Search Results (2,011)

This paper examines public architecture in Baghdad during the late nineteenth and early twentieth centuries, focusing on how public buildings contributed to the formation of urban centrality and how this process interacted with local architectural practices. Rather than approaching public construction solely through administrative or ideological frameworks, the study conceptualizes public buildings as structuring components in the reconfiguration of the urban fabric. Methodologically, the research adopts a two-stage, multi-scalar approach. First, public buildings in Beirut, Damascus, and Baghdad are identified and comparatively analyzed using QGIS-based spatial analysis, employing Kernel Density Estimation and DBSCAN clustering to examine patterns of spatial concentration, distribution, and relationships with major urban axes. This comparative stage establishes a comparative spatial framework for understanding urban centrality in provincial capitals. In the second stage, Baghdad is examined as a focused case study through building-scale architectural analysis, incorporating plan organization, construction techniques, material use, and environmental adaptation based on archival documents, historical maps, and visual sources. The results indicate that public buildings in Baghdad were not isolated institutional entities but integral components in the formation of new urban focal areas structured along river-oriented and infrastructural axes. Architecturally, these buildings exhibit a hybrid character, combining standardized public building programs with locally embedded materials, construction methods, and spatial adaptations. The study concludes that public architecture in late Ottoman Baghdad emerged through a negotiated process between centralized planning principles and local architectural knowledge, producing a distinct yet contextually grounded form of urban centrality. Full article

The potential accessibility has been widely represented in the scientific literature since the 1950s and in the work of Hansen. Until today, different sets of measures have been developed for evaluating it in different scientific areas such as transport infrastructure, land use planning, regional development, and others. In the Serbian scientific literature, this concept received limited attention, so this paper represents a new contribution to the field of managing territorial development within spatial planning. The main aim of this research is to view the sustainable territorial development of the Republic of Serbia from a new perspective, which combines demographic and socioeconomic indicators with infrastructure development. Considering that, the potential accessibility to the population of local self-government centers index was calculated at the settlement level. This approach corresponds with demographic and economic trends in Serbia that are present in recent decades and some newer analyses in the scientific and professional literature regarding processes within the Serbian urban system. Findings from this research can make a significant contribution to further understanding of Serbian urban system patterns and sustainable territorial development. Full article

Timber price dynamics are most often analysed using trends, seasonality, and classical measures of volatility, which describe the magnitude of fluctuations but only to a limited extent capture the temporal structure of the price-generating process. The aim of this study is to identify the structural complexity and long-term memory of quarterly prices of WC0 pine timber in the regional timber market in Poland. The analysis is based on nominal net prices (PLN/m³) from 16 forest districts of the Regional Directorate of State Forests in Kraków over the period 2005–2024, with reference to nationally averaged timber prices. Long-term dependence is assessed using the Hurst exponent estimated by detrended fluctuation analysis (DFA) applied to log returns, while the geometric complexity of price trajectories is characterised by the fractal dimension and additionally validated using the Higuchi estimator. Cross-sectional results reveal substantial spatial heterogeneity in scaling properties, indicating the coexistence of persistent (trend-following) and corrective (anti-persistent) dynamics across forest districts. Rolling-window analysis (40 quarters) demonstrates temporal variability in price dynamics, with particularly pronounced shifts observed in 2019–2021. Cluster analysis based on time-varying Hurst exponent values identifies two groups of forest districts with distinct persistence trajectories, corresponding to more trend-dominated and corrective price dynamics. In contrast, national-level prices generally exhibit higher persistence than local prices, reflecting the effects of price aggregation. Overall, the results show that fractal analysis uncovers persistent spatial and temporal differences in timber price structures that remain invisible when relying solely on variance-based measures, with direct implications for the choice of planning horizons and timber sale strategies in regional markets. Full article

Precise segmentation of brain tumors from multimodal MRI scans is essential for accurate neuro-oncological diagnosis and treatment planning. To address this challenge, we propose a label-free optimization-driven segmentation framework based on the $\alpha$-expansion graph cut algorithm, offering improved computational efficiency and interpretability compared to deep learning alternatives. The method relies on structured optimization and handcrafted features, including local intensity patches, entropy-based texture descriptors, and statistical moments, to compute voxel-wise unary potentials via gradient-boosted decision trees (XGBoost). These are integrated with spatially adaptive pairwise terms within a graph model optimized through $\alpha$-expansion. Evaluation on 146 BraTS validation volumes demonstrates reliable whole-tumor overlap, with a mean Dice score of 0.855 ± 0.184 and a 95% Hausdorff distance of 18.66 mm. Bootstrap analysis confirms the statistical stability of these results. The low computational overhead and modular design make the method particularly suitable for transparent and resource-constrained clinical deployment scenarios. Full article

Unmanned Aerial Vehicle imagery often suffers from severe spatial detail degradation due to sensor limitations and motion blur, hindering downstream vision tasks. To address this, we propose a lightweight super-resolution framework leveraging a Tiny-Transformer backbone enhanced by a multi-domain feature fusion strategy. Specifically, we jointly model spatial structural semantics and frequency domain texture priors via a cross-domain fusion attention mechanism, enabling coordinated restoration of global consistency and local details. Extensive experiments demonstrate that our method outperforms state-of-the-art approaches on standard benchmarks, achieving significant gains in Peak Signal-to-Noise Ratio and structural similarity index while maintaining low computational cost. Notably, the model exhibits superior robustness in reconstructing high-frequency textures common in aerial scenes. This work provides an efficient, deployable solution for enhancing visual fidelity in resource-constrained applications such as urban planning and precision agriculture. Full article

Urban areas require context-specific bioenergy solutions to advance toward circular and sustainable energy systems. In Bogotá, urban pruning and grass-cutting residues constitute a relatively stable biomass stream; however, the absence of district-scale valorization infrastructure leads to their direct disposal in landfill. This study develops and applies a GIS-based planning methodology to support the territorial design of a small-scale anaerobic digestion plant using urban green waste. In this study, “small-scale” is understood as an early-stage urban facility concept compatible with the available pruning stream of approximately 1200–1300 t/month of valorizable biomass, corresponding only to an order-of-magnitude energy range of a few hundred kW_e/kW_t, rather than to a final engineering design. The approach integrates official geospatial data with logistical, environmental, and institutional criteria to characterize biomass availability and evaluate location alternatives under real urban constraints. A continuous location model based on the Weber problem is first applied to estimate a theoretical lower bound of spatial effort, using public schools weighted by enrollment as a proxy for sensitive urban demand. Subsequently, a GIS-assisted Analytic Hierarchy Process (AHP) is implemented to incorporate environmental exclusions, territorial compatibility, and the operational structure of exclusive waste service areas. Results show that the optimal geometric location diverges from the territorially feasible alternative once environmental restrictions and biomass supply coherence are explicitly considered. The findings highlight that urban bioenergy infrastructure planning is governed less by pure spatial efficiency than by the integration of supply, demand, and institutional constraints. The proposed methodology provides a reproducible decision-support tool for urban bioenergy planning and contributes to sustainable waste management, circular economy strategies, and local energy resilience in cities of the Global South. Full article

A comprehensive characterization of the wave climate on the coast at Manzanillo, Colima, Mexico, based on an 11-year hindcast (2008–2018), was performed using a hybrid approach that integrates hydrodynamic numerical models with machine learning techniques. Wave conditions were analyzed at 23 nearshore sites, including headlands, outer beaches, and sheltered beaches. The effects of the complex coastal morphology on wave propagation were evident, especially regarding storm waves. Two distinct wave climates were seen: a low-energy regime in the dry season (November–April) and a more energetic regime in the rainy season (May–October). Spatial variability was greatly modulated by headlands, bays, and port infrastructure, leading to sharp local contrasts in wave height, slope, and wave power. For instance, mean wave power ranged from 9.34 kW/m at exposed sites such as El Faro de Campos to only 0.36 kW/m near sheltered areas, such as San Pedrito beach. From these findings, it is clear that a regional scale description of the wave climate is insufficient when assessing coastal vulnerability in this morphologically complex area. The new dataset is a valuable baseline for use in coastal management, port planning, and risk assessments for Manzanillo, which is one of Mexico’s most important ports. Full article

Vehicle detection is a core task in smart city perception management and an important technical support for sustainable urban development and intelligent transportation optimization. In high-resolution unmanned aerial vehicle (UAV) remote sensing images, it faces challenges such as variable target scales, severe occlusion, and difficulty in modeling long-range dependencies. To address these issues, this study proposes the MCViM-YOLO algorithm, which integrates the local perception advantage of convolution with the global modeling capability of the state space model (Mamba). Based on YOLOv12, the algorithm reconstructs the neck network: it introduces the Mix-Mamba module (parallel multi-scale convolution and selective state space model) to simultaneously capture local details and global spatial dependencies, adopts the dual-factor calibration fusion module (DCFM) to adaptively fuse heterogeneous features, and employs a dual-branch attention detection head (DADH) to optimize the prediction of difficult samples (e.g., occluded, small-scale vehicles). Experiments on the VEBAI dataset demonstrate that our proposed model achieves an mAP@0.5 of 92.391% and a recall rate of 86.070%, with a computational complexity of 10.41 GFLOPs. The results show that the proposed method effectively improves the accuracy and efficiency of vehicle detection in complex remote sensing scenarios, provides technical support for traffic flow monitoring, low-carbon urban planning, and other sustainable applications, and offers an innovative paradigm for the deep integration of CNN and state space models with both theoretical research value and engineering application prospects. Full article

In the face of intensifying climate disruptions, coastal landscapes like Necoclí in Colombia’s Department of Antioquia are sites of both vulnerability and resilience. This paper examines how thick mapping acts as a methodology for decentralized spatial planning and a practice of revolutionary care by amplifying youth voices and fostering situated climate adaptation. Drawing from a participatory mapping process co-developed with young people, we reflect on how community-based approaches can trigger territorial restructuring from the bottom up. Through storytelling, visual documentation, and collective drawing, the mapping process brought to light lived experiences and local ecological knowledge that are often excluded from technocratic spatial integration strategies. These thick maps function as tools for sub-local territorial agency, allowing youth to reconnect with their landscapes while providing municipal administrations with the granular data needed for equitable spatial development. The paper explores how this form of mapping challenges top-down adaptation narratives and enables more inclusive planning for just futures by centering the territorial dimensions of climate risk. Our findings reveal a profound divergence in territorial perception: while older settlers maintain a narrative of loss tied to a lush, forested past, children’s drawings expose an internalized ecological thinning, characterized by the absence of native flora and the threatening proximity of a rising sea. Ultimately, this study demonstrates how thick mapping contributes to socio-ecological transitioning by bridging the gap between national climate policies and the spatial expression of local needs in frontline communities. Full article

The revitalization of vitality in historic cultural districts can enhance a city’s cultural attractiveness and promote the upgrading of the urban cultural industry and sustainable development. Revealing the threshold and synergistic effects of different districts’ scene elements on district vitality helps to identify the distribution patterns of district vitality and provides a basis for managerial decision-making. This study first uses a geographic information system (ArcGIS) to overlay Baidu heatmaps with the street-network distribution in order to depict the spatiotemporal heterogeneity of district vitality and to compute vitality values by partitions at the district scale. Subsequently, based on an explanatory framework that integrates the physical space and subjective cognition, multi-source data such as street-view panoramas and points of interest (POIs) are quantified to obtain scene-element values for each unit area. Then, the scene-element values and vitality values are integrated into a consolidated database. Additionally, the LightGBM model and the SHAP method are employed to evaluate each element’s marginal contribution and relative importance to district vitality, thereby screening out the key scene elements. Finally, by means of SHAP dependence plots and interaction-effect analysis, the threshold intervals of the key elements and their synergistic relationships are identified, revealing the nonlinear threshold effects and synergies by which scene elements influence spatial vitality. The results show that during rest days, district vitality exhibits stronger diffusion, and the synergistic effect between Leisure-Facility Attractiveness and Street-Network Accessibility is the most prominent in enhancing vitality. High Exhibition-Facility Attractiveness is difficult to sustain crowds on its own; only when Leisure-Facility Attractiveness is likewise high does its effectiveness increase significantly. When Transport Accessibility is within the 0.20–0.40 interval, the positive effect of Leisure-Facility Attractiveness is significantly amplified. An excessive Traditional–Modern Facility Mix readily leads to homogenization of districts; therefore, when introducing modern business formats, local cultural characteristics must be retained. Overall, the generation of district vitality relies more on the synergy between material factors and subjective cognition than on improvements to any single element. The findings of this study provide suggestions for the planning of scene elements and the enhancement of vitality in historic cultural districts. Full article

High-precision sediment distribution maps are indispensable for nearshore sediment dynamics and ecology and nearshore resource management. Using grain-size data of surface sediments from the nearshore waters of Lianyungang and auxiliary datasets including bathymetric and hydrodynamic conditions, this study assessed Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Support Vector Regression (SVR) for predicting sediment grain-size fractions and mapping sediment substrate types. All three models capture the spatial gradient of sediment grain size from fine to coarse from the nearshore to the offshore regions, but differ in preserving local heterogeneity and defining transition boundaries: XGBoost delivers the most balanced performance by preserving grain-size variability, reducing boundary mixing, and improving the identification of classes with limited samples; RF excels in robust delineation of gradual transitions, whereas SVR tends to produce fragmented boundaries and unstable performance for classes with limited samples. Feature importance reveals that hydrodynamic drivers dominate the spatial distribution of sand, whereas terrain indices are more influential for the clay distribution pattern, confirming the role of microtopography in modulating fine-sediment trapping. Overall, this study improves mapping accuracy and supports marine spatial planning and coastal infrastructure design. Full article

Studies of vocal communication often focus on the messages that calls and songs convey related to reproductive activities, foraging, predator avoidance, social bonding, individual recognition, and conflict resolution. We consider ways in which vocalizations may dynamically mediate social interactions at a more basic level, through collective coordination of movements and the enhancement of spatial perception. From this perspective, animals may vocalize to probe the locations, movements, and intentions of others, to manipulate position changes by listeners, or to increase their own capacity to localize sounds. An animal’s capacity to flexibly adjust vocalizations, both in real-time and over longer periods, can increase their ability to monitor and influence conspecifics independently of any information that may be encoded within those vocalizations. Beyond simply conveying messages, reproductive fitness, or emotional states, an animal’s ability to modulate vocalizations may dynamically affect its future action plans and social roles within a group. Identifying situational, life-history, and sociospatial factors that determine how animals vocally interact in real-time is key to understanding how an animal’s vocalizations relate to its own actions and the actions of others. Full article

Human engineering activity, such as cross-regional transportation construction, often disturbs the geological environment and triggers landslides. This study investigated a landslide induced by tunnel excavation in the northeastern region of the Qinghai–Tibet Plateau, exploring how a seemingly low-risk local small-scale landslide can trigger an engineering disaster. Based on field geological and geomorphological surveys, unmanned aerial vehicle (UAV) remote sensing photography, and SBAS-InSAR data analysis (time-series monitoring from 2021 to 2023), the spatiotemporal evolution patterns and causative mechanisms of landslide deformation were systematically elucidated. The results indicate the following: (1) The landslide evolved from initial multiple small local slides, gradually expanding and connecting to form a larger and deep-seated landslide. (2) SBAS-InSAR analysis revealed that the landslide deformation rate ranged from −38.13 to 12.01 mm/a, with a maximum cumulative deformation of 121.91 mm. Substantial deformation was concentrated in April–June 2021, June–August 2022, and April–July 2023. Spatially, the deformation intensity exhibited a pattern of middle section > front > rear, with greater deformation closer to the tunnel construction point. (3) The landslide deformation is primarily related to tunnel construction disturbance. The topography, geological structure, and frozen ground thawing exerted certain influences. The deformation mechanism is summarized as follows: Slope toe excavation initially triggers local sliding, leading to tension cracking at the rear edge. Subsequently, tunnel construction further promotes landslide expansion, resulting in the formation of a deep-seated landslide. This study showed that the landslide resulted from the combined effects of engineering activity and natural conditions. The results reveal that, under disturbances from inappropriate engineering activities, local small landslides may develop into major disasters. Therefore, the construction plan for the tunnel must be revised to mitigate such risks. Full article

This study examines near-surface air-temperature variability during extreme heatwaves in Coimbra (Portugal), focusing on Urban Heat Island (UHI) dynamics through a hotspot-based assessment of intra-urban thermal hotspots (IUTHs), defined as localized zones of recurrent elevated near-surface temperatures. Using an extensive multi-site dataset collected at multiple times of the day across heterogeneous urban environments, the analysis evaluates how urbanization intensity, surface cover, green infrastructure, and site-specific context influence diurnal temperature contrasts and patterns of heat exposure. Statistical results reveal clear spatial thermal disparities, with densely built-up and highly impervious areas such as Santana and the Seminary surroundings consistently emerging as intra-urban hotspots, particularly during afternoon peak temperatures. In contrast, green spaces (Botanical Garden and Mermaid Garden) act as cooling refugia, exhibiting lower near-surface air temperatures and reduced thermal amplitude compared with surrounding urban areas. Proximity to water bodies further moderates ambient conditions, highlighting the buffering role of blue infrastructure during extreme heat periods. These findings demonstrate that analysing UHI intensity through fine-scale intra-urban hotspot patterns provides valuable insights for urban climate adaptation. The results support the strategic integration of green spaces and nature-based solutions in urban planning to mitigate heat risk, strengthen climate resilience, safeguard public well-being, and promote more adaptive and liveable cities. Full article

Arctic regions are experiencing accelerated environmental change, yet integrated assessments of terrain-scale responses remain limited. This study quantifies the spatial-temporal variability of glaciers, shorelines, and outwash plains in Kaffiøyra, Svalbard, Norway, over four decades (1985–2023) using cross-evaluated Landsat and Sentinel imagery. Our results reveal systematic retreat across all eight glaciers (R² = 0.83–0.96), with tidewater glaciers experiencing substantially greater terminus area loss (62.8% and 72.1%) compared to land-terminating glaciers (34.5–69.0%). Coastal changes were highly variable: erosion (up to −3.2 m/yr) was most pronounced on shores exposed to southwesterly summer waves, while significant accretion (+13.0 m/yr) occurred near the tidewater glacier terminus. The insignificant outwash changes (−6.4% to +2.7%) despite substantial land-terminating glacier retreat indicate these systems respond to different controls. A moderate negative correlation between glacier terminus area and summer temperatures (r = −0.55 to −0.69) enabled a simple projection model. Diagnostic projections to 2020–2039 showed that both downscaled climate models and extrapolated local data overestimated retreat. However, extrapolated local data proved more accurate, with its projection gap averaging 11% for land-terminating and 46% for tidewater glaciers. The study provides crucial insights into Arctic terrain behaviors, highlighting complex and divergent responses. These findings emphasize the need for enhanced localized monitoring systems through ongoing high-resolution image surveys and planned modeling to understand accelerating polar environmental changes. Full article