Tourism Competitiveness Evaluation and Spatio-temporal Characteristics of Chinese Border Counties

Under the current government strategy of building a Silk Road economic belt, tourism in Chinese border counties has becoming increasingly popular. Studying tourism competitiveness in Chinese border counties is of sizable theoretical and practical importance, as there are several notable factors involved. In this study, we constructed a tourism competitiveness evaluation model based on eight factors: natural environment, tourism resource, location and transportation, social environment, tourism service facility, border port, tourism industrial cluster and tourism market. We then analyzed the spatial characteristics of tourism competitiveness in border counties and identified five types of border counties: resource advantage type(RA), border-port advantage type(PA), location advantage type(LA), agglomeration advantage type(AA), and relative balance type(RB), and examined the correlation between tourism market competitiveness and interior competitiveness factors in the counties from 2006 to 2011. Results showed that tourism resource, location and transportation, and tourism service facility are the most important competition factors for RA border counties during the study period. Competition factors in PA counties transferred from tourism resource, social environment and tourism service facility to border port and tourism industrial cluster; competition factors in LA counties transferred from natural environment and tourism resource to tourism service facility and tourism industrial cluster and border port. Competition factors in AA counties transferred from tourism service facility to tourism resource. Tourism industrial cluster, tourism service facility and tourism resource proved to be important competition factors in RB counties. The findings of this study can be used to target tourism strategies according to different county types.

Spatio-Temporal Characteristics of Winter Cold Events in China from 1960 to 2020

Under the background of global warming, extreme cold events occur frequently. It is important to enhance the understanding of cold air patterns for forecasting cold air and reducing cold air-induced meteorological disasters. The study used the daily minimum temperatures from the National Climate Centre to classify the cold events affecting China into five different grades and the characteristics of different intensity cold events in China during the winter from 1960 to 2020 were analyzed. The results showed that there is little difference in the distribution of the frequency of general cold events from north to south, with duration longer in the north than in the south and an increase in frequency in the north in the last 60 years. The frequency of strong cold events is more in the north of China than in the south of China, and the duration is longer in the south than in the north China, with the frequency decreasing in most parts of the country. In addition to latitude, cold events frequency is closely linked to topography, with basins surrounded by high mountains being difficult to be affected by cold events, especially extreme cold events. In terms of month distribution, December was subject to the highest frequency of cold events and the longest duration of a single cold events process.

Spatio-temporal Characteristics and Geographical Determinants of Air Quality in Cities at the Prefecture Level and Above in China

In recent years, the large scale and frequency of severe air pollution in China has become an important consideration in the construction of livable cities and the physical and mental health of urban residents. Based on the 2016-year urban air quality index(AQI) data published by the Ministry of Environmental Protection of China, this study analyzed the spatial and temporal characteristics of air quality and its influencing factors in 338 urban units nationwide. The analysis provides an effective scientific basis for formulating national air pollution control measures. Four key results are shown. 1) Generally, air quality in the 338 cities is poor, and the average annual values for urban AQI and air pollution in 2016 were 79.58% and 21.22%, respectively. 2) The air quality index presents seasonal changes, with winter > spring > autumn > summer and a u-shaped trend. 3) The spatial distribution of the urban air quality index shows clear north-south characteristic differences and a spatial agglomeration effect; the high value area of air pollution is mainly concentrated in the North China Plain and Xinjiang Uygur Autonomous Region. 4) An evaluation of the spatial econometric model shows that differences in urban air quality are due to social, economic, and natural factors.

Spatio-temporal Characteristics of Area Coverage and Observation Geometry of the MISR Land-surface BRF Product: A Case Study of the Central Part of Northeast Asia

The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP)±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.

Analysis of the Spatio-Temporal Characteristics of Winter Surface Urban Heat Island:A Case Study in Beijing,China

This study reveals the temporal and spatial evolution characteristics of the winter nighttime urban heat island(UHI)effect in the case of Beijing,China.The land surface temperature(LST)is retrieved by radiative transfer equation by using the remote sensing data from Landsat ETM+/OLI_TIRS from 2007 to 2017 for the winter nighttime period,and LST is then divided by the mean-standard deviation method into different levels of thermal landscapes.A combination of the migration calculation of gravity center and multi-directional profile analysis is used to study the directional differentiation characteristics of LST and the migratory characteristics of the gravity center of UHI.Finally,the overall temporal and spatial evolution characteristics of winter nighttime surface urban heat island(SUHI)in Beijing are studied,and the possible reasons for the changes are discussed.Results show that Beijing's UHI effect first increased and subsequently decreased from 2007 to 2017.The winter heat island in the urban area developed from low-density agglomeration to high-density agglomeration to lowdensity diffusion.Additionally,the high-level thermal landscapes migrated to the southwest along with the city center of gravity,and the expansion rate is fastest in the southwest,which is directly linked to the changes in the urban construction land.Moreover,the overall spatial distribution of winter nighttime LST is high in the east and south and low in the west and north,and is influenced by topography,land cover,urbanization,anthropogenic heat,and other factors as well.

Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022

Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.

Spatio-temporal characteristics and influencing factors of Pseudo Human Settlements in Northeast China based on the Baidu Index

Pseudo Human Settlements(PHS)are a fundamental element in human settlements geography,serving as an innovative frontier in the exploration of human–land relationships.Since entering the information age,PHS have emerged as a new catalyst for people's lives and urban development.Based on the Baidu Index,cold hot spot analysis and the Pearson correlation coefficient method were used to evaluate the spatiotemporal variation characteristics of the development of the quality of PHS at different levels in the three provinces of Northeast China(TPNC)during 2011–2022 and to characterize the influence of the system and factors.The results indicated that:1)temporally,PHS exhibits significant fluctuations,with an overall pattern of rapid increase followed by a gradual decline;2)spatially,PHS is marked by regional differentiation,with“three-core”dominance and a“cluster-like”distribution;3)systematically,the five major PHS systems generally exhibit an ascending and then a descending trend;4)in terms of influence,the socialization system serves as the core influence of PHS,with WeChat,JD.COM,and others are identified as the core influencing factors of subsystems.The findings of this study can provide scientific guidance for diversifying approaches to human settlements,promoting sustainable urban development,and revitalizing Northeast China.

SPATIO-TEMPORAL VARIATION CHARACTERISTICS OF EXTREMELY HEAVY PRECIPITATION FREQUENCY OVER SOUTH CHINA IN THE LAST 50 YEARS

This paper comprehensively studies the spatio-temporal characteristics of the frequency of extremely heavy precipitation events over South China by using the daily precipitation data of 110 stations during 1961 to 2008 and the extremely heavy precipitation thresholds determined for different stations by REOF, trend coefficients, linear trend, Mann-Kendall test and variance analysis. The results are shown as follows. The frequency distribution of extremely heavy precipitation is high in the middle of South China and low in the Guangdong coast and western Guangxi. There are three spatial distribution types of extremely heavy precipitation in South China. The consistent anomaly distribution is the main type. Distribution reversed between the east and the west and between the south and the north is also an important type. Extremely heavy precipitation events in South China mainly occurred in the summer-half of the year. Their frequency during this time accounts for 83.7% of the total frequency. In the 1960 s and 1980 s, extremely heavy precipitation events were less frequent while having an increasing trend from the late 1980 s. Their climatological tendency rates decrease in the central and rise in the other areas of South China, and on average the mean series also shows an upward but insignificant trend at all of the stations. South China's frequency of extremely heavy precipitation events can be divided into six major areas and each of them shows a different inter-annual trend and three of the representative stations experience abrupt changes by showing remarkable increases in terms of Mann-Kendall tests.

Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

Spatio-Temporal Air Pollutant Characterization for Urban Areas

Urban pollution has now become increasingly recognized as an important determinant of air pollution in developed countries. The effect of urban air pollution in developing countries, on the other hand, has not been adequately addressed in the data Spatio-temporal time series. Thus, this study was intended to characterize the effect of urbanization on air pollution for an urbanized Klang Valley, Malaysia using Spatio-temporal data from 2008 to 2017. The Air Pollution Index (API) data and local pollutant concentration were employed to establish the links between urban air pollution. The analysis will be supported by determining the source of pollutants during the study period using Principal Component Analysis (PCA). The study identified that Carbon monoxide (CO), Nitrogen Dioxide (NO2), and Ozone (O3) are the major air pollution that has contributed to degrading air quality in the Klang Valley due to the vehicles, combustion process, and industries.

Characteristics,Processes,and Causes of the Spatio-temporal Variabilities of the East Asian Monsoon System

Recent advances in the study of the characteristics, processes, and causes of spatio-temporal variabilities of the East Asian monsoon （EAM） system are reviewed in this paper. The understanding of the EAM system has improved in many aspects： the basic characteristics of horizontal and vertical structures, the annual cycle of the East Asian summer monsoon （EASM） system and the East Asian winter monsoon （EAWM） system, the characteristics of the spatio-temporal variabilities of the EASM system and the EAWM system, and especially the multiple modes of the EAM system and their spatio-temporal variabilities. Some new results have also been achieved in understanding the atmosphere-ocean interaction and atmosphere-land interaction processes that affect the variability of the EAM system. Based on recent studies, the EAM system can be seen as more than a circulation system, it can be viewed as an atmosphere-ocean-land coupled system, namely, the EAM climate system. In addition, further progress has been made in diagnosing the internal physical mechanisms of EAM climate system variability, especially regarding the characteristics and properties of the East Asia-Pacific （EAP） teleconnection over East Asia and the North Pacific, the ＂Silk Road＂ teleconnection along the westerly jet stream in the upper troposphere over the Asian continent, and the dynamical effects of quasi-stationary planetary wave activity on EAM system variability. At the end of the paper, some scientific problems regarding understanding the EAM system variability are proposed for further study.

Analysis of Characteristics of Spatio-temporal Evolution of Land Use in Inhabited Islands of Pearl River Estuary

Under the support of the remote sensing and geographical information system(GIS) techniques,we acquire the land use data in 1990 and 2008 regarding 6 inhabited islands,namely Longxue Island,Hengmen Island,Weiyuan Island,Qi'ao Island,Hengqin Island and Gaolan Island in Pearl River Estuary.By using dynamic degree of land use,land use change intensity,relative change rate and other indicators,we conduct quantitative description,and thus quantitatively and qualitatively analyse characteristics of temporal evolution and law of spatial pattern change concerning land use of each island.The study indicates that in the period 1990-2008,the area of construction land and water in 6 islands increased,while the area of agricultural land and unused land increased in some islands and decreased in others.The land use change shows spatial disparity;the holistic land use change degree in Hengmen Island is higher than that of other islands;the dynamic degree of land use,intensity of land use,and relative change rate differ in different islands.

Spatio-temporal Evolution Characteristics and Driving Mechanism of the New Infrastructure Construction Development Potential in China

With the advent of the era of big data and artificial intelligence, new infrastructure construction(NIC) has attracted the attention of many countries. The development of NIC provides an opportunity to bridge the digital divide and narrow the regional gap,providing continuous impetus to further promote economic development. Here, we considered 31 provincial-level administrative units in China(not including Hong Kong, Macao, and Taiwan of China due to data unavailable) and established comprehensive evaluation indicators for the development potential of NIC. Afterward, we used the entropy-weight TOPSIS model to determine the development potential of NIC and analyze its spatio-temporal evolution characteristics. Furthermore, the GeoDetector model was applied to explore the driving mechanism of the NIC development potential. The conclusions were as follows: (1) The Chinese NIC development potential is generally low. The eastern China was the region with the highest development potential year by year, while the development potential in the central China was found to be in an accelerating phase. (2) The evolution of the Chinese NIC development potential’s spatial pattern has been characterized by an inland extension and coastal agglomeration. Moreover, we identified a superior development zone, a rising development zone, an inferior development zone, and a declining development zone. (3) The scope of Chinese NIC development potential agglomeration areas has gradually expanded and its degree has gradually deepened. The range of high-value agglomeration in eastern area gradually expanded and its degree gradually deepened. (4) Investment in innovative talents appears as the core factor affecting the Chinese NIC development potential. Whether acting alone or synergistically with other factors, its promoting effect on Chinese NIC development potential is the strongest.

Spatio-Temporal Characteristics of Standardized Precipitation Index in the Taihu Basin during 1951-2000

Spatial and temporal characteristics of standardized precipitation index （SPI）, which is widely used for drought/flood monitoring, are investigated in this study. The purpose is to obtain a reasonable primary scheme of zoning on the basis of drought/ wetness conditions in the study area. Spatio-temporal distributions of SPI with the time scales of 3 months and 12 months are investigated with the datasets of precipitation in the Taihu basin during past decades （1951-2000）. Results indicate that SPI series of 3 months show random fluctuation while that of 12 months behaves like I/f noise. SPI series of 3 months show little trend while that of 12 months show significant trend at several stations. Drought magnitude （DM） is also estimated on the basis of SPI values to assess drought condition. No trend is detected in DMs with time scales of both 3 months and 12 months. Spatial variability of DM is analyzed by mapping the DM with 12 months for extreme drought and wetness, and regional characteristics are analyzed for DM.

Spatio-temporal model for soil characteristic of reclamation land

The development of spatio-temporal data model is introduced. According to the soil characteristic of reclamation land, we adopt the base state with amendments model of multi-layer raster to organize the spatio-temporal data, using the combined data structure on linear quadtree and linear octree to code. The advantage of this model is that it can easily obtain the information of certain layer and integratedly analyze the data with other methods. Then, the methods of obtain and analyses are introduced. The method can provide a tool for the research of the soil characteristic change and spatial distribution in reclamation land.

Optimised CNN Architectures for Handwritten Arabic Character Recognition

Handwritten character recognition is considered challenging compared with machine-printed characters due to the different human writing styles.Arabic is morphologically rich,and its characters have a high similarity.The Arabic language includes 28 characters.Each character has up to four shapes according to its location in the word(at the beginning,middle,end,and isolated).This paper proposed 12 CNN architectures for recognizing handwritten Arabic characters.The proposed architectures were derived from the popular CNN architectures,such as VGG,ResNet,and Inception,to make them applicable to recognizing character-size images.The experimental results on three well-known datasets showed that the proposed architectures significantly enhanced the recognition rate compared to the baseline models.The experiments showed that data augmentation improved the models’accuracies on all tested datasets.The proposed model outperformed most of the existing approaches.The best achieved results were 93.05%,98.30%,and 96.88%on the HIJJA,AHCD,and AIA9K datasets.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Recent advances in spatio-temporally controllable systems for management of glioma

Malignant glioma remains one of the most aggressive intracranial tumors with devastating clinical outcomes despite the great advances in conventional treatment approaches,including surgery and chemotherapy.Spatio-temporally controllable approaches to glioma are now being actively investigated due to the preponderance,including spatio-temporal adjustability,minimally invasive,repetitive properties,etc.External stimuli can be readily controlled by adjusting the site and density of stimuli to exert the cytotoxic on glioma tissue and avoid undesired injury to normal tissues.It is worth noting that the removability of external stimuli allows for on-demand treatment,which effectively reduces the occurrence of side effects.In this review,we highlight recent advancements in drug delivery systems for spatio-temporally controllable treatments of glioma,focusing on the mechanisms and design principles of sensitizers utilized in these controllable therapies.Moreover,the potential challenges regarding spatio-temporally controllable therapy for glioma are also described,aiming to provide insights into future advancements in this field and their potential clinical applications.

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating method.The variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared thermometer.The addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni alloys.The images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed camera.The solidification rate of Cu-Ni alloys,with the addition of Co elements,was explored.Finally,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 alloys.The experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification phase.In the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling degree.Furthermore,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.