Search Results (253)

Urban tourism has evolved into a complex adaptive system, where unregulated expansion disrupts the ecological balance and intensifies resource stress. Understanding the dynamic evolution and resilience mechanisms of the tourism ecological health network (TEHN) is essential for supporting sustainable urban tourism as a coupled human–natural system. Using Shanghai as a case study, we applied the "vigor–organization–resilience–services" (VORS) framework to evaluate ecosystem health, which served as a constraint for constructing the TEHN, using the minimum cumulative resistance (MCR) model for the period from 2001 to 2023. A resilience framework integrating structural and functional dimensions was further developed to assess spatiotemporal evolution and guide targeted enhancement strategies. The results indicated that as ecosystem health degraded, particularly in peripheral areas, the urban TEHN in Shanghai shifted from a dispersed to a centralized structure, with limited connectivity in the periphery. The resilience of the TEHN continued to grow, with structural resilience remaining at a high level, while functional resilience still required enhancement. Specifically, the low integration and limited choice between the tourism network and the transportation system hindered tourists from selecting routes with higher ecosystem health indices. Enhancing functional resilience, while sustaining structural resilience, is essential for transforming the TEHN into a multi-centered, multi-level system that promotes efficient connectivity, ecological sustainability, and long-term adaptability. The results contribute to a systems-level understanding of tourism–ecology interactions and support the development of adaptive strategies for balancing network efficiency and environmental integrity. Full article

Petrochemical complexes are spatially expansive and host diverse emission sources, making accurate monitoring of volatile organic compounds (VOCs) challenging using conventional two-dimensional methods. This study introduces Mobile-extraction Differential Optical Absorption Spectroscopy (Me-DOAS), a real-time, three-dimensional remote sensing technique for assessing benzene emissions in the Ulsan petrochemical complex, South Korea. A vehicle-mounted Me-DOAS system conducted monthly measurements throughout 2024, capturing data during four daily intervals to evaluate diurnal variation. Routes included perimeter loops and grid-based transects within core industrial zones. The highest benzene concentrations were observed in February (mean: 64.28 ± 194.69 µg/m³; geometric mean: 5.13 µg/m³), with exceedances of the national annual standard (5 µg/m³) in several months. Notably, nighttime and early morning sessions showed elevated levels, suggesting contributions from nocturnal operations and meteorological conditions such as atmospheric inversion. A total of 179 exceedances (≥30 µg/m³) were identified, predominantly in zones with benzene-handling activities. Correlation analysis revealed a significant relationship between high concentrations and specific emission sources. These results demonstrate the utility of Me-DOAS in capturing spatiotemporal emission dynamics and support its application in exposure risk assessment and industrial emission control. The findings provide a robust framework for targeted management strategies and call for integration with source apportionment and dispersion modeling tools. Full article

Amid ongoing societal development, tourists’ travel behavior patterns have been undergoing substantial transformations, and understanding their evolution has emerged as a key area of scholarly interest. Taking Beijing as a case study, this research aims to uncover the spatiotemporal evolution patterns of tourist flows and their underlying driving mechanisms. Based on digital footprint relational data, a dual-perspective analytical framework—“tourist perception–tourist flow network”—is constructed. By integrating the center-of-gravity model, social network analysis, and regression models, the study systematically examines the dynamic spatial structure of tourist flows in Beijing from 2012 to 2024. The findings reveal that in the post-pandemic period, Beijing tourists place greater emphasis on the cultural connotation and experiential aspects of destinations. The gravitational center of tourist flows remains relatively stable, with core historical and cultural blocks retaining strong appeal, though a slight shift has occurred due to policy influences and emerging attractions. The evolution of the spatial network structure reveals that tourism flows have become more dispersed, while the influence of core scenic spots continues to intensify. Government policy orientation, tourism information retrieval, and the agglomeration of tourism resources significantly promote the structure of tourist flows, whereas the general level of tourism resources exerts no notable influence. These findings offer theoretical insights and practical guidance for the sustainable development and regional coordination of tourism in Beijing, and provide a valuable reference for the spatial restructuring of urban tourism in the post-COVID-19 era. Full article

Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for the rapid dispersion of hazardous air pollutants (HAPs). In this study, we conducted spatiotemporal data collection and analysis for the first time in Korea using real-time measurements obtained through mobile extractive differential optical absorption spectroscopy (Me-DOAS) mounted on a solar occultation flux (SOF) vehicle. The measurements were conducted in the Saha Sinpyeong–Janglim Industrial Complex in Busan, which comprises the Sasang Industrial Complex and the Sinpyeong–Janglim Industrial Complex. BTEX compounds were selected as target volatile organic compounds (VOCs), and real-time measurements of both BTEX and fine particulate matter (PM) were conducted simultaneously. Correlation analysis revealed a strong relationship between PM₁₀ and PM_2.5 (r = 0.848–0.894), indicating shared sources. In Sasang, BTEX levels were associated with traffic and localized facilities, while in Saha Sinpyeong–Janglim, the concentrations were more influenced by industrial zoning and wind patterns. Notably, inter-compound correlations such as benzene–m-xylene and p-xylene–toluene suggested possible co-emission sources. This study proposes a GIS-based, three-dimensional air quality management approach that integrates variables such as traffic volume, wind direction, and speed through real-time measurements. The findings are expected to inform effective pollution control strategies and future environmental management plans for industrial complexes. Full article

This study focuses on the Triangle of Central China and investigates the spatiotemporal evolution, driving factors, and impacts of population aging on regional sustainable development from 2000 to 2020. The study adopts an innovative two-scale analytical framework at the prefecture and district/county level, integrating spatial autocorrelation analysis, the Geodetector model, and geographically weighted regression. The results show a significant acceleration in population aging across the study area, accompanied by pronounced spatial clustering, particularly in western Hubei and the Wuhan metropolitan area. Over time, the spatial distribution has evolved from a relatively dispersed pattern to one of high concentration. Key drivers of the spatial heterogeneity of aging include economic disparities, demographic transitions, and the uneven spatial allocation of public services such as healthcare and education. These aging patterns profoundly affect the region’s potential for sustainable development. Accordingly, the study proposes a multi-scale collaborative governance strategy: At the prefecture level, efforts should focus on promoting the coordinated development of the silver economy and optimizing the spatial redistribution of healthcare resources; At the district and county level, priorities should include strengthening infrastructure, curbing the outflow of young labor, and improving access to basic public services. By integrating spatial analysis techniques with sustainable development policy recommendations, this study provides a basis for scientifically measuring, understanding, and managing demographic transitions. This is essential for achieving long-term socioeconomic sustainability in rapidly aging regions. Full article

The Cao’e-Jiaojiang-Oujiang River Basin possesses abundant vernacular architectural heritage with significant historical–cultural value. However, challenges like dispersed distribution and inconsistent conservation hinder its systematic protection and utilization within territorial spatial planning, necessitating a deeper understanding of its spatiotemporal patterns. Utilizing 570 identified heritage sites, this study employed ArcGIS spatial analysis (Kernel Density Estimation, Nearest Neighbor Index), correlation analysis with DEM data, and suitability analysis (Minimum Cumulative Resistance model, Gravity Model) to systematically examine spatial distribution characteristics, their evolution, and relationships with the geographical environment and historical context. Results revealed a distinct “four cores and three belts” spatial pattern. Temporally, distribution evolved from “discrete” (Song-Yuan) to “aggregated” (Ming-Qing) and then “diffused” (Modern era). Spatially, heritage showed density in plains, preference for low slopes, and settlement along waterways. Suitability analysis indicated higher corridor potential in the northern section (Cao’e-Jiaojiang) than the south (Oujiang), leading to the identification of a “Northern Segment (Shaoxing-Ningbo-Shengzhou-Taizhou)” and “Southern Segment (Wenzhou-Lishui)” corridor structure. This research provides a scientific basis for systematic conservation and integrated heritage corridor construction of vernacular architectural heritage in the basin, supporting Zhejiang’s Poetry Road Cultural Belt initiatives and cultural heritage protection within territorial spatial planning. Full article

This study investigates the spatiotemporal evolution of oil released during the Agia Zoni II shipwreck in the Saronic Gulf in 2017, employing the OpenOil module of the OpenDrift framework. The simulation integrates oceanographic and meteorological data to model the transport, weathering, and fate of spilled oil over a six-day period. Oil behavior is examined across key transformation processes, including dispersion, emulsification, evaporation, and biodegradation, using particle-based modeling and a comprehensive set of environmental inputs. The modeled results are validated against in situ observations and visual inspection data, focusing on four critical dates. The study demonstrates OpenOil’s potential for accurately simulating oil dispersion dynamics in semi-enclosed marine environments and highlights the significance of environmental forcing, vertical mixing, and shoreline interactions in determining oil fate. It concludes with recommendations for improving real-time response strategies in similar spill scenarios. Full article

In Ukraine, SARS-CoV-2 detection and national genomic surveillance have been complicated by full-scale war, limited resources, and varying levels of public health infrastructure impacted across the country. Following the Spring of 2022, only a paucity of data have been reported describing the prevalence and variant dynamics of SARS-CoV-2 in the country. Comparative whole genome analysis has overtaken diagnostics as the new gold standard for detecting and tracing emerging variants while showing utility to rapidly inform diagnostics, vaccine strategies, and health policy. Herein, we provide an updated report characterizing the dynamics and prevalence of SARS-CoV-2 in Ukraine from 1 May 2022 to 31 March 2024. The present study extends previous reports for disease incidence Waves 1–4 in Ukraine with the addition herein of Waves 5, 6, and 7, occurring from August to November 2022 (Wave 5), February to May 2023 (Wave 6), and October 2023 to January 2024 (Wave 7). During the study period, the national Case Fatality Rate (CFR) fluctuated between 0.46% and 1.74%, indicating a consistent yet modest rate when compared to the global average. The epidemiological dynamics of Variants of Concern (VOCs) in Ukraine reflected global patterns over this period, punctuated by the rise of the BA.5 lineage and its subsequent replacement by the Omicron subvariants XBB and JN.1. Our analysis of variant dispersal patterns revealed multiple potential spatiotemporal introductions into Ukraine from Europe, Asia, and North America. Our results highlight the importance of ongoing genomic surveillance to monitor variant dynamics and support global efforts to control and mitigate COVID-19 disease risks as new variants arise. Full article

Understanding spatiotemporal mismatches between urban expansion and population dynamics is essential for guiding sustainable development in rapidly urbanizing regions. Using multi-source nighttime light (NTL) images and global settlement layers, this study investigates the settlement growth pattern and potential spatiotemporal mismatch with population distribution in Guangdong, China, from 1995 to 2019 at a 5-year interval. Specifically, population spatialization in urban and rural areas is separately mapped by adopting a population-based thresholding method, achieving strong agreement with the census record. Our analysis reveals distinct expansion patterns and mismatch conditions across Guangdong’s Core, Belt, and District subzones. The Core and District subzones primarily experienced infilling and edge-expansion urban growth, while the Belt subzone exhibited more dispersed spatial patterns. Notably, only 5 of 21 prefectures exhibited faster population growth than urban expansion, likely due to sustained migration driven by economic opportunities and advanced urbanization. Quantitatively, both urban expansion and population growth followed a Core, Belt, District order. Spatially, population-dominated areas were primarily clustered within 10 km of urban centers, while the District subzone extensively displayed overfilled settlements, indicating low-efficient land use. Temporally, urban growth relative to population in the Core subzone turned from slower pre-2000 to faster post-2000, followed by gradual deceleration, while the Belt subzone maintained balanced growth throughout the study period. The District subzone sustained faster urban growth from 2000 to 2019. Findings of the study provide an important reference for scientific urban planning and sustainable regional development, not only in Guangzhou but other rapidly urbanizing regions globally. Full article

Understanding how piglets move around sows during posture changes is crucial for their safety and healthy growth. Automated monitoring can reduce farm labor and help prevent accidents like piglet crushing. Current methods (called Joint Detection-and-Tracking-based, abbreviated as JDT-based) struggle with problems like misidentifying piglets or losing track of them due to crowding, occlusion, and shape changes. To solve this, we developed MSHMTracker, a smarter tracking system that introduces a motion-status hierarchical architecture to significantly improve tracking performance by adapting to piglets’ motion statuses. In MSHMTracker, a score- and time-driven hierarchical matching mechanism (STHM) was used to establish the spatio-temporal association by the motion status, helping maintain accurate tracking even in challenging conditions. Finally, piglet group aggregation or dispersion behaviors in response to sow posture changes were identified based on the tracked trajectory information. Tested on 100 videos (30,000+ images), our method achieved 93.8% tracking accuracy (MOTA) and 92.9% identity consistency (IDF1). It outperformed six popular tracking systems (e.g., DeepSort, FairMot). The mean accuracy of behavior recognition was 87.5%. In addition, the correlations (0.6 and 0.82) between piglet stress responses and sow posture changes were explored. This research showed that piglet movements are closely related to sow behavior, offering insights into sow–piglet relationships. This work has the potential to reduce farmers’ labor and improve the productivity of animal husbandry. Full article

Accurate measurement of pipeline flow is of great significance for industrial and environmental monitoring. Traditional intrusive methods have the disadvantages of high cost and damage to pipeline structure, while non-intrusive techniques can circumvent such issues. Although Taylor’s frozen hypothesis has a theoretical advantage in non-intrusive velocity detection, current research focuses on planar flow fields, and its applicability in turbulent circular pipes remains controversial. Moreover, there is no precedent for combining it with distributed acoustic sensing (DAS) technology. This paper constructs a circular pipe turbulence model through large eddy simulation (LES), revealing the spatiotemporal distribution characteristics of turbulent kinetic energy and the energy propagation rules of FK spectra. It proposes a dispersion feature enhancement algorithm based on cross-correlation, which combines a rotatable elliptical template with normalized cross-correlation coefficients to suppress interference from non-target directions. An experimental circulating pipeline DAS measurement system was set up to complete signal denoising and compare two principles of flow velocity verification. The results show that the vortex structure of turbulent flow in circular pipes remains stable in the convection direction, conforming to theoretical premises; the relative error of average flow velocity by this method is ≤3%, with significant improvements in accuracy and stability in high-flow zones. This study provides innovative methods and experimental basis for non-intrusive flow detection using DAS. Full article

In high-speed railway networks, multiple spatiotemporal correlated disruptions often cause passenger trip failures and delay propagation. Conventional single-disruption rescheduling strategies struggle to resolve such cross-line conflicts, necessitating an integrated, passenger-centric rescheduling framework for multiple correlated disruptions. This paper proposes a mixed-integer linear programming (MILP) model to minimize total passenger delay time and trip failures under scenarios involving disruptions that are geographically dispersed but operationally interconnected. Two rescheduling mechanisms are introduced: a stepwise rescheduling method, which iteratively applies single-disruption models to optimize local problems, and an integrated rescheduling method, which simultaneously considers the global impact of all disruptions. Case studies on a real-world China’s high-speed railway network (29 stations, 42 trains, and 36,193 passenger trips) demonstrate that the proposed integrated rescheduling method reduces total passenger delays by 13% and trip failures by 67% within a 300 s computational threshold. By systematically coordinating spatiotemporal interdependencies among disruptions, this approach enhances network accessibility and service quality while ensuring operational safety, providing theoretical foundations for intelligent railway rescheduling. Full article

The Sterile Insect Technique (SIT) is most effective at large regional scales when applied within an area-wide framework. However, there is a need to investigate its feasibility at smaller scales, e.g., for emergency responses to local fruit fly invasions or planning for preventive release of sterile males in local high-risk zones. Available decision support tools and SIT implementation models are effective for large-scale interventions but tend to ignore the influences of fine-grained terrain structures and therefore offer little guidance for small-scale SIT operations in locally diverse landscapes. This study addresses this issue by adapting a site-specific individual-based PESTonFARM model to simulate both the behaviour and fate of individual members of ultra-small invasive medfly propagules and the post-release dispersal and mating performance of sterile males in heterogeneous and mosaic landscapes. To illustrate model operation, several SIT implementation scenarios were simulated to reveal the influence of local landscape structure on the behaviour of wild and released sterile males and to quantitatively assess the effectiveness of different SIT scenarios. Our results demonstrate the sensitivity of the model and showed that the influence of the spatiotemporal structure of local resources should not be ignored when planning local SIT operations. Full article

The concept of space–time duality in optics was originally based on the mathematical connection between the diffraction of beams in space and the dispersion of pulses in time. This concept has been extended in recent years from the temporal analog of reflection for optical pulses to photonic time crystals in a medium where refractive index varies with time in a periodic fashion. In this review, I discuss how the concept of space–time duality and the use of nonlinear optics has led to many advances in recent years. Starting from the historical origin of space–time duality, time lenses and their applications are reviewed first. Later sections cover phenomena such as soliton-induced temporal reflection, time-domain waveguiding, and the formation of spatiotemporal Bragg gratings. Full article

The integration of high proportions of renewable energy into power systems to replace traditional synchronous generators has led to continuous weakening of the system inertia support and primary frequency regulation resources. Spatiotemporal dispersion of the system’s frequency response has become increasingly prominent. Historical data from numerous frequency disturbance events show that the unified system’s frequency can no longer accurately represent the variations in the frequency response at each node in the system. To address this issue, a method for frequency measurement point selection and system partitioning in a high-renewable-energy-penetration power system is proposed. Firstly, the frequency regulation influence (FRI) index is defined to quantify the comprehensive ability of nodes to dynamically regulate the spatiotemporal dynamics of the power system’s frequency, identifying key frequency regulation nodes as the regional frequency measurement points. Secondly, a hierarchical clustering method is employed to partition the remaining nodes around the frequency measurement points, and the optimal partitioning result is evaluated using modularity indicators. Finally, the effectiveness of the proposed method is verified using a modified standard 39-node system. The simulation results reveal that the proposed frequency measurement point selection and system partitioning method can effectively enhance the accuracy of regional frequency response measurements, as well as the evaluation accuracy of inertia and primary frequency regulation. Full article