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Significant research has been conducted in recent years to determine crash hotspots. This study focused on the effects of various traffic parameters, including average traffic speed and traffic volume, on the spatial distributions of freeway crashes. Specifically, this study analyzed the spatial distributions of crashes on the Qazvin–Abyek freeway in Iran using four-year crash records. Spatial crash clustering analysis was performed to identify hotspots and high cluster segments using global Moran’s I, local Moran’s I, and Getis-Ord Gi*. The global Moran’s I indicated that clusters were formed under the low range of hourly traffic volume (less than 1107 veh/h) and the high range of traffic speed (more than 97 km/h), which increased the number of heavy vehicle crashes in the early morning (time 03–06) around the 52 km segment. The results obtained from kernel density estimation (KDE), local Moran’s I, and Getis-Ord Gi* revealed similar crash hotspots. The results further showed different spatial distributions of crashes for different traffic hourly volumes, traffic speed, and crash times, and there was hotspot migration by applying different traffic conditions. These findings can be used to identify high-risk crash conditions for traffic managers and help them to make the best decisions to enhance road safety.

This study analyzes the spatiotemporal characteristics of PM10 across 53 Asian dust events that affected the Korean Peninsula between January 2019 and June 2024. Self-Organizing Map (SOM) analysis was applied to sea level pressure and 850 hPa wind fields from the NCEP/DOE Reanalysis II dataset, classifying synoptic patterns into four distinct clusters. Cluster 1, associated with a deep low over Manchuria and strong westerly inflow, produced the highest PM10 concentrations and the longest durations across most regions, with sharp afternoon peaks and the highest skewness values, and was mainly sourced from the Gobi Desert. Cluster 2 featured a high–low pressure dipole, generating localized impacts in northwestern regions and shorter durations, with moderate afternoon increases, originating primarily from the Gobi Desert and Inner Mongolia. Cluster 3, linked to a low east of Japan, resulted in elevated PM10 mainly in central and southeastern regions, with peaks often occurring earlier in the day, and was associated with Manchurian dust sources. Cluster 4 exhibited a straight northwesterly flow with the high shifted eastward, producing moderate but spatially widespread concentrations and relatively consistent afternoon peaks, also linked to Manchurian sources. These results suggest that integrating synoptic pattern classification into dust forecasting can improve accuracy, enable early recognition of high-concentration events, and support the development of timely and region-specific warning strategies.

Background: Violence against doctors is a global concern. Violent injuries against doctors occur periodically in China. At least one violent injury event was witnessed by 54% of medical staff against doctors in 2020. Analyzing this phenomenon and establishing preventive measures is a common concern of the medical and criminal communities. Methods: This study comprised 712 injury events against doctors in Guangdong Province, China, from January 2019 to October 2022. The spatial distribution and spatiotemporal changes of these events were analyzed using ArcGIS and Excel software. Results: Considering the geographical distribution, the injury events against doctors showed a three-level concentric circle pattern where, Guangzhou and Shenzhen, adjacent cities, and distant cities were ranked as high, medium, and low-risk areas, respectively. In temporal distribution, the periods of high incidence were 9-11, 14-15, and 20 o'clock, and the incidence tended to be similar daily, with the peaks in June and July. Conclusion: We found that the risk level of injury events against doctors was positively correlated with the medical resources level in the areas. The injury event incidence was higher during the daytime working hours. Temperature may have a strong positive effect on injury events against doctors. Keywords: injury events against doctors, Guangdong Province, spatiotemporal distribution characteristics, spatiotemporal distribution analysis, geographic information system

Recently, air quality has become a hot topic due to its profound impact on the quality of the human living environment. This paper selects the tourist city of Dalian as the research object. The concentration and spatial distribution of PM10 and NO2 in the main urban area were analyzed during the peak tourist seasons in summer and winter. Simulations were used to explore the spatial and temporal variation patterns of PM10 and NO2, combining building and road density at different scales to reveal the coupling relationship between individual pollutant components and urban parameters. The results show that the PM10 concentration is high in the center and NO2 is concentrated in the northern district of Dalian City. In an area with a radius of 100 m, the dilution ratio of building density and road density to the concentration of the PM10 pollutants is at least 43%. Still, the concentration of NO2 is only coupled with road density. This study reveals the spatial and temporal variation patterns of PM10 and NO2 in Dalian, and finds the coupling relationship between the two pollutants and building density and road density. This study provides a reference for preventing and controlling air pollution in urban planning.

Food security has become a key global issue due to rapid population growth, extensive conversion of arable lands, and declining overall productivity in some areas because of the effects of floods, water shortage, salinity intrusion, and plant diseases. In this study, we analyzed the relationship between the pattern of salinity intrusion and the spatiotemporal distribution of rice cultivation in the winter–spring crops of 2015, 2016, 2019 and 2020 in coastal provinces of the Vietnamese Mekong Delta. Sentinel-1 (S-1) data were used to extract the spatial distribution information of six rice growth stages based on a rice age algorithm. The classification accuracy of rice crop growth stages was found to have an overall accuracy of 85% and a Kappa coefficient of 0.80 (n = 373). For evaluating salinity intrusion effects, salinity isolines (4 g/L) were used to determine the percentage of rice areas affected. Results show that in the years observed to have severe salinity intrusion such as 2016 and 2020, a strong shift in planting calendar was identified to avoid salinity intrusion, with some areas being sown or transplanted 10–30 days earlier than normal planting. In addition, the lack of irrigation water and salinity intrusion limits rice cultivation in the dry season of coastal areas. Further analysis from the S-1 data confirms that the spatiotemporal distribution of rice cultivation is related to the change in government policy/recommendation affected by salinity intrusion. These findings demonstrate the potential and feasibility of using S-1 data to develop an operational rice crop adaptation framework on the delta scale.

Biotic interactions in aquatic communities are dominated by predation, and the distribution of trophic link strengths in aquatic food webs crucially impacts their dynamics and stability. Although individual body size explains a large proportion of variation in trophic link strengths in aquatic habitats, current predominately body size-based views can gain additional realism by incorporating further traits. Functional traits that potentially affect the strength of trophic links can be classified into three groups: i) body size, ii) traits that identify the spatiotemporal overlap between the predators and their prey, and iii) predator foraging and prey vulnerability traits, which are readily available for many taxa. Relationship between these trait groups and trophic link strength may be further modified by population densities, habitat complexity, temperature and other abiotic factors. I propose here that this broader multi-trait framework can utilize concepts, ideas and existing data from research on metabolic ecology, ecomorphology, animal personalities and role of habitats in community structuring. The framework can be used to investigate non-additive effects of traits on trophic interactions, shed more light on the structuring of local food webs and evaluate the merits of taxonomic and functional group approaches in the description of predator-prey interactions. Development of trait- and size-based descriptions of food webs could be particularly fruitful in limnology given the relative paucity of well resolved datasets in standing waters.

The Early Cretaceous Jehol Biota is a terrestrial lagerstätte that contains exceptionally well-preserved fossils indicating the origin and early evolution of Mesozoic life, such as birds, dinosaurs, pterosaurs, mammals, insects, and flowering plants. New geochronologic studies have further constrained the ages of the fossil-bearing beds, and recent investigations on Early Cretaceous tectonic settings have provided much new information for understanding the spatiotemporal distribution of the biota and dispersal pattern of its members. Notably, the occurrence of the Jehol Biota coincides with the initial and peak stages of the North China craton destruction in the Early Cretaceous, and thus the biotic evolution is related to the North China craton destruction. However, it remains largely unknown how the tectonic activities impacted the development of the Jehol Biota in northeast China and other contemporaneous biotas in neighboring areas in East and Central Asia. It is proposed that the Early Cretaceous rift basins migrated eastward in the northern margin of the North China craton and the Great Xing’an Range, and the migration is regarded to have resulted from eastward retreat of the subducting paleo-Pacific plate. The diachronous development of the rift basins led to the lateral variations of stratigraphic sequences and depositional environments, which in turn influenced the spatiotemporal evolution of the Jehol Biota. This study represents an effort to explore the linkage between terrestrial biota evolution and regional tectonics and how plate tectonics constrained the evolution of a terrestrial biota through various surface geological processes.

Dockless bike-sharing is becoming popular all over the world, and short-term spatiotemporal distribution forecasting on system state has been further enlarged due to its dynamic spatiotemporal characteristics. We employ a deep learning approach, named the convolutional long short-term memory network (conv-LSTM), to address the spatial dependences and temporal dependences. The spatiotemporal variables including number of bicycles in area, distribution uniformity, usage distribution, and time of day as a spatiotemporal sequence in which both the input and the prediction target are spatiotemporal 3D tensors within one end-to-end learning architecture. Experiments show that conv-LSTM outperforms LSTM on capturing spatiotemporal correlations.

ContextConstructing a sustainable landscape pattern from the perspective of landscape sustainability is scientifically built on the clarification of the formation mechanisms of landscape services and their relationships. However, the trade-offs and synergies of landscape services have regional heterogeneity, and their influencing factors are largely unknown in polar ecosystem. The Qinghai–Tibet Plateau is a unique but fragile ecosystem, and its landscape services are vital components to the sustainability in this specific polar region.ObjectivesThis study sought to understand the landscape service relationships, their dynamics and influencing factors, and achieve a sustainable landscape management in the Qinghai–Tibet Plateau.MethodsIn this work, we evaluated the spatiotemporal distribution and relationships of multiple landscape services including soil retention (SR), water yield (WY), habitat quality (HQ), crop supply (CS) and livestock supply (LS). We further identified temperature, elevation, population size, land use and land cover (LULC) as influencing factors on landscape services relationships within specific landscape gradients.ResultsOur results show that: (1) SR, WY and HQ decreased significantly from the southeast to the northwest. (2) Regulating services-supporting services are mainly identified as synergies, and CS–HQ and CS–LS are manifested as trade-offs. (3) Geophysical factors (temperature, altitude) have impact on the distribution of CS and the trade-off and synergistic dynamics of WY–HQ, increased population size enhances CS–HQ trade-offs, while between supporting and regulating services show trade-offs in high-coverage grassland and unused land.ConclusionsThe quantitative assessment of landscape services and relationships provides the basis for sustainable landscape management in the context of national policies and climate change.

Objective In recent years, the increasing incidence of brucellosis in children has become more serious. However, relatively few studies have been conducted to characterize the spatialtemporal distribution of brucellosis in children. This study aimed to analyze the spatiotemporal distribution characteristics and ecological influencing factors of brucellosis incidence among children in Inner Mongolia. Methods This study used data on brucellosis incidence in children aged 0–14 years reported in Inner Mongolia from 2016 to 2020. A Bayesian model was used to analyze the spatial and temporal distribution of brucellosis in children from 2016 to 2020 in Inner Mongolia. Geographical weighted regression model was used to analyze the ecological factors related to the incidence of brucellosis in children. Result Bayesian spatiotemporal analysis indicated that the highest brucellosis risk and increased disease incidence were observed in Hinggan, Inner Mongolia, in children aged 0–14 years. Alxa had the lowest risk but the incidence rate increased rapidly. The incidence of childhood brucellosis was positively associated with the number of sheep at the year-end (β: 2.5909 ~ 2.5926, P  < 0.01), average temperature (β: 2.8978 ~ 2.9030, P  < 0.05), and precipitation level (β: 3.3261 ~ 3.3268, P  < 0.01). Conclusion From 2016 to 2020, the overall incidence of brucellosis in children in Inner Mongolia showed an upward trend, with cases exhibiting spatial aggregation. We should focus on areas where the incidence of brucellosis in children is rising rapidly. The incidence of childhood brucellosis was associated with the number of sheep at the year-end, average temperature and precipitation level. Implications and contribution The findings suggest that brucellosis in children is not to be taken lightly. For children should also focus on protection, take corresponding protective measures. While we focus on high-risk areas, we must also monitor areas where the risk of disease is low, but the incidence is rising fast, to prevent outbreaks in low-risk areas from becoming high-risk areas.