Search Results (295)

Indigenous knowledge and associated indigenous resource management practices are at the root of sustainable land and marine management. Typically, they point to the necessity of maintaining biodiversity and of ensuring the sustenance of social and economic systems, which benefit the well-being of indigenous communities. Conscious of these core attributes, the Government of Indonesia has enabled formal access for indigenous communities to forests for their livelihoods. Nonetheless, meeting the sustainable development goals through such forest management and conservation in Indonesia is threatened by various competing interests and power imbalances. These lead to the disproportionate conversion of naturally vegetated areas, as well as the inability of communities to benefit from economic opportunities. Moreover, the Government of Indonesia has insufficiently regulated the utilisation of indigenous knowledge to conserve the forest areas. This creates a policy design and implementation gap which is not properly understood or addressed. In this conceptual article, we posit that applying cultural space methodology fills the gaps. This methodology combines cultural space and land administration concepts and connects people to land and marine space. This article discusses how and why using the methodology proves to be effective for agricultural and maritime communities in Indonesia and helps to reform the administration capacities of the territories. It identifies and assesses people and land/marine space relationships by the existence of (1) knowledge, practices, and/or objects that represent the relationship, (2) the social, economic, and environmental function of space for the community, and (3) administration of the forest and conservation areas. The methodology also provides a procedure to convert information on the interrelation of the indigenous community, its cultural space in the forest and conservation areas, and indigenous knowledge into geospatial information and data that represent the cultural space unit as a geographic feature. Full article

Platform-mediated short-term rental (STR) markets concentrate intensely in heritage urban cores, yet the temporal stability of this concentration remains poorly understood. This study examines spatial dynamics of STR concentration in Dubrovnik’s UNESCO-listed historic core across five biennial cross-sections (2017–2025) using complete administrative eVisitor registration data and an H3 hexagonal grid at resolution 11. Global and local spatial autocorrelation (Moran’s I, LISA, Getis-Ord Gi*), Emerging Hot Spot Analysis for spatiotemporal typologies, and bivariate LISA to distinguish capacity saturation from fragmentation were applied. Results demonstrate structural persistence: Moran’s I remained highly significant (p < 0.001) across all periods including COVID-19 disruption (range 0.417–0.467, CV = 4.4%), despite 53% supply growth and only 3.7% spatial expansion. Consecutive hotspots dominated typological classification, indicating active consolidation. Capacity analysis revealed concordant High–High patterns (56.8% of significant cells) with zero High–Low associations, confirming saturation not fragmentation. Findings support spatial lock-in in STR markets: concentration persists because locational advantages are properties of place rather than market volume, requiring spatially differentiated regulation rather than aggregate supply controls. Full article

This article argues that there is a “substance” within places that is essential for understanding local space and its spatial processes but remains a research lacuna in human geography. It consists of geographical entities which, through relationships with the place, participate significantly in processes within it, e.g., production of its space, configuring the nature of its space, and transforming the nature of the place. I first address the issue of a geographical entity and its agency that is attributed to it under the posthuman paradigm and how it may be viewed relationally, highlighting commonalities and differences between human geography and sociology, why entitativity does not defy relationality, the nature of relationality of geographical entities, and how it may be studied practically. Three geographical entities with different natures and geographical contexts are illustrated: the spatiality of an urban military base; the nature of a rural space created and transformed by an industrial compound; and the transformed nature of a place by an intentional community. The discussion highlights the merit of geographical entities as significant “substances” for understanding local space and the various issues and questions that surface when engaging with them. The conclusion dwells upon the value of studying geographical entities for human geography and for geography in general. Full article

Coffee production in Peru plays a crucial socio-economic role, supporting over 200,000 families and contributing significantly to export income. However, the spatial variation in coffee farming across ecological and socio-economic regions remains poorly understood. This study examines spatial patterns of coffee farm clustering in three Peruvian mountainous regions (Moyobamba, Tingo María, and Tocache) using descriptive statistics, geospatial visualization, and unsupervised clustering techniques. Farm-level reports and government geospatial records covering 2019–2023 were analyzed to evaluate cultivation area, altitude, and spatial distribution. Kernel density mapping, Moran’s I spatial autocorrelation, and Local Indicators of Spatial Association (LISA) were applied to identify statistically significant clustering patterns, while regression analysis and DBSCAN clustering were used to evaluate spatial trends and production hotspots. Moran’s I indicated moderate spatial clustering (0.34, p < 0.001), while regression analysis showed a weak negative association between altitude and cultivation area (β = −1.144 × 10⁻⁴, adjusted R² = 0.023). Results suggest that measured environmental variables explain only a limited proportion of spatial variation in coffee production, indicating that additional unmeasured factors, potentially including socio-economic influences, may contribute to observed clustering patterns. These findings highlight the value of spatial analysis for understanding production heterogeneity and for supporting regionally adapted agricultural planning strategies. Full article

Access to safe and reliable water resources is one of the most critical global challenges of the twenty-first century. In developing regions, such as Palestine, ensuring adequate water access has become increasingly difficult due to rapid population growth and the intensifying impacts of climate change, which place additional pressure on limited water resources. In this context, alternative water sources, such as rooftop rainwater harvesting (RWH), represent a promising option for enhancing water resilience. This study assesses the impacts of climate change on water resilience in the West Bank by evaluating the future performance of rooftop RWH systems. The potential effects of climate change on optimal storage capacity, system reliability, and deficit ratio are assessed spatially across different West Bank governorates. Monthly rainfall projections for the period 2021–2100 were obtained under three climate change scenarios (SSP126, SSP370, and SSP585). The results indicate that climate change is expected to negatively affect both optimal storage capacity and system reliability, with the most pronounced impacts occurring under the high-emission scenarios. However, the magnitude of these impacts varies spatially among governorates. At the West Bank level, the reliability of the RWH system decreases from 38% to 34% when shifting from the low-emission scenario to the high-emission scenario. Additionally, the optimal storage capacity and the harvested volume will decrease from 65 m³ to 58 m³. This study is the first in this area to use the mass balance approach to predict the future impact of climate risk on the storage capacity of rooftop rainwater harvesting systems. Overall, the findings provide a comprehensive assessment of the feasibility of rooftop RWH as a mitigation and adaptation measure to climate risks and its potential role in enhancing water resilience in the West Bank. This study presents the full framework for assessing the reliability of rainwater harvesting systems under conditions of climate uncertainty. Full article

In Brazil, approximately 16.4 million people (8.1% of the population) live in informal settlements (favelas), with Rio de Janeiro among the most heavily affected. This situation results from rapid rural–urban migration and unplanned urbanization, leading to persistent land tenure conflicts, exemplified by the decades-long struggle in the Santa Luzia favela. This study demonstrates how participatory geospatial methodologies can support land regularization while preventing displacement. Unlike conventional participatory mapping studies that often prioritize community empowerment over technical precision or, conversely, state-led cadastres that prioritize accuracy over local participation, this study integrates two complementary frameworks: counter-cartographies (to redress power asymmetries) and fit-for-purpose land administration (to ensure minimal technical standards for tenure security). Through a university–community collaboration, a low-cost cadastral survey of Santa Luzia was conducted using remotely piloted aircraft photogrammetry to generate high-resolution orthoimagery (2 cm ground sample distance), GIS vectorization integrated with resident interviews and local knowledge, and spatial analysis compliant with local technical standards. The findings demonstrate three specific innovations: (1) methodological: volunteer students and community residents co-produced cartography achieving 2 cm precision, meeting legal requirements for land regularization without expensive professional surveys; (2) participatory: unlike purely community-led mapping that may lack legal enforceability or top-down systems that exclude local knowledge, this model embeds participatory data collection within Brazil’s Social Interest Regularization (REURB-S) framework, ensuring both grassroots legitimacy and state recognition; and (3) policy-making: the project operationalizes counter-cartographies not as symbolic resistance but as a legally compliant pathway to tenure security, offering a transferable model for democratizing land administration in informal settlements while challenging exclusionary urban planning. Full article

Land management is a relevant problem in rural areas all over the world, conditioning the planning decisions and the applicability of planning instruments. This study evaluates the limitations of cadastral data in representing land fragmentation and management patterns in wild-fire-prone landscapes, using Alferce (Portugal) as a case study with broader international relevance. Similar challenges—fragmented ownership, incomplete land registries, and increasing wildfire risk—affect many regions worldwide, particularly across the Mediterranean basin and other fire-prone rural landscapes. A mixed-methods approach combines cadastral data with field data from 23 landowners producing two datasets: cadaster-only and ownership-enhanced. Fragmentation is assessed using Simmons and Januszewki indices, supported by spatial analysis (Kernel Density and Moran’s I). Results show that cadastral data alone significantly overestimates fragmentation. While parcel-based analysis suggests a highly fragmented landscape, incorporating ownership information reveals more aggregated management structures. The 23 landowners manage 1247 ha (≈13% of the area), forming a “keystone” group with strong potential for coordinated land management and fire prevention. Higher fragmentation is associated with population centers. These findings demonstrate that cadastral units do not reflect functional management units and considerations about property fragmentation are biased by the lack of information about the owners, a key theoretical contribution with implications beyond Portugal. For policymakers, integrating ownership data and targeting key land managers can improve land use planning and wildfire mitigation and, overall, the sustainability of the territory. Despite limitations (small sample), the approach is transferable to other regions facing similar structural constraints. Full article

Property taxation serves as a critical instrument for fiscal efficiency and equitable distribution, yet implementation faces significant challenges including valuation inaccuracies, insufficient administrative capacity, and diminished public trust. Indonesia’s Land and Building Tax (PBB-P2) utilizes the Sales Value of Taxable Objects (NJOP) as an administrative proxy for market value, which frequently deviates from actual land prices. These disparities create horizontal inequities, diminish local revenue potential, and generate taxpayer resistance, especially in decentralized regions with constrained technical resources. This research presents the Spatially Adaptive Land Value Determination (SALAD) model as a comprehensive framework for enhancing property tax governance and modernizing fiscal cadastre systems. Unlike conventional mass appraisal methods, SALAD integrates spatial zoning, assessment ratio analysis, land-use characteristics, and the Index of Developing Villages (IDM) with socio-economic indicators including purchasing power and community fiscal behavior. The model incorporates structured social validation to improve public acceptance. Field validation in Lebak Regency employed mixed-methods design with surveys of 75 respondents across 20 villages and interviews with village heads and tax officials. Results demonstrate that transparency, fairness, and visible public benefits are essential for community support. Validation indices vary significantly by IDM category (ANOVA: F = 4.23, p = 0.03 for economic; F = 3.81, p = 0.04 for institutional), confirming that the SALAD model’s adaptive mechanism is empirically grounded. Full article

Road Traffic Accidents (RTAs) represent a significant public safety issue in rapidly urbanising nations, resulting in considerable fatalities, injuries, and economic losses. This research investigates the spatio-temporal distribution and hotspot dynamics of RTAs in Siliguri City, India, a principal transnational transport corridor connecting northeastern India with adjacent countries. A geocoded dataset comprising RTA incidents from 2021 to 2023 was analysed using integrated GIS-based machine learning and statistical methods. Temporal clusters were identified through Kulldorff’s purely temporal scan statistics, while Kernel Density Estimation (KDE) quantified accident density during morning peak, midday/off-peak, evening peak, and lean/night-time intervals. Spatial clustering was further assessed using LISA-Moran’s I, purely spatial scan statistics, and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN). Emerging Hotspot Analysis (EHA) was employed to detect evolving hotspot patterns over time. The findings indicate that major accident hotspots are concentrated at key intersections and transport corridors, such as Hill Cart Road, Darjeeling More, Sevoke Road, Eastern Bypass, and Burdwan Road. Moran’s I (0.157; p = 0.007) demonstrates significant but moderate spatial autocorrelation, and spatial scan statistics identified three principal high-risk zones. HDBSCAN classified 81.90% of incidents within clustered areas. Lean/night-time periods exhibited the highest accident densities, reaching 14.21 accidents/km² at critical intersections. These results underscore the utility of integrating GIS and machine learning techniques for urban traffic safety planning and hotspot-focused intervention strategies. Full article

In multi-hazard environments, women’s social reproductive labor often constitutes a foundation of community survival, yet remains undertheorized in disaster scholarship. This study contributes to an active scholarly conversation by examining Daya Annisa, a women-led grassroots organization in Bantul Regency, Yogyakarta, Indonesia, a region under continuous geological stress from the Sunda Megathrust, the Opak Fault, and Mount Merapi. Drawing on in-depth interviews and focus group discussions analyzed through Social Reproduction Theory (SRT), with a Strengths, Weaknesses, Opportunities, and Threats (SWOT) framework reinterpreted as an analytical lens on the structural conditions of reproductive labor, the analysis traces four interlinked practices: preparedness embedded in arisan and pengajian gatherings, community-based vulnerability mapping, trust-based crisis response, and informal post-disaster livelihoods. The paper argues that resilience in such settings is best understood not as a passive capacity to absorb shocks, but as the active, gendered, and largely uncompensated labor through which communities are materially sustained when formal systems are stretched. Three policy shifts follow: long-term flexible funding calibrated to continuous reproductive preparedness; institutional integration of community-generated vulnerability data with appropriate privacy and inclusion safeguards; and inclusion of grassroots women’s organizations as autonomous decision-making actors in disaster governance. Full article

This study analyzes the spatial distribution of restaurant services in Tanta, Egypt, using a multi-scalar framework that integrates spatial autocorrelation, kernel density estimation, diversity measures, and spatial econometric modeling. It is theoretically grounded in Central Place Theory (CPT) and Central Flow Theory (CFT) to examine how urban hierarchy and mobility dynamics jointly shape food service geography in a mid-sized Global South city. The findings reveal significant spatial inequalities, with nearly half of all restaurants concentrated in a limited number of central neighborhoods, while peripheral areas remain underserved. Spatial regression analysis indicates that these patterns are not adequately explained by population distribution, as total population and density variables showed non-significant effects in the OLS model. Instead, clustering is more strongly associated with accessibility and infrastructure. The transition from OLS to the Spatial Error Model (SEM) significantly improved the explanatory power (R² increased from 0.369 to 0.534), with a highly significant Lambda coefficient (λ = 0.69, p < 0.00001) confirming that unobserved spatial processes and mobility flows are the primary drivers of restaurant concentration. Correlation results further indicate that road density (Coefficient = 2.10, p < 0.01) and educational facilities have significant positive relationships with restaurant density, whereas most demographic indicators show weak effects. Furthermore, a significant negative interaction between population and road density (−2.63, p = 0.014) underscores that mobility corridors can override traditional residential thresholds, providing empirical support for CFT. Diversity analysis highlights clear intra-urban disparities, with high-diversity clusters located along major accessibility axes. Kernel density results point to a hybrid spatial structure, where traditional urban cores coexist with emerging secondary nodes. Overall, the study demonstrates that restaurant distribution in Tanta is better explained through a hybrid CPT–CFT framework, where accessibility and mobility flows outweigh population thresholds. These findings challenge traditional models and emphasize the need for dynamic, accessibility-oriented planning approaches to address spatial inequalities in urban services. Full article

Rapid urbanization highlights the increasing importance of urban green infrastructure in shaping urban spatial organization, quality of life, and environmental sustainability. This study examines spatial inequalities in the provision of urban parks in Sofia (Bulgaria) and Istanbul (Republic of Türkiye) from a comparative urban geography perspective. The two cities are selected as contrasting urban contexts in Southeastern Europe, characterized by different patterns of urban development, population density, and spatial structures. A GIS-based analytical framework is applied at the district administrative level, integrating indicators such as the share of urban parks, park area per capita, Local Moran’s I, and the Gini coefficient. The results reveal distinct spatial patterns: Sofia demonstrates relatively higher levels of park provision but pronounced inequalities, characterized by the concentration of large park areas in a limited number of central districts. In contrast, Istanbul exhibits a more even spatial distribution but significantly lower levels of park area per capita, indicating an overall shortage of urban park space. The findings demonstrate that Sofia and Istanbul experience different forms of spatial disparities in park provision due to distinct trajectories of urban development. Full article

This study aims to investigate the short-term dynamics of agricultural landscapes using AI-supported multi-temporal land use/land cover (LULC) data. The Finike district, located within the Mediterranean climate zone, was selected as the study area, and 10 m spatial resolution ArcGIS Living Atlas LULC raster datasets for the years 2017 and 2024 were used. Spatial dynamics of agricultural areas were analyzed using Fragstats by quantifying changes in area and dominance (CA, PLAND), fragmentation and patch density (NP, PD), spatial integrity and largest patch structure (LPI), shape complexity (PARA_MN), and aggregation–connectivity patterns (CLUMPY, AI), thereby providing a comprehensive assessment of fragmentation, dispersion, clustering, and landscape cohesion over time. The analyses were conducted specifically for the agricultural class for both class-level and landscape-level metrics. The findings indicate that agricultural areas, which covered approximately 3128 hectares in 2017, decreased to 2643 hectares by 2024, as shown in the quantitative results of landscape metrics, accompanied by a pronounced increase in fragmentation. The increase in the number of patches, the decrease in mean patch size, and the rise in patch density demonstrate that the agricultural landscape has transformed into a more fragmented and irregular structure. The results further reveal a weakening of spatial integrity in agricultural areas, suggesting increased pressure from land use change processes, particularly urban expansion, in the study area, and highlighting potential risks for land management, agricultural sustainability, and ecological functions. Overall, the study highlights that the integrated use of high-resolution, AI-supported LULC data and landscape metrics provides a robust and effective framework for monitoring short-term dynamics in agricultural landscapes and supporting evidence-based planning processes. Full article

Urban tourism research has long recognised that understanding cities depends not only on accumulated knowledge but also on the ability to read space, interpret urban form and connect physical settings with cultural meaning. Although these ideas are well established in tourism geography, fewer studies have examined how such skills can be developed through structured learning activities in higher education. This article addresses this gap by analysing the Urban Hunting Game (UHG) as a place-based learning approach designed to strengthen students’ spatial awareness and analytical capacity to interpret urban environments through fieldwork and digital mapping. The UHG was implemented in two European cities, Porto and Kaunas, through distinct pedagogical structures shaped by local conditions. In Porto, students followed a collaborative process using uMap to co-create a single itinerary. In Kaunas, international student groups independently designed thematic routes using MyMaps. This differentiated methodological approach proved advantageous, as it showed how different levels of autonomy and digital engagement influence spatial decisions, interpretive strategies and the narratives that the students construct. Based on student-generated maps and observational notes, the findings show that the UHG enhances spatial literacy, encourages attention to detail and supports the translation of field observation into coherent tourism experiences. This study contributes to tourism geography by illustrating how map-centred, place-based learning methodologies can be adapted to diverse urban contexts and by highlighting their potential to develop interpretive and analytical competences relevant to urban tourism studies. Full article

This study examines the multidimensional nature of poverty and its underlying local determinants within the Suri Sadar Sub-Division of Birbhum District, Eastern India, an area marked by sharp ecological and socio-economic contrasts. Adopting a mixed-method approach, the research integrates primary household survey data (2024-25) with secondary spatial datasets to construct a comprehensive analytical framework. The extent and intensity of multidimensional poverty were measured using the Alkire–Foster (AF) method, while the determinants were identified through a Binary Logistic Regression model. Findings reveal that multidimensional poverty in the region is deeply rooted in the intersection of human, environmental, and spatial factors rather than mere income deprivation. Approximately 26.8 per cent of households were found to be multidimensionally poor, with the western plateau blocks, i.e., Rajnagar, Khoyrasole, and Md. Bazar, showing the highest deprivation levels. Spatial poverty drivers include education, agriculture, and gender equality improvements. Policy implications emphasise the need for geographically tailored, multi-sectoral interventions that focus on human capability, investing in infrastructure, and promoting gender-inclusive development. By elucidating the localized dynamics of poverty, this research contributes to the broader discourse on spatial inequality and sustainable development in rural Eastern India, offering actionable insights for evidence-based regional planning and targeted poverty alleviation. Full article