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Keywords = spatial distribution

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30 pages, 11808 KB  
Article
Evolutionary Characteristics and Dynamic Mechanism of the Global Transportation Carbon Emission Spatial Correlation Network
by Yi Liang, Han Liu, Zhaoge Wu, Xiaoduo Wang and Zhaoxu Yuan
ISPRS Int. J. Geo-Inf. 2026, 15(2), 89; https://doi.org/10.3390/ijgi15020089 (registering DOI) - 19 Feb 2026
Abstract
This study constructs a global transportation carbon emission spatial correlation network via a modified gravity model and explores its evolutionary characteristics and dynamic mechanisms by integrating three-dimensional evolutionary analysis (node, overall, structural) and temporal exponential random graph model (TERGM). The main findings are [...] Read more.
This study constructs a global transportation carbon emission spatial correlation network via a modified gravity model and explores its evolutionary characteristics and dynamic mechanisms by integrating three-dimensional evolutionary analysis (node, overall, structural) and temporal exponential random graph model (TERGM). The main findings are as follows: (1) Global transportation carbon emission spatial correlation intensity keeps rising, with improved connectivity and integration, forming three regionally agglomerated correlation poles centered on the United States (America), China (Asia) and major European countries (Europe). (2) Network centrality distributes asymmetrically: Switzerland, Norway and the United States remain core nodes, while China, Japan and other Asian economies with strong direct correlation radiation are not in the core tier. (3) Third, evolutionary dynamics stem from the synergistic interaction of multidimensional attributes. ① Economic level positively drives bidirectional connection emission and attraction; economic scale and openness curb emission but boost attraction, while tertiary industry structure inhibits both. ② Only economic level and government efficiency exert significant positive effects on absdiff, fostering network heterophilic attraction. ③ Spatial and institutional proximity in edgecov effectively facilitate connection formation. ④ Endogenous network variables present a collaborative mechanism of reciprocity and transmission, constrained by network density. ⑤ Temporal effects show early connection structure forms path dependence, resulting in low dynamic variability and overall network stability. Full article
(This article belongs to the Special Issue Spatial Data Science and Knowledge Discovery)
16 pages, 3300 KB  
Article
Maritime-Oriented Analysis of Heat Transfer Enhancement in Jeffrey Nanofluid Flow over a Stretching Sheet Embedded in a Porous Medium
by Nourhan I. Ghoneim, A. M. Amer, Seyed Behbood Issa-Zadeh and Ahmed M. Megahed
Eng 2026, 7(2), 98; https://doi.org/10.3390/eng7020098 (registering DOI) - 19 Feb 2026
Abstract
This study numerically investigates the hydrothermal behaviour of a Jeffrey nanofluid with relevance to maritime thermal systems. The coupled nonlinear governing equations for momentum, heat, and mass transport are solved using a shooting technique that accounts for magnetohydrodynamic effects, Darcy porous-media resistance, viscous [...] Read more.
This study numerically investigates the hydrothermal behaviour of a Jeffrey nanofluid with relevance to maritime thermal systems. The coupled nonlinear governing equations for momentum, heat, and mass transport are solved using a shooting technique that accounts for magnetohydrodynamic effects, Darcy porous-media resistance, viscous dissipation, and spatially varying internal heat generation. Variable thermophysical properties, including temperature-dependent viscosity and density, are also considered. The results reveal that porous resistance, fluid elasticity, and thermophysical variations significantly influence velocity, temperature, and concentration fields. The combined effects of porous drag and variable properties markedly alter the characteristics of heat and mass transfer. These findings provide insights into thermal and mass-transport performance, including skin friction, heat transfer, and concentration distributions, which are critical metrics for porous heat exchangers and nanofluid-based maritime coatings. Here, maritime relevance is represented via a generalised porous nanofluid model rather than a specific material. Among the key findings, increasing the slip velocity factor can reduce the surface skin-friction coefficient by approximately 48.7%, while the heat-transfer rate increases by nearly 27.1%, accompanied by a decrease of about 18.9% in the Sherwood number. Conversely, raising the density factor enhances the skin friction coefficient by roughly 103.8% and also augments the heat and mass transfer rates by about 61.3% and 106.1%, respectively. Likewise, at zero relaxation–retardation ratio, the flow reduces to the Newtonian case. Increasing this factor reduces the local Nusselt number by about 1.45%, indicating a slight weakening of heat transfer due to elastic effects. Furthermore, the reliability of the current numerical framework is established through a dual-validation approach, including an analytical assessment of limiting cases and a rigorous comparison with established data from the literature. Full article
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23 pages, 3258 KB  
Article
Invisible Footprints: Exploring Microplastic Pollution in the Colombian Caribbean Sea
by René A. Rojas-Luna, Jonathan D. Ayala-Rodríguez, Carlos A. García-Alzate, Roberto García-Alzate, Jorge Trilleras, Jairo Humberto Medina-Calderon, Adriana Santos-Martínez, José Ernesto Mancera Pineda, Cesar A. Sierra and Victoria A. Arana
Water 2026, 18(4), 508; https://doi.org/10.3390/w18040508 - 19 Feb 2026
Abstract
Microplastic (MP) pollution poses a significant and emerging threat to global marine ecosystems; however, regional data for the Caribbean remain limited. This study presents a spatial and temporal characterization of MPs in surface and mid-waters of the Colombian Caribbean (Atlántico and Magdalena departments), [...] Read more.
Microplastic (MP) pollution poses a significant and emerging threat to global marine ecosystems; however, regional data for the Caribbean remain limited. This study presents a spatial and temporal characterization of MPs in surface and mid-waters of the Colombian Caribbean (Atlántico and Magdalena departments), which were analyzed as independent compartments due to methodological differences in sampling strategies. Sixteen sampling stations were established across two anthropogenic influence zones: Zone 1 (nearshore/bather zone) and Zone 2 (offshore). MPs were quantified and characterized according to shape, color, size, and polymer composition using attenuated total reflectance Fourier transform infrared microspectroscopy (µATR-FTIR) and multivariate techniques. MPs were detected in 100% of samples. Surface water MP abundance was higher in Magdalena (4.5 MPs m−3) than in Atlántico (1.7 MPs m−3). Mid-water MP concentrations reached maximum values during the high rainfall season in Atlántico, reflecting localized hydrological and anthropogenic influences rather than vertical gradients. Higher concentrations were generally observed in the nearshore Zone 1 compared to offshore Zone 2, although these differences were not consistently statistically significant. Fibers and fragments were the predominant shapes, and synthetic–natural polymer blends, polyethylene terephthalate (PET), polypropylene (PP), and polyacrylic acid (PAA) were the most prevalent. Generalized Additive Models (GAM) indicated that strong fluvial inputs and proximity to urban and riverine sources were factors driving MP distribution. Additionally, the detection of polymers reported in the literature as rare and high-risk, such as acrylonitrile butadiene styrene (ABS), acrylonitrile styrene acrylate (ASA), styrene–ethylene–butylene–styrene (SEBS), and polyvinyl stearate (PVS), highlights the complexity of MP sources in the region. Overall, these results provide the first spatial and temporal characterization of MPs in the surface and mid-water of the Colombian Caribbean and identify critical contamination hotspots that warrant targeted mitigation strategies. Full article
(This article belongs to the Special Issue Microplastics and Microfiber Pollution in Aquatic Environments)
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21 pages, 11756 KB  
Article
An Integrated Diagnostic Approach to Deepen the Understanding of Michele di Matteo’s Wooden Panel Coronation of the Virgin
by Valeria Comite, Chiara Andrea Lombardi, Andrea Bergomi, Alfonsina D’Amato, Mattia Borelli, Gianluca Carabelli, Valentina Verzoni, Mario Colella, Daniele Bolleri, Vittoria Guglielmi and Paola Fermo
Heritage 2026, 9(2), 80; https://doi.org/10.3390/heritage9020080 - 19 Feb 2026
Abstract
This study presents a non-invasive, integrated and multidisciplinary diagnostic approach applied to the analysis of the altarpiece Coronation of the Virgin, attributed to Michele di Matteo (15th century). The investigation focused on the evaluation of a restoration intervention carried out in 2023 [...] Read more.
This study presents a non-invasive, integrated and multidisciplinary diagnostic approach applied to the analysis of the altarpiece Coronation of the Virgin, attributed to Michele di Matteo (15th century). The investigation focused on the evaluation of a restoration intervention carried out in 2023 using quantitative colorimetric measurements to assess chromatic variations induced by surface treatments. Other non-invasive techniques, including multispectral imaging, hyperspectral imaging, Raman spectroscopy, and visible reflectance spectroscopy, were employed to investigate the painted surface, examine underlying features, and support the characterization and spatial distribution of pictorial materials through comparison with reference standards. Finally, the proteinaceous binding media used by the artist were investigated using nano-liquid chromatography coupled with tandem mass spectrometry (nLC-MS/MS), a sensitive, high-resolution analytical approach in the field of cultural heritage studies. Overall, the integrated approach documented chromatic changes induced by cleaning, revealed the preparatory drawing and previously unknown decorative elements by infrared reflectography, and confirmed the presence of pigments previously identified in earlier studies, allowing, in some cases, for an investigation of their distribution across the painted surface. The characterization of proteinaceous binding media further contributed to a deeper understanding of the materials and techniques employed by the artist. Full article
(This article belongs to the Section Cultural Heritage)
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22 pages, 4044 KB  
Article
Research on the Spatial Sequence of Building Facades in Historic Towns in the Chengdu Plain Region of China
by Yixiao He and Bin Cheng
Buildings 2026, 16(4), 838; https://doi.org/10.3390/buildings16040838 - 19 Feb 2026
Abstract
Historic towns serve as vital carriers of both tangible and intangible cultural heritage, preserving unique historical memories. Quantitative analysis of their architectural facades is crucial for scientific conservation and cultural continuity. While existing studies predominantly employ qualitative descriptions or small-sample analyses, a systematic [...] Read more.
Historic towns serve as vital carriers of both tangible and intangible cultural heritage, preserving unique historical memories. Quantitative analysis of their architectural facades is crucial for scientific conservation and cultural continuity. While existing studies predominantly employ qualitative descriptions or small-sample analyses, a systematic and replicable quantitative methodology remains elusive. To address this gap, this study innovatively proposes an integrated framework combining UAV oblique photogrammetric modeling, multivariate statistics, and spatial time series analysis. This framework aims to establish a methodological system for analyzing the morphological characteristics of building facades in historic districts. The study selected main streets from four ancient towns in the Chengdu Plain—Pingle, Anren, Xinchang, and Yuantong—and performed 3D reconstruction and morphological indicator extraction on 365 contiguous facade samples. Factor analysis was employed to reduce dimensionality, identifying three dimensions influencing facade morphology. Combined with cluster analysis for classification, the study systematically categorized four statistically significant and architecturally meaningful facade types. Furthermore, it quantified the sequential patterns and combination modes of street-facing distributions, providing crucial theoretical support and reference for the preservation, renewal, and sustainable development of ancient towns. Full article
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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29 pages, 10399 KB  
Article
Analysis of Internal Mechanical Friction Losses Influence on the Francis-99 Runner Using the Friction Torque Approach
by Otibh M. M. Abubkry, Yun Zeng, Juan Duan, Altyib Abdallah Mahmoud Ahmed, Hassan Babeker and Altyeb Ali Abaker Omer
Computation 2026, 14(2), 53; https://doi.org/10.3390/computation14020053 - 19 Feb 2026
Abstract
Francis turbines are renowned for their high efficiency and adaptability across a wide range of head and discharge conditions. However, internal mechanical friction losses (IMFLs), resulting from rotational frictional resistance between the rotating runner and the surrounding fluid, remain a significant obstacle to [...] Read more.
Francis turbines are renowned for their high efficiency and adaptability across a wide range of head and discharge conditions. However, internal mechanical friction losses (IMFLs), resulting from rotational frictional resistance between the rotating runner and the surrounding fluid, remain a significant obstacle to further performance optimisation. This study introduced a CFD-derived integral friction torque framework, validated through theoretical analysis, that enables the spatially resolved quantification of IMFLs in Francis turbine runners. Building on this framework, a comprehensive computational approach was established to quantify IMFLs in a Francis turbine runner using a CFD-derived integral torque method combined with a theoretical verification model. Three runner configurations were analysed: the original runner model (ORM), a modified runner (RM1) with selective exit height reduction, and a modified runner (RM2) with uniform exit height reduction. Transient simulations were conducted at the best efficiency point (BEP) using the shear stress transport (SST) k–ω turbulence model and a sliding mesh approach. The numerical results were verified using the theoretical model and systematically evaluated to assess IMFL mechanisms and runner performance. The findings demonstrate that variations in runner geometry significantly influence internal frictional resistance and turbine efficiency. Compared with ORM, both RM1 and RM2 reduced the rotational friction torque, with RM2 exhibiting the greatest improvement: a 2.83% reduction in total friction resistance torque, a 14.74% reduction in total power losses, and a 1% absolute increase in efficiency. These improvements are primarily attributed to reduced wall shear stress and a more uniform pressure distribution across the runner surface. Full article
(This article belongs to the Section Computational Engineering)
26 pages, 12208 KB  
Article
Classification of the Surrounding Rock Based on Image Processing Analysis and Transfer Learning
by Yanyun Fan, Jiaqi Zhu, Hua Luo, Yaxi Shen, Shuanglong Wang, Xiaoning Liu, Dong Li and Chuhan Deng
J. Imaging 2026, 12(2), 89; https://doi.org/10.3390/jimaging12020089 - 19 Feb 2026
Abstract
Currently, standardized classification methods of surrounding rock are relatively insufficient. The classification of surrounding rock mainly relies on the subjective judgment of technicians, leading to diverse evaluation results. This study focuses on the feature extraction and classification methods of surrounding rock images in [...] Read more.
Currently, standardized classification methods of surrounding rock are relatively insufficient. The classification of surrounding rock mainly relies on the subjective judgment of technicians, leading to diverse evaluation results. This study focuses on the feature extraction and classification methods of surrounding rock images in a certain tunnel of the Central Yunnan Water Diversion Project by using image processing analysis and transfer learning. Rich surrounding rock images and the water conservancy tunnel data are collected, and then the surrounding rock is classified relatively accurately according to the code and expert guidance. By introducing the fractal theory, the complexity and irregularity of the spatial distribution of weak layers and joints on the surrounding rock surface are revealed effectively. Based on the analysis of changes in fractal dimension characteristic values, a classification method for surrounding rock based on the fractal theory is proposed. Combined with the quantified parameters of surrounding rock images and the strength data collected by rebound meters, a method for correcting the surrounding rock strength based on image analysis is proposed, which can effectively solve the error caused by the uneven distribution of rock masses in the traditional rebound meter strength values. After correction, more accurate strength characteristics can be obtained, which is conducive to the standardized classification of the surrounding rock. After studying the recognition of tunnel surrounding rock images with transfer learning, a model is constructed to achieve rapid classification of tunnel surrounding rock. This research provides support for the standardized classification of tunnel surrounding rock. Full article
(This article belongs to the Section Image and Video Processing)
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17 pages, 3604 KB  
Article
The Proximity of PD-1CD103+ Tissue-Resident CD8+ T Cells to Tumor Cells Is Correlated with Improved Clinical Outcomes in Patients with Cholangiocarcinoma
by Zhenyu Li, Danping Liu, Jingjing He, Junrui Ma, Muyuan He, Xiaobao Yang, Yanan Zhao, Xuefeng Fei, Dakang Xu and Mengjie Deng
Cancers 2026, 18(4), 680; https://doi.org/10.3390/cancers18040680 - 19 Feb 2026
Abstract
Background/Objectives: Cholangiocarcinoma (CCA) is characterized by a heterogeneous immune microenvironment, where the prognostic significance of CD8+ tissue-resident memory T (TRM) cell activation and spatial positioning remains to be fully elucidated. This study investigated how the activation phenotypes and their spatial [...] Read more.
Background/Objectives: Cholangiocarcinoma (CCA) is characterized by a heterogeneous immune microenvironment, where the prognostic significance of CD8+ tissue-resident memory T (TRM) cell activation and spatial positioning remains to be fully elucidated. This study investigated how the activation phenotypes and their spatial distribution relative to tumor cells influence anti-tumor immunosurveillance and predict clinical outcomes in CCA. Methods: Multiplex immunohistochemistry (mIHC) and single-cell RNA sequencing (scRNA-seq) were employed to characterize naïve (PD-1CD103+CD8+) and exhausted (PD-1+CD103+CD8+) subsets. G-cross function analysis was utilized to quantify the spatial proximity between these specific TRM subsets and tumor cells, correlating the spatial interaction with patient overall survival. Results: scRNA-seq profiling revealed that PD-1CD103+CD8+ TRM cells were enriched in genes associated with lymphocyte activation and cytotoxicity, while PD-1+CD103+CD8+ TRM cells exhibited an exhaustion signature. Spatially, PD-1CD103+CD8+ TRM cells exhibited increased interactions with tumor cells, whereas PD-1+CD103+CD8+ TRM cells showed reduced engagement. Therefore, the close proximity of PD-1CD103+CD8+ TRM cells to tumor cells was identified as a significant predictor of favorable clinical outcomes. Conclusions: The activation state of CD8+ TRM cells combined with their spatial localization constitutes a critical prognostic factor in CCA. Effective anti-tumor immunosurveillance relies on the direct engagement of naïve TRM cells with tumor cells. These findings highlight the potential of PD-1-targeted immunotherapies to remodel the spatial proximity of the tumor microenvironment, potentially promoting the redistribution of effector cells into tumor-proximal regions. Full article
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27 pages, 4560 KB  
Article
Digital Village Construction and High-Quality Development of Grain Production Under the Background of Population Shrinkage: Evidence from China’s Major Grain-Producing Areas
by Jinrui Chang, Jiaxuan Yu, Jianbo Liu and Huiming Jiang
Agriculture 2026, 16(4), 470; https://doi.org/10.3390/agriculture16040470 - 19 Feb 2026
Abstract
Digital village (DV) construction is the core driving force for high-quality development of the rural economy, and is a key strategy for achieving coordinated progress in urban development and rural revitalization. This study empirically analyzes the direct effect and enhancement mechanisms of DV [...] Read more.
Digital village (DV) construction is the core driving force for high-quality development of the rural economy, and is a key strategy for achieving coordinated progress in urban development and rural revitalization. This study empirically analyzes the direct effect and enhancement mechanisms of DV construction on the high-quality development of grain production (HDGP) by panel data from 170 cities in China’s major grain-producing areas spanning 2013–2022; this study uses the CRITIC-EWM combined evaluation, two-way fixed effects, mediating effect and moderating effect model. The results show that: (1) HDGP appears more sluggish compared to the orderly growth of DV construction, but the level of DV construction and the level of HDGP are mismatched in spatial distribution. (2) DV construction has a significant promoting effect on HDGP, and the digitalization of economy and digitalization of life play more efficiently motivating role in HDGP. (3) This promoting effect is stronger in the population-shrinking regions than in the non-population-shrinking regions. (4) Approximately 8% of the promoting impact of DV construction on the HDGP is achieved indirectly through the scale of new agricultural business entities. (5) Government innovation planning exerts a significant enhancing moderating effect on the influence of DV construction on HDGP. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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20 pages, 3747 KB  
Article
Impacts of the Built Environment in Typical Medical-Circle Catchments on Residents’ Activities: A Gradient Boosting Decision Tree Framework with Visual SHAP Interpretation
by Xiaotong Wang and Jialei Li
Buildings 2026, 16(4), 832; https://doi.org/10.3390/buildings16040832 - 19 Feb 2026
Abstract
Urban emergency medical services (EMSs) depend on time-critical accessibility, spatial demand distribution, and resilient transport networks. This study examines how built-environment characteristics shape spatiotemporal population intensity (as a proxy for latent EMS demand) within Shenzhen’s 10 min ambulance-accessible Emergency Medical Circle (EMC), using [...] Read more.
Urban emergency medical services (EMSs) depend on time-critical accessibility, spatial demand distribution, and resilient transport networks. This study examines how built-environment characteristics shape spatiotemporal population intensity (as a proxy for latent EMS demand) within Shenzhen’s 10 min ambulance-accessible Emergency Medical Circle (EMC), using high-resolution Baidu Huiyan mobile-device data. Human activity intensity was quantified in 200 × 200 m grids and modeled against 20 built-environment indicators using a Gradient Boosting Decision Tree (LightGBM), with SHAP employed for interpretable attribution. By analyzing the distribution density and variance of SHAP dependence patterns, pronounced diurnal shifts in dominant drivers were identified. Medical facility density anchors nocturnal demand, road network permeability dominates pre-dawn mobility, land-use entropy and functional diversity peak during the midday period, while transit hubs and mixed-use amenities consolidate evening activity. The results further reveal critical non-linear thresholds—such as medical facility density (~1.5–2.5 km−2) and building density (~45,000–60,000 m2 km−2)—beyond which marginal contributions diminish or become negative, indicating that proximity alone does not guarantee effective emergency coverage. These findings provide quantitative, time-sensitive guidance for EMC planning, highlighting the need for balanced facility dispersion, network prioritization, and demand-aware spatial design. By integrating high-resolution population dynamics with visually interpretable machine learning, this study advances a human-centered and operationally grounded framework for resilient emergency medical systems. Full article
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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25 pages, 2986 KB  
Article
A Comprehensive Evaluation of Evapotranspiration in Mainland Portugal Based on Climate Reanalysis Data
by João Pedro Pegas, João Filipe Santos and Maria Manuela Portela
Atmosphere 2026, 17(2), 215; https://doi.org/10.3390/atmos17020215 - 18 Feb 2026
Abstract
Gridded meteorological data sources, such as reanalysis datasets, are increasingly used to estimate evapotranspiration, a key variable for surface water-budget analyses at regional and national scales and for assessing plant water requirements for irrigation. This study, conducted over mainland Portugal for the 44-year [...] Read more.
Gridded meteorological data sources, such as reanalysis datasets, are increasingly used to estimate evapotranspiration, a key variable for surface water-budget analyses at regional and national scales and for assessing plant water requirements for irrigation. This study, conducted over mainland Portugal for the 44-year reference period from 1980 to 2023, first presents a comprehensive comparative analysis of the spatial patterns of potential (Ep) and reference (Eto) evapotranspiration at a 0.1° spatial resolution using daily data. Estimates derived from two high-resolution datasets (GLEAM and ERA5-Land) are compared with those obtained from the Thornthwaite, Hargreaves–Samani, and Penman–Monteith models. Secondly, trend analyses of Eto magnitudes on a monthly and annual basis in a gridded format were conducted. The resulting spatial distributions of Ep and Eto show higher values in milder and flatter southern Portugal and lower values in the cooler and more mountainous northern regions, in agreement with existing knowledge. The Penman–Monteith model exhibited the highest reliability, while the Thornthwaite model generally underestimated evapotranspiration across the country, and the Hargreaves–Samani model showed underestimation in coastal areas. Trend analysis of Eto indicates an overall increase in atmospheric evaporative demand over the full study period, with a more pronounced rise during the recent 22-year period (2002–2023) compared with the earlier period (1980–2001). These increases are statistically significant in August and October and may reflect a climate shift towards a progressively longer dry season. Understanding how changes in evapotranspiration affect hydrological processes—including surface water availability, river discharge, reservoir performance, and crop requirement—is critical. This study aims to contribute to addressing these emerging challenges. Full article
(This article belongs to the Special Issue The Challenge of Weather and Climate Prediction (2nd Edition))
26 pages, 3984 KB  
Article
Exploring Spatial Patterns of Short-Term Rental Accommodations in Lisbon with Geographic Information System (GIS)
by Jorge Ferreira and Gonçalo Antunes
ISPRS Int. J. Geo-Inf. 2026, 15(2), 88; https://doi.org/10.3390/ijgi15020088 - 18 Feb 2026
Abstract
There has been substantial debate regarding the consequences of overtourism in cities. Scholars have also examined variables that are directly and indirectly related to tourism, including demography, urban rehabilitation and requalification, gentrification, speculation in the real estate market, the influence of digital booking [...] Read more.
There has been substantial debate regarding the consequences of overtourism in cities. Scholars have also examined variables that are directly and indirectly related to tourism, including demography, urban rehabilitation and requalification, gentrification, speculation in the real estate market, the influence of digital booking platforms, and the expansion of short-term rental (STR) accommodation. This research seeks to develop a clearer spatial understanding of this last one. By analyzing their distribution, density (maximum occupancy), and clustering and by employing Geographic Information Systems (GIS), this article will propose methodologies to better visualize spatial patterns, providing different perspectives of the city of Lisbon and its most tourism-intensive parishes. The article finds that STRs in Lisbon have expanded rapidly, concentrating overwhelmingly in six historic parishes where STR supply and maximum occupancy now exceed resident populations and housing availability. GIS analysis reveals intense clustering in central neighborhoods—especially Alfama—indicating significant tourism pressure and signs of overtourism. These spatial patterns correlate with depopulation and rising housing costs. The study concludes that STR are now a decisive factor in urban imbalance and that detailed spatial analysis is essential for regulating tourism, defining carrying-capacity thresholds, and developing more sustainable, socially just urban planning policies. Full article
(This article belongs to the Special Issue Spatial Data Science and Knowledge Discovery)
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23 pages, 7665 KB  
Article
First Observation of Offshore Gradient of CO2 and CH4 Concentration in Southeast China from 21° N to 32° N Based on Shipborne Campaign
by Yiwei Xu, Jie Wang, Libin Zhu, Na Ma, Jie Qin, Jiandong Xia, Wenjie Hu, Chen Deng, Lewei Zeng, Wilson B. C. Tsui and Xiaoquan Song
Atmosphere 2026, 17(2), 214; https://doi.org/10.3390/atmos17020214 - 18 Feb 2026
Abstract
A shipborne campaign was conducted in China’s southeastern coastal waters (21° N–32° N) from 14 to 31 January 2024 to investigate atmospheric CO2 and CH4 concentrations and their offshore gradients. Advanced instrumentation enabled high-precision measurements, validated by canister sampling with strong [...] Read more.
A shipborne campaign was conducted in China’s southeastern coastal waters (21° N–32° N) from 14 to 31 January 2024 to investigate atmospheric CO2 and CH4 concentrations and their offshore gradients. Advanced instrumentation enabled high-precision measurements, validated by canister sampling with strong correlations to reference data. The voyage employed a dual-route design: a northbound baseline along the mainland coast and a southbound route with offshore excursions up to 80 nm, facilitating the first quantification of GHG gradients in the continental shelf region. Baseline concentrations from the northbound route revealed regional variability: CO2 levels ranged from 422.75 ± 9.96 ppm (Fujian) to 445.62 ± 1.51 ppm (Zhejiang), while CH4 levels spanned 2005.78 ± 5.89 ppb (Fujian) to 2064.59 ± 13.93 ppb (Zhejiang). Southbound analysis at 10 nm intervals showed CO2 gradients transitioning from positive to negative at ~30 nm and back to positive at ~70 nm, whereas CH4 exhibited complex behavior, including a positive–negative–positive transition at 30–40 nm and consistent increase beyond 50 nm. Under winter monsoon conditions, transport flux analysis identified eastward CO2 fluxes of 3819.55–6587.77 g·m−2·s−1 and CH4 fluxes of 6.42–11.42 g·m−2·s−1. Southward transport diminished along the coast, with CO2 fluxes declining from 5741.07 to 879.76 g·m−2·s−1 and CH4 fluxes from 9.84 to 1.49 g·m−2·s−1 between Zhoushan and Hong Kong. The Taiwan Strait demonstrated a funneling effect, enhancing southward transport. These findings address data gaps in ocean regions and provide insights for future GHG monitoring. Full article
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17 pages, 3802 KB  
Article
Spatial Epidemiological Approach to Tuberculosis Treatment Outcomes in a Tertiary-Level Hospital: A Retrospective Analysis
by Luis Eduardo Del Moral Trinidad, Gilberto Silva Bañuelos, Esteban Gonzalez-Diaz and Melva Guadalupe Herrera Godina
Trop. Med. Infect. Dis. 2026, 11(2), 57; https://doi.org/10.3390/tropicalmed11020057 - 18 Feb 2026
Abstract
Tuberculosis (TB) remains a persistent public health challenge in Mexico, particularly in large urban settings marked by social heterogeneity. We conducted a retrospective cohort study of patients diagnosed with tuberculosis and treated at a tertiary-level hospital in Guadalajara, Mexico, between 2020 and 2023. [...] Read more.
Tuberculosis (TB) remains a persistent public health challenge in Mexico, particularly in large urban settings marked by social heterogeneity. We conducted a retrospective cohort study of patients diagnosed with tuberculosis and treated at a tertiary-level hospital in Guadalajara, Mexico, between 2020 and 2023. Unfavorable treatment outcomes were defined as treatment failure, loss to follow-up, or death. Multivariable logistic regression was used to identify factors independently associated with unfavorable outcomes. Spatial analyses, including Kernel Density Estimation, Global Moran’s I, Local Indicators of Spatial Association (LISA), and Getis–Ord Gi*, were applied to explore the geographic distribution of unfavorable outcomes. Unfavorable tuberculosis treatment outcomes among patients treated at a tertiary-level hospital were not randomly distributed in space. Spatial epidemiological methods provided complementary, exploratory insights beyond individual-level clinical factors, highlighting geographic patterns that may inform place-sensitive public health interventions and strengthen routine tuberculosis surveillance, without implying causal inference. Full article
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34 pages, 4588 KB  
Article
Site and Capacity Planning of Electric Vehicle Charging Stations Based on Road–Grid Coupling
by Zhenke Tian, Qingyuan Yan, Yuelong Ma and Chenchen Zhu
World Electr. Veh. J. 2026, 17(2), 101; https://doi.org/10.3390/wevj17020101 - 18 Feb 2026
Abstract
To address the rapidly growing demand for charging stations (CSs) and the associated challenges posed by the expansion of electric vehicles (EVs), this study proposes a collaborative planning method integrates user demand considerations with operational constraints at the grid level. Based on graph [...] Read more.
To address the rapidly growing demand for charging stations (CSs) and the associated challenges posed by the expansion of electric vehicles (EVs), this study proposes a collaborative planning method integrates user demand considerations with operational constraints at the grid level. Based on graph theoretical principles, static topology models of the road network and distribution grid were constructed. A dynamic origin–destination (OD) prediction framework was then formulated by jointly considering traffic flow variations, battery energy consumption, user charging behavior, and ambient temperature, in which an enhanced gravity model is coupled with the Floyd algorithm. Charging load characteristics were quantified through Monte Carlo simulation, and K-means++ clustering was further applied to identify spatial charging demand hotspots. On this basis, a multi-objective optimization model was established to simultaneously balance the annualized cost of charging stations, user costs, and voltage deviation in the distribution network. To solve the resulting high dimensional problem, a collaborative optimization mechanism was designed by integrating a weighted Voronoi diagram with a multi-objective particle swarm optimization (MOPSO) algorithm, enabling dynamic service area partitioning and global capacity optimization. Case analysis demonstrates that the proposed method reduces user time costs by 15.8%, optimizes queue delay by 42.2%, and improves voltage stability, maintaining fluctuations within 5%. It also balances the interests of charging station operators, users, and distribution networks, with only a slight increase in construction costs. These results offer valuable theoretical and practical insights for charging infrastructure planning. Full article
(This article belongs to the Section Charging Infrastructure and Grid Integration)
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