. Full article

Climate change poses significant risks to both natural and urban systems, and fostering climate literacy among younger generations is increasingly recognized as a key component of resilience strategies. This paper presents the outcomes of a transnational climate education project involving high school students from Cinisello Balsamo (Italy) and Edremit (Turkey), developed under the EU-funded Town Twinning program. The project combined scientific seminars, experiential learning, and digital tools (including carbon footprint calculators and immersive virtual glacier tours) to enhance climate knowledge and civic engagement. Youth Climate Councils were established to co-develop local sustainability proposals and engage with municipal authorities. Quantitative tests and qualitative evaluations confirmed significant learning gains and high satisfaction among participants. A comparative analysis with international initiatives highlights the project’s unique integration of scientific rigor, participatory methods, and cross-border cooperation. The proposed model offers a replicable framework for embedding place-based climate education into urban governance and youth policy. Full article

This study aimed to investigate the physical factors influencing the occurrence of forest fires and to create a fire risk map of Phrae Province. Remote sensing and geographic information system (GIS) technology were applied for the analysis, focusing on seven factors: the digital elevation model (DEM); slope; Normalized Difference Vegetation Index (NDVI); aspect; and distances from people, water, and roads. All of these geographical factors can affect forest fires. This resulted in a MaxEnt (Maximum Entropy) model with an AUC (area under the curve) of 0.849, indicating its great prediction ability. The findings revealed that the variables influencing forest fire incidence were the DEM, NDVI, slope, distance from roads, distance from water, distance from communities, and aspect, in that order. Subsequently, a fire risk map for wildfires was developed by reclassifying the data into five levels—very low risk, low risk, medium risk, high risk, and very high risk—accounting for 341,395.54, 88,132.64, 76,162.41, 81,157.55, and 57,384.10 hectares or 52.99, 13.68, 11.82, 12.60, and 8.91% of the total area, respectively. The areas classified as very high risk, high risk, medium risk, and low risk included the Song, Long, and Rong Kwang Districts. The area with the lowest risk was Nong Muang Khai District. Full article

Outdoor activities are significantly influenced by meteorological conditions. Human tower exhibitions are performed in urban squares. Human towers were recognised as an Intangible Cultural Heritage by UNESCO in 2010. The objectives of this study are (1) to analyse the long-term temperature trend (1951–2024) for four summer human tower exhibitions; (2) to determine to extent to which thermal comfort has worsened over the last 74 years based on the Heat Index (HI); and (3) to assess temperature and thermal comfort in the squares during the selected evening exhibitions. Two of the four human tower exhibitions were recently rescheduled to the evening in response to afternoon heat. Temperatures have increased both in the afternoon and in the evening over the last 74-year period, but the warming is more pronounced in the afternoon. Evening hours have also become warmer, although they still represent a more tolerable thermal condition for outdoor activities. However, thermal comfort has decreased in three of the four human tower exhibitions in recent years. Two sensors recorded relative humidity and temperature data to determine the meteorological conditions during the exhibitions in the squares. The temperature decreased as the exhibition progressed. This pattern was modified by factors such as the presence of clouds and the shade generated by the buildings. HI values above 32 °C (extreme caution threshold) were prevalent in one exhibition. In the other three exhibitions, the values remained within the caution threshold for the majority of the time. Rescheduling the exhibition is one adaptation measure to ensure that human towers are performed safely in the face of climate change. Full article

Urban boundary delineation is essential for understanding spatial structure, monitoring urbanization, and guiding sustainable land management. Nighttime light (NTL) data effectively capture urban dynamics across multiple spatial scales. This study integrates NTL data with spectral indices to delineate the urban boundaries of the Barcelona Metropolitan Region (BMR) from 2006 to 2018. Through multivariate regression analysis, the normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) are identified as key indicators of urban spatial heterogeneity. These indices are combined with brightness thresholds derived from three NTL datasets, DMSP-OLS, Black Marble, and VIIRS, to delineate urban areas more accurately. Results indicate that VIIRS achieved the highest precision in identifying construction land and urbanized areas, with an overall accuracy exceeding 90% and consistency with population density and GDP distribution. A strong spatial correlation between urban distribution and the NDVI–NDBI relationship is confirmed in the BMR. The coupling of multisource remote sensing data improves the accuracy, stability, and reliability of urban boundary delineation, overcoming single-source limitations. This integrated method supports urban planning and sustainable land management through consistent, objective urban mapping and offers a practical reference for applying remote sensing technologies to monitor urbanization dynamics across broader spatial and temporal contexts. Full article

Historical water infrastructures represent an overlooked cultural heritage of extraordinary importance, encompassing centuries of technical knowledge deeply intertwined with the landscape and social life. Matera stands out as a case study of international relevance, where the morphology of the historic urban fabric of the Sassi has been shaped by the Grabiglioni, or Fossi, streams that today lie hidden and compromised, deprived of the recognition they deserve. This study presents an integrated analysis that combines history, morphology, hydrology, and infrastructure to uncover the origin, evolution and cultural value of the entire context. Thus, the environmental and identity-related potential of these historical infrastructures emerges, along with the critical issues they pose, partly as a consequence of urban expansions. Reintegrating the Grabiglioni into urban development policies is not merely a matter of preservation; it represents a strategic opportunity to transform this heritage into a resource for safety, sustainability, and urban regeneration. The multidisciplinary approach proposed here can serve as a guide for similar studies on historical water infrastructures, restoring life and memory to legacies that narrate a timeless engineering intelligence and a careful understanding of the various territorial components (morphology, climate, works, and transformations). This article is a revised and expanded version of Altamura D. et al., Interdisciplinary investigation approach to analyze historical water infrastructures and urban transformations: the case study of the Grabiglioni in the Sassi of Matera, Italy, presented at CEES—International Conference on Construction, Energy, Environment and Sustainability in Bari (2025). Full article

Wildfire behavior and post-fire effects are strongly modulated by terrain, yet the relative influence of individual topographic factors on burn severity remains incompletely quantified at landscape scales. The Composite Burn Index (CBI) provides a field-calibrated measure of severity, but large-area analyses have been hampered by limited plot density and cumbersome data extraction workflows. In this study, we paired 6150 CBI plots from 234 U.S. wildfire events (1994–2017) with 30 m SRTM DEM, extracting mean elevation, slope, and compass aspect within a 90 m buffer around each plot to minimize geolocation noise. Topographic variables were grouped into ecologically meaningful classes—six elevation belts (≤500 m to >2500 m), six slope bins (≤5° to >25°), and eight aspect octants—and their relationships with CBI were evaluated using Tukey HSD post hoc comparisons. Our findings show that all three factors exerted highly significant influences on severity (p < 0.001): mean CBI peaked in the 1500–2000 m belt (0.42 higher than lowlands), rose almost monotonically with steepness to slopes > 20° (0.37 higher than <5°), and was greatest on east- and northwest-facing slopes (0.19 higher than south-facing aspects). Further analysis revealed that burn severity emerges from strongly context-dependent synergies among elevation, slope, and aspect, rather than from simple additive effects. By demonstrating a rapid, reproducible workflow for terrain-aware severity assessment entirely within GEE, the study provides both methodological guidance and actionable insights for fuel-management planning, risk mapping, and post-fire restoration prioritization. Full article

Market gardening plays a crucial role in ensuring food security and reducing poverty in Africa’s rapidly urbanizing regions. However, urban agricultural systems are increasingly threatened by climatic shocks such as floods, droughts, and heat waves. This study uses an integrated approach to analyze the multidimensional factors of climatic vulnerability among urban market gardeners in the Grand Nokoué region of Benin. Based on socio–economic, technico–agronomic, and perceptual data collected from 369 growers, multiple correspondence analysis (MCA) coupled with ascending hierarchical analysis (AHA) was performed to identify vulnerability profiles. K–means partitioning was used to confirm the optimal number of groups, thereby guaranteeing the robustness and internal consistency of the typology. Three distinct vulnerability groups were identified, each characterized by specific socioeconomic, technical, and territorial characteristics, as well as varying exposure to the risks of flooding, drought, and dry spells. The results show that the most vulnerable farmers tend to be young women with low incomes, limited access to land, and a reliance on manual irrigation in flood–prone areas. These findings emphasize the uneven distribution of adaptive capacities and the pressing requirement for tailored public policies to enhance resilience, especially among small–scale, low–income, and land–insecure urban farmers, who are vulnerable to various climate–related risks. Full article

Climate change affects all human and ecological systems. The rapid climate impacts are increasingly evident on all economic activities, including tourism. Regarding the fact that “the window is closing”, climate resilience is urgently needed to protect tourism resources and maintain the quality of tourism offerings. Since the recent climate and tourism scientific literature emphasizes the necessity to mobilize existing knowledge, standardize practices, and explore appropriate tools related to tourism adaptation, we provided desk research and discussed the latest achievements of the Intergovernmental Panel on Climate Change’s (IPCC) and related knowledge platforms. According to the results of this review, it seems that the vast majority of the authors use vulnerability assessment (VA) to provide a solid basis for climate change adaptation (CCA) options applicable to tourism. Also, there is a lack of application of the latest IPCC recommendations founded in climate risk assessment (CRA). In the context of CRA, vulnerability was often assessed in a static way, with limited consideration of future hazards, probabilistic estimates, and the interactions between climatic and non-climatic drivers. Moreover, the methodologies applied to assess climate-related issues in tourism have been highly heterogeneous, hindering comparability and aggregation of results. Since risk is a useful conceptual framework for understanding tourism’s climate issues and modalities to reach its climate resilience, we discussed the significance of shifting the vulnerability concept towards a risk-centered framework. This review paper also provides a basis for a common understanding of CRA, a step-by-step approach to its assessment, and the explanation of CCA options to strengthen the tourism community, since a decisive decade of climate action is upon us. Full article

Fast fashion is a rapidly expanding sector characterized by high production volumes, low costs, and short product lifecycles. While recent efforts have focused on improving sustainability within supply chains, consumer behavior remains a critical yet underexplored driver of environmental impacts. This study presents a web-based calculator tool designed to estimate both the carbon and plastic footprints associated with individual fast fashion consumption, with a particular focus on shopping behaviors, garment disposal, and laundry habits. Adopting a geographical perspective, the analysis explicitly considers the spatial dynamics of consumption and logistics within the urban context of Milan (Italy), a dense metropolitan area representative of high fashion activity and mobility. By incorporating user-reported travel patterns, logistics routes, and localized emission factors, the tool links consumer habits to place-specific environmental impacts. By involving over 360 users, the tool not only quantifies emissions and plastic waste (including microfibers) but also serves an educational function, raising awareness about the hidden consequences of fashion-related choices. Results reveal high variability in environmental impacts depending on user profiles and behaviors, with online shopping, frequent use of private vehicles, and improper garment disposal contributing significantly to emissions and plastic pollution. Our findings highlight the importance of integrating consumer-focused educational tools into broader sustainability strategies. The tool’s dual function as both calculator and awareness-raising platform suggests its potential value for educational and policy initiatives aimed at promoting more sustainable fashion consumption patterns. Full article

Flood impacts are intensifying due to the increasing frequency and severity of factors such as severe weather events, climate change, and unplanned urbanization. This study focuses on Briar Creek in Charlotte, North Carolina, an area historically affected by flooding. Three machine learning algorithms —bagging (random forest), extreme gradient boosting (XGBoost), and logistic regression—were used to develop a flood susceptibility model that incorporates topographical, hydrological, and meteorological variables. Key predictors included slope, aspect, curvature, flow velocity, flow concentration, discharge, and 8 years of rainfall data. A flood inventory of 750 data points was compiled from historic flood records. The dataset was divided into training (70%) and testing (30%) subsets, and model performance was evaluated using accuracy metrics, confusion matrices, and classification reports. The results indicate that logistic regression outperformed both XGBoost and bagging in terms of predictive accuracy. According to the logistic regression model, the study area was classified into five flood risk zones: 5.55% as very high risk, 8.66% as high risk, 12.04% as moderate risk, 21.56% as low risk, and 52.20% as very low risk. The resulting flood susceptibility map constitutes a valuable tool for emergency preparedness and infrastructure planning in high-risk zones. Full article

This study investigates how land access, inheritance expectations, and socio-economic conditions influence migration intentions of rural youth in central Vietnam. Drawing on survey data from 200 young respondents and employing logistic regression analysis, the research reveals that youth with higher levels of education and income exhibit a greater propensity to migrate in pursuit of improved livelihoods. Male respondents were significantly more likely to migrate, reflecting gender norms and unequal access to opportunities. Crucially, secure land tenure—measured through formal land titles and perceived inheritance rights—was strongly associated with lower migration intentions. Conversely, tenure insecurity emerged as a significant push factor, undermining youth confidence in long-term rural investment and contributing to land use instability. This study argues that secure land access is not only vital for sustaining rural livelihoods but also foundational for youth and women’s engagement, socio-economic stability, and long-term community resilience. From this viewpoint, this study highlights the need for youth-inclusive land reforms, the promotion of rural entrepreneurship, and expanded access to vocational training as critical policy interventions. Full article

The Cau River Basin in northeastern Vietnam is an ecologically and economically important watershed, yet it has lacked comprehensive hydrological modelling to date. Characterised by highly complex topography, diverse land use/land cover, and limited hydrometeorological data, the basin presents challenges for water resource assessment and management. This study applies the SWAT hydrological model to simulate streamflow dynamics in the Cau River Basin over a 31-year period (1990–2020) using multiple-source geospatial data, including a 30 m digital elevation model, official soil and land use maps, and daily climate records from six meteorological stations. Model calibration (1997–2008) and validation (2009–2020) were conducted using the SWAT-CUP tool, achieving strong performance with a Nash–Sutcliffe Efficiency (NSE) of 0.95 and 0.90, and R² of 0.95 and 0.91, respectively. Sensitivity analysis identified four key parameters most influential on streamflow (curve number, saturated hydraulic conductivity, soil evaporation compensation factor, and available water capacity), supporting a more focused and effective calibration process. Model results revealed substantial spatio-temporal variability in runoff, with annual surface runoff ranging from 19.8 mm (2011) to 56.4 mm (2013), generally lower in upstream sub-watersheds (<30 mm) and higher in downstream areas (>60 mm). The simulations also showed a clear seasonal contrast between the wet and dry periods. These findings support evidence-based strategies for flood and drought mitigation, inform agricultural and land use planning, and offer a transferable modelling framework for similarly complex watersheds. Full article

Climate change represents one of the main challenges of this century. The hazards generated by this process are various and involve territorial assets all over the globe. Hydrogeological risk represents one of these aspects, and the violence of rain precipitations has led experts to focus their interest on the study of geotechnical assets in relation to these dangerous weather events. At the same time, geospatial representation in 3D WebGIS based on open-source solutions led specialists to employ this kind of technology to remotely analyze and monitor territorial events considering different sources of information. This study considers the construction of a 3D WebGIS framework for the real-time management of geospatial information developed with open-source technologies applied to the dynamic mapping of precipitation in the metropolitan area of Palermo (Italy) based on real-time weather station acquisitions. The structure considered is a WebGIS platform developed with Cesium.js JavaScript libraries, the Postgres database, Geoserver and Mapserver geospatial servers, and the Anaconda Python platform for activating real-time data connections using Python scripts. This framework represents a basic geospatial digital twin structure useful to municipalities, civil protection services, and firefighters for land management and for activating any preventive operations to ensure territorial safety. Furthermore, the open-source nature of the platform favors the free diffusion of this solution, avoiding expensive applications based on property software. The components of the framework are available and shared using GitHub. Full article

An indicator-based approach was implemented to assess the contributions of soils in supplying ecosystem services, providing a scalable tool for modeling the spatial heterogeneity of soil functions at regional and local scales. The method consisted of (i) the definition of soil-based ecosystem services (SESs), using available point data and thematic maps; (ii) the definition of appropriate SES indicators; (iii) the assessment and mapping of potential SESs provision for the Emilia-Romagna region (22.510 km²) in NE Italy. Depending on data availability and on the role played by terrain features and soil geography and its complexity, maps of basic soil characteristics (textural fractions, organic C content, and pH) covering the entire regional territory were produced at a 1 ha resolution using digital soil mapping techniques and geostatistical simulations to explicitly consider spatial variability. Soil physical properties such as bulk density, porosity, and hydraulic conductivity at saturation were derived using pedotransfer functions calibrated using local data and integrated with supplementary information such as land capability and remote sensing indices to derive the inputs for SES assessment. Eight SESs were mapped at 1:50,000 reference scale: buffering capacity, carbon sequestration, erosion control, food provision, biomass provision, water regulation, water storage, and habitat for soil biodiversity. The results are discussed and compared for the different pedolandscapes, identifying clear spatial patterns of soil functions and potential SES supply. Full article