For exploring the aftershock occurrence process of the 2008 Wenchuan strong earthquake, the spatio-temporal point pattern analysis method is employed to study the sequences of aflershocks with magnitude M≥4.0, M≥4.5...For exploring the aftershock occurrence process of the 2008 Wenchuan strong earthquake, the spatio-temporal point pattern analysis method is employed to study the sequences of aflershocks with magnitude M≥4.0, M≥4.5, and M≥5.0. It is found that these data exhibit the spatio-temporal clustering on a certain distance scale and on a certain time scale. In particular, the space-time interaction obviously strengthens when the distance is less than 60 km and the time is less than 260 h for the first two aftershock sequences; however, it becomes strong when the distance scale is less than 80 km and the time scale is less than 150 h for the last aftershock sequence. The completely spatial randomness analysis on the data regardless of time component shows that the spatial clustering of the aftershocks gradually strengthens on the condition that the distance is less than 60 km. The results are valuable for exploring the occurrence rules of the Wenchuan strong earthquake and for predicting the aftershocks.展开更多
Drought, which is one of the most frequently occurring severe hazards with long time scales and cov- ering wide geographical areas, is a natural phenomenon resulting in significant economic losses in agriculture and i...Drought, which is one of the most frequently occurring severe hazards with long time scales and cov- ering wide geographical areas, is a natural phenomenon resulting in significant economic losses in agriculture and industry. Drought is caused by an imbalance between the inputs of and the demand for water which is insufficient to meet the demands of human activities and the eco-environment. As a major arid and semi-arid area and an important agricultural region in Northwest China, North Xinjiang （NX） shows great vulnerability to drought. In this paper, the characteristics of inter-annual and seasonal drought were analyzed in terms of drought occurrence and drought coverage, by using the composite index of meteorological drought and the data of daily precipitation, air temperature, wind speed, relative humidity and sunshine duration from 38 meteorological stations during the period 1961-2012. Trend analysis, wavelet analysis and empirical orthogonal function were also applied to investigate change trend, period and regional characteristics, respectively. In NX, annual and seasonal drought occurrence and drought coverage all showed a decreasing trend that was most significant in winter （with rates of-0.26 month/10a and -15.46%, respectively）, and drought occurrence in spring and summer were more frequent than that in autumn and winter. Spatially, drought was severe in eastern regions but mild in western regions of NX. Annual and seasonal drought occurrence at 38 meteorological stations displayed decreasing trends and were most significant in ＂Shi- hezi-Urumqi-Changji＂, which can help to alleviate severe drought hazards for local agricultural production and improve human livelihood. NX can be approximately classified into three sub-regions （severe drought region, moder- ate drought region and mild drought region）, which were calculated from annual drought frequencies. The cross wavelet transform suggested that SOl （Southern Oscillation Index）, AOI （Arctic Oscillation Index）, AAOI （Antarctic Oscillation Index）, PAOI （Pacific/North American Oscillation Index） and NAOI （North Atlantic Oscillation Index） have significant correlation with the variation of drought occurrence in NX. To prevent and mitigate the occurrence of drought disasters in NX, agricultural and government managers should pay more attention to those drought events that occur in spring and summer.展开更多
Border area is not only an important gateway for inland opening-up,but also an important part of completing the building of a moderately prosperous society and optimizing national urban spatial pattern in China.Due to...Border area is not only an important gateway for inland opening-up,but also an important part of completing the building of a moderately prosperous society and optimizing national urban spatial pattern in China.Due to the location,natural resources endowment,and traffic accessibility,the urbanization speed is relatively slow in border areas.Therefore,it is a special area that needs to pay close attention to,especially under the background of the Belt and Road Initiative and China's regional coordinated development program.Based on the county-level data from 2000 to 2015,this paper tries to analyze the spatio-temporal pattern of urbanization in 134 border counties,and applies geographical detector method to study the driving forces of urbanization in border areas.Conclusions are as follows:(1)From 2000 to 2015,urbanization rate in border areas has been lower than the national average,and the gap has been widening.Some border counties in southern Xinjiang,Tibet,northeast of Inner Mongolia,and Yunnan,are even facing the problem of population loss.(2)In the same period,urbanization rate in the northwestern and southwestern border is low,while their urbanization rate grows relatively faster comparing with other border counties;urbanization rate in Tibet border is the lowest and grows relatively slowly;urbanization rate in the northeastern and northern border is slightly higher,but it grows slowly or even stagnates.(3)Transportation and industry are the important driving forces of urbanization in border areas,while the driving forces of market is relatively weak.And there are obvious mutual reinforcements among the driving forces,while the effort and explanatory power of resource force increases obviously after interaction.(4)Urbanization rate in the northwestern and southwestern border areas grows relatively fast,with industrial force and transportation force,market force and administrative force as the main driving forces respectively.Tibet border area has the lowest urbanization rate and growth rate,as the driving force of urbanization with strong contribution has not yet formed in Tibet.In the northeastern and northern border areas,the contribution of transportation force to urbanization is greater than other forces,and its interaction with market and industry has obvious effects.展开更多
The dockless bike-sharing system has rapidly expanded worldwide and has been widely used as an intermodal transport to connect with public transportation.However,higher flexibility may cause an imbalance between suppl...The dockless bike-sharing system has rapidly expanded worldwide and has been widely used as an intermodal transport to connect with public transportation.However,higher flexibility may cause an imbalance between supply and demand during daily operation,especially around the metro stations.A stable and efficient rebalancing model requires spatio-temporal usage patterns as fundamental inputs.Therefore,understanding the spatio-temporal patterns and correlates is important for optimizing and rescheduling bike-sharing systems.This study proposed a dynamic time warping distance-based two-dimensional clustering method to quantify spatio-temporal patterns of dockless shared bikes in Wuhan and further applied the multiclass explainable boosting machine to explore the main related factors of these patterns.The results found six patterns on weekdays and four patterns on weekends.Three patterns show the imbalance of arrival and departure flow in the morning and evening peak hours,while these phenomena become less intensive on weekends.Road density,living service facility density and residential density are the top influencing factors on both weekdays and weekends,which means that the comprehensive impact of built-up environment attraction,facility suitability and riding demand leads to the different usage patterns.The nonlinear influence universally exists,and the probability of a certain pattern varies in different value ranges of variables.When the densities of living facilities and roads are moderate and the relationship between job and housing is relatively balanced,it can effectively promote the balanced usage of dockless shared bikes while maintaining high riding flow.The spatio-temporal patterns can identify the associated problems such as imbalance or lack of users,which could be mitigated by corresponding solutions.The relative importance and nonlinear effects help planners prioritize strategies and identify effective ranges on different patterns to promote the usage and efficiency of the bike-sharing system.展开更多
In this study,we employed a number of geospatial techniques to examine the spatiotemporal patterns and changes of environmental attitudes and place attachment values in the Gauteng province of South Africa.The data we...In this study,we employed a number of geospatial techniques to examine the spatiotemporal patterns and changes of environmental attitudes and place attachment values in the Gauteng province of South Africa.The data were obtained from the Gauteng City Region Observatory’s Quality of Life Survey collected at three separate points in time,namely 2013,2015,and 2017.Results indicated that wards(smallest administrative and analysis units)located on the urban periphery of Gauteng,which are generally less affluent,largely held more negative environmental attitudes and place attachment values during the three time periods.In contrast,centrally located wards,which are generally more affluent,expressed more positive environmental attitudes but less place attachment values,especially in 2017.The findings of this research not only highlight the complex spatio-temporal distribution of environmental attitudes and place attachment values throughout Gauteng but also empha-size the need for spatially targeted state interventions for future environmental planning within the province.展开更多
Hengduan Mountains offer land space for a variety of ecological services. However, the sustainable development and management of land space has been challenged by increased human activities in recent years. This paper...Hengduan Mountains offer land space for a variety of ecological services. However, the sustainable development and management of land space has been challenged by increased human activities in recent years. This paper performs the spatial pattern analysis of the quantitative and structural changes of various landscapes at different altitudes, and uses the land use data in 1990, 2000, 2010 and 2015 to reveal how various land patterns have changed. The results show that, within the production-living-ecological space schema, the ecological space dominates Hengduan Mountains, while the production and living space was mainly distributed in south region. During 1990-2015, the production-living-ecological spatial changes had been gradually accelerated and the regional differences had become more prominent. The agricultural production space had continuously decreased by 1132.31 km^2, and the industrial and mining production space had rapidly increased by 281.4 km^2 during 1990-2015. The living space had steadily increased, and the ecological space had increased with fluctuations. The land space pattern in Hengduan Mountains was greatly restricted by the terrain, such as altitude and slope. The implementations of China Western Development Strategy and the Returning Farmland to Forest Program had favorably promoted the changes of land spatial pattern in Hengduan Mountains.展开更多
In recent years,tourism has emerged as a significant driver of economic development in China’s border regions.The study utilizes various methods,such as the super-efficiency SBM model,spatial variability,cold and hot...In recent years,tourism has emerged as a significant driver of economic development in China’s border regions.The study utilizes various methods,such as the super-efficiency SBM model,spatial variability,cold and hot spot analysis,and Geo-Detector approach,to measure and describe the spatial and temporal evolution patterns of land border tourism efficiency and its influencing factors.The findings reveal that the Dai autonomous prefecture of Xishuangbanna has the highest border tourism efficiency of 1.6207,while Ngari prefecture has the lowest tourism efficiency with a value of only 0.0365 at the prefecture level during the period 2010-2019.The southwest and northwest regions of China are high-and low-level agglomeration areas respectively,indicating varying levels of border tourism development.Additionally,the study identifies an upward trend in China’s border tourism efficiency from 2010-2019.The southwest region emerges as a hotspot and the most active region,while the northwest and northeast regions are considered cold spots with ample room for improvement.Furthermore,the density of transportation facilities,national vulnerability,cultural proximity,the number of border ports,and market opportunity are crucial factors influencing the spatial and temporal pattern of border tourism efficiency in China.展开更多
With the rapid economic development during the last 30 years in China, more and more disparities have emerged among different regions. It has been one of the hot topics in the fields of physical geography and economic...With the rapid economic development during the last 30 years in China, more and more disparities have emerged among different regions. It has been one of the hot topics in the fields of physical geography and economic geography, and also has been the task for Chinese government to handle. Nevertheless, to quantitatively assess the impacts of physio-geographical patterns （PGP） on the regional development disparity has been ignored for a long time. In this paper, a quantitative method was adopted to assess the marginal effects of the PGP on spatio-temporal disparity using the partial determination coefficients. The paper described the construction of the evaluation model step by step following its key scientific thinking. Total GDP, per capita GDP, primary industrial output value and secondary industrial output value were employed in this study as the indicators to reflect the impacts of PGP on the regional development disparity. Based on the evaluation methods built by researchers, this study firstly analyzed the temporal impacts of the PGP on spatio-temporal disparity of the regional development in China during the past 50 years, and then explained the spatial differences at each development stage. The results show that the spatio-temporal disparity in China is highly related to the PGP, and that the marginal contribution rate could be employed as an effective way to quantitatively assess the impact of the PGP on spatio-temporal disparity of the regional development.展开更多
Improving comprehensive agricultural productivity is an important measure to realize agricultural modernization.Based on the data from Jilin Statistical Yearbook,this study analyzed the spatial and temporal characteri...Improving comprehensive agricultural productivity is an important measure to realize agricultural modernization.Based on the data from Jilin Statistical Yearbook,this study analyzed the spatial and temporal characteristics of comprehensive agricultural productivity discrepancy in the main agricultural production areas of Jilin Province,China.The comprehensive agricultural productivity of 25 county-level administrative units were evaluated by a comprehensive index system based on five aspects which included 20 indicators from 2004 to 2017.The pattern of the discrepancy was analyzed by the spatial differentiation indices and spatial convergence theory.The results were as follows:1) the overall comprehensive agricultural productivity was in a ’W-type’ rising trend;2) the discrepancy was in’inverted W-type’ trend;3) the spatial distribution characteristics were mainly discrete plaque and ’inverted V-type’;4) the formation of differences was forced by a combination of internal and external driving forces.Our study demonstrates the effectiveness of rising agricultural productivity and the level of economic and social developments in different counties in Jilin Province.展开更多
Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation e...Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation efficiency, cluttered backgrounds and intro-variability among same type of actions. Spatio-temporal interest point （STIP） based methods have shown promising results to tackle human action classification in complex scenes efficiently. However, the state-of-the-art works typically utilize bag-of-visual words （BoVW） model which only focuses on the word distribution of STIPs and ignore the distinctive character of word structure. In this paper, the distribution of STIPs is organized into a salient directed graph, which reflects salient motions and can be divided into a time salient directed graph and a space salient directed graph, aiming at adding spatio-temporal discriminant to BoVW. Generally speaking, both salient directed graphs are constructed by labeled STIPs in pairs. In detail, the ＂directional co-occurrence＂ property of different labeled pairwise STIPs in same frame is utilized to represent the time saliency, and the space saliency is reflected by the ＂geometric relationships＂ between same labeled pairwise STIPs across different frames. Then, new statistical features namely the Time Salient Pairwise feature （TSP） and the Space Salient Pairwise feature （SSP） are designed to describe two salient directed graphs, respectively. Experiments are carried out with a homogeneous kernel SVM classifier, on four challenging datasets KTH, ADL and UT-Interaction. Final results confirm the complementary of TSP and SSP, and our multi-cue representation TSP ＋ SSP ＋ BoVW can properly describe human actions with large intro-variability in real-time.展开更多
Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-de...Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.展开更多
Nowadays, wildlife road mortality is acknowledged as a main source of threatening long-term survival of wildlife. This paper as the first to analysis wild life vehicle collisions in Iran, aims to reconstruct and inter...Nowadays, wildlife road mortality is acknowledged as a main source of threatening long-term survival of wildlife. This paper as the first to analysis wild life vehicle collisions in Iran, aims to reconstruct and interpret the spatio-temporal patterns of WVCs on Asiaei highway in Golestan National Park (GNP). With the collaboration of environmental protection department of GNP, we identified about 1900 WVC Records involving 34 different species of mammals, birds, reptiles and amphibians between 2004 and 2013. Mammals were involved in more than 50% of overall WVCs, among which wild boar (Sus scrofa), Golden Jackal (Canis aureus), Red Fox (Vulpes vulpes), hedgehog (Erinaceus concolor), stone marten (Martes foina) and porcupine (Hystrix indica) were involved in more than 90% of mammals’ mortalities;So, we focused on analyzing spatio-temporal pattern of vehicle collisions of these six mammal species. During the study period, these species have undergone 95% increase in road mortalities, averagely. Detailed temporal analyses exhibited an increasing trend of road mortalities from spring to summer and then a reducing one to late winter. It was shown that a large number of collisions occurred in holiday periods when recreational trips considerably increased the traffic volume of Asiaei highway. Preliminary inspection of spatial patterns using Kernel density analysis revealed six collision hotspots, mostly located in the road bends with densely forested land cover on both sides;the promenades along the road seemed to play a significant role too. Scale dependency analyses of collision patterns, demonstrated clustering pattern at micro scales less than 10 km, randomness at meso scales 10 - 20 km and both regularity and clustering at macro scales more than 20 km. This paper suggests that road mortality of common species in GNP is a momentous issue, which needs to be considered by relevant governmental and public organizations. We also emphasize that the analyses of spatial and temporal patterns of WVCs are fundamentals to plan for mitigate wildlife road mortality.展开更多
In crime science, understanding the dynamics and interactions between crime events is crucial for comprehending the underlying factors that drive their occurrences. Nonetheless, gaining access to detailed spatiotempor...In crime science, understanding the dynamics and interactions between crime events is crucial for comprehending the underlying factors that drive their occurrences. Nonetheless, gaining access to detailed spatiotemporal crime records from law enforcement faces significant challenges due to confidentiality concerns. In response to these challenges, this paper introduces an innovative analytical tool named “stppSim,” designed to synthesize fine-grained spatiotemporal point records while safeguarding the privacy of individual locations. By utilizing the open-source R platform, this tool ensures easy accessibility for researchers, facilitating download, re-use, and potential advancements in various research domains beyond crime science.展开更多
Understanding crop patterns and their changes on regional scale is a critical re- quirement for projecting agro-ecosystem dynamics. However, tools and methods for mapping the distribution of crop area and yield are st...Understanding crop patterns and their changes on regional scale is a critical re- quirement for projecting agro-ecosystem dynamics. However, tools and methods for mapping the distribution of crop area and yield are still lacking. Based on the cross-entropy theory, a spatial production allocation model （SPAM） has been developed for presenting spa- tio-temporal dynamics of maize cropping system in Northeast China during 1980-2010. The simulated results indicated that （1） maize sown area expanded northwards to 48~N before 2000, after that the increased sown area mainly occurred in the central and southern parts of Northeast China. Meanwhile, maize also expanded eastwards to 127°E and lower elevation （less than 100 m） as well as higher elevation （mainly distributed between 200 m and 350 m）; （2） maize yield has been greatly promoted for most planted area of Northeast China, espe- cially in the planted zone between 42°N and 48°N, while the yield increase was relatively homogeneous without obvious longitudinal variations for whole region; （3） maize planting density increased gradually to a moderately high level over the investigated period, which reflected the trend of aggregation of maize cultivation driven by market demand.展开更多
Attended collection and delivery points are vital components of ‘last-mile logistics’.Based on point of interest(POI) data for Cainiao Stations and China Post stations in Changsha City, China, this paper provides a ...Attended collection and delivery points are vital components of ‘last-mile logistics’.Based on point of interest(POI) data for Cainiao Stations and China Post stations in Changsha City, China, this paper provides a detailed exploration of the basic features, spatial distribution, and location influencing factors of attended collection and delivery points.Specifically, analyses of the types, service objects and location distributions of the attended collection and delivery points alongside a discussion of their spatial pattern and influencing factors provides a reference for their general geographic layout and characteristics.The findings of this study indicate that: 1) The main mode of operation of attended collection and delivery points is franchises, with other modes of operation rely on supermarkets and other individual shop types.2) The main service targets of attended collection and delivery points are communities, schools, and businesses, followed by townships, enterprises, scenic spots, and administrative units.3) Approximately 77.44% of the attended collection and delivery points are located near the exits of service areas;others are situated in the centre of the service areas.For the Cainiao Stations, 80% are located within 125 m of the exit;for the China Post stations, 80% are located within 175 m of the exit.4) The spatial distribution of the attended collection and delivery points in Changsha is unbalanced, with ‘more centre and fewer surrounding’.The centre is an ‘inverted triangle’, and the edge is an ‘orphan’, showing a northwest-southeast orientation and symmetrical along the axis.The layout of the attended collection and delivery points forms three core areas, and the number of sites decreases with the distance from the core.5) The number and distribution of the attended collection and delivery points are strongly consistent with the regional economic development level, population, and roadway system traffic convenience.Most attended collection and delivery points are on residential, scientific and educational, and commercial and financial land.展开更多
The relationship between fractal point pattern modeling and statistical methods of pa- rameter estimation in point-process modeling is reviewed. Statistical estimation of the cluster fractal dimension by using Ripley...The relationship between fractal point pattern modeling and statistical methods of pa- rameter estimation in point-process modeling is reviewed. Statistical estimation of the cluster fractal dimension by using Ripley＇s K-function has advantages in comparison with the more commonly used methods of box-counting and cluster fractal dimension estimation because it corrects for edge effects, not only for rectangular study areas but also for study areas with curved boundaries determined by re- gional geology. Application of box-counting to estimate the fractal dimension of point patterns has the disadvantage that, in general, it is subject to relatively strong ＂roll-off＂ effects for smaller boxes. Point patterns used for example in this paper are mainly for gold deposits in the Abitibi volcanic belt on the Canadian Shield. Additionally, it is proposed that, worldwide, the local point patterns of podiform Cr, volcanogenic massive sulphide and porphyry copper deposits, which are spatially distributed within irregularly shaped favorable tracts, satisfy the fractal clustering model with similar fractal dimensions. The problem of deposit size （metal tonnage） is also considered. Several examples are provided of cases in which the Pareto distribution provides good results for the largest deposits in metal size-frequency distribution modeling.展开更多
Most of the exist action recognition methods mainly utilize spatio-temporal descriptors of single interest point while ignoring their potential integral information, such as spatial distribution information. By combin...Most of the exist action recognition methods mainly utilize spatio-temporal descriptors of single interest point while ignoring their potential integral information, such as spatial distribution information. By combining local spatio-temporal feature and global positional distribution information(PDI) of interest points, a novel motion descriptor is proposed in this paper. The proposed method detects interest points by using an improved interest point detection method. Then, 3-dimensional scale-invariant feature transform(3D SIFT) descriptors are extracted for every interest point. In order to obtain a compact description and efficient computation, the principal component analysis(PCA) method is utilized twice on the 3D SIFT descriptors of single frame and multiple frames. Simultaneously, the PDI of the interest points are computed and combined with the above features. The combined features are quantified and selected and finally tested by using the support vector machine(SVM) recognition algorithm on the public KTH dataset. The testing results have showed that the recognition rate has been significantly improved and the proposed features can more accurately describe human motion with high adaptability to scenarios.展开更多
Based on spatio-temporal correlativity analysis method, the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented. The asynchronous correlative characteristics o...Based on spatio-temporal correlativity analysis method, the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented. The asynchronous correlative characteristics of gas migration in working face airflow direction are qualitatively analyzed. The calculation method of asynchronous correlation delay step and the prediction and inversion formulas of gas concentration changing with time and space after gas emission in the air return roadway are provided. By calculating one hundred and fifty groups of gas sensors data series from a coal mine which have the theoretical correlativity, the correlative coefficient values range of eight kinds of data anomaly is obtained. Then the gas moni- toring data anomaly identification algorithm based on spatio-temporal correlativity analysis is accordingly presented. In order to improve the efficiency of analysis, the gas sensors code rules which can express the spatial topological relations are sug- gested. The experiments indicate that methods presented in this article can effectively compensate the defects of methods based on a single gas sensor monitoring data.展开更多
Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topologi...Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.展开更多
In order to detect the traffic pattern of moving objects in the city more accurately and quickly, a parallel algorithm for detecting traffic patterns using stay points and moving features is proposed. First, the featu...In order to detect the traffic pattern of moving objects in the city more accurately and quickly, a parallel algorithm for detecting traffic patterns using stay points and moving features is proposed. First, the features of the stay points in different traffic patterns are extracted, that is, the stay points of various traffic patterns are identified, respectively, and the clustering algorithm is used to mine the unique features of the stop points to different traffic patterns. Then, the moving features in different traffic patterns are extracted from a trajectory of a moving object, including the maximum speed, the average speed, and the stopping rate. A classifier is constructed to predict the traffic pattern of the trajectory using the stay points and moving features. Finally, a parallel algorithm based on Spark is proposed to detect traffic patterns. Experimental results show that the stay points and moving features can reflect the difference between different traffic modes to a greater extent, and the detection accuracy is higher than those of other methods. In addition, the parallel algorithm can increase the speed of identifying traffic patterns.展开更多
基金supported by the Key Project of Chinese National Programs for Fun-damental Research and Development (973 program) (2008CB425704)
文摘For exploring the aftershock occurrence process of the 2008 Wenchuan strong earthquake, the spatio-temporal point pattern analysis method is employed to study the sequences of aflershocks with magnitude M≥4.0, M≥4.5, and M≥5.0. It is found that these data exhibit the spatio-temporal clustering on a certain distance scale and on a certain time scale. In particular, the space-time interaction obviously strengthens when the distance is less than 60 km and the time is less than 260 h for the first two aftershock sequences; however, it becomes strong when the distance scale is less than 80 km and the time scale is less than 150 h for the last aftershock sequence. The completely spatial randomness analysis on the data regardless of time component shows that the spatial clustering of the aftershocks gradually strengthens on the condition that the distance is less than 60 km. The results are valuable for exploring the occurrence rules of the Wenchuan strong earthquake and for predicting the aftershocks.
基金supported by International Science & Technology Cooperation Program of China (2010DFA92720)the Scientific Innovation Research Project for Graduate Students of XinjiangSoil Science Key Discipline Project of Xinjiang Uygur Autonomous Region
文摘Drought, which is one of the most frequently occurring severe hazards with long time scales and cov- ering wide geographical areas, is a natural phenomenon resulting in significant economic losses in agriculture and industry. Drought is caused by an imbalance between the inputs of and the demand for water which is insufficient to meet the demands of human activities and the eco-environment. As a major arid and semi-arid area and an important agricultural region in Northwest China, North Xinjiang （NX） shows great vulnerability to drought. In this paper, the characteristics of inter-annual and seasonal drought were analyzed in terms of drought occurrence and drought coverage, by using the composite index of meteorological drought and the data of daily precipitation, air temperature, wind speed, relative humidity and sunshine duration from 38 meteorological stations during the period 1961-2012. Trend analysis, wavelet analysis and empirical orthogonal function were also applied to investigate change trend, period and regional characteristics, respectively. In NX, annual and seasonal drought occurrence and drought coverage all showed a decreasing trend that was most significant in winter （with rates of-0.26 month/10a and -15.46%, respectively）, and drought occurrence in spring and summer were more frequent than that in autumn and winter. Spatially, drought was severe in eastern regions but mild in western regions of NX. Annual and seasonal drought occurrence at 38 meteorological stations displayed decreasing trends and were most significant in ＂Shi- hezi-Urumqi-Changji＂, which can help to alleviate severe drought hazards for local agricultural production and improve human livelihood. NX can be approximately classified into three sub-regions （severe drought region, moder- ate drought region and mild drought region）, which were calculated from annual drought frequencies. The cross wavelet transform suggested that SOl （Southern Oscillation Index）, AOI （Arctic Oscillation Index）, AAOI （Antarctic Oscillation Index）, PAOI （Pacific/North American Oscillation Index） and NAOI （North Atlantic Oscillation Index） have significant correlation with the variation of drought occurrence in NX. To prevent and mitigate the occurrence of drought disasters in NX, agricultural and government managers should pay more attention to those drought events that occur in spring and summer.
基金National Natural Science Foundation of China,No.41871120Priority Research Program of Chinese Academy of Sciences,No.XDA20010102。
文摘Border area is not only an important gateway for inland opening-up,but also an important part of completing the building of a moderately prosperous society and optimizing national urban spatial pattern in China.Due to the location,natural resources endowment,and traffic accessibility,the urbanization speed is relatively slow in border areas.Therefore,it is a special area that needs to pay close attention to,especially under the background of the Belt and Road Initiative and China's regional coordinated development program.Based on the county-level data from 2000 to 2015,this paper tries to analyze the spatio-temporal pattern of urbanization in 134 border counties,and applies geographical detector method to study the driving forces of urbanization in border areas.Conclusions are as follows:(1)From 2000 to 2015,urbanization rate in border areas has been lower than the national average,and the gap has been widening.Some border counties in southern Xinjiang,Tibet,northeast of Inner Mongolia,and Yunnan,are even facing the problem of population loss.(2)In the same period,urbanization rate in the northwestern and southwestern border is low,while their urbanization rate grows relatively faster comparing with other border counties;urbanization rate in Tibet border is the lowest and grows relatively slowly;urbanization rate in the northeastern and northern border is slightly higher,but it grows slowly or even stagnates.(3)Transportation and industry are the important driving forces of urbanization in border areas,while the driving forces of market is relatively weak.And there are obvious mutual reinforcements among the driving forces,while the effort and explanatory power of resource force increases obviously after interaction.(4)Urbanization rate in the northwestern and southwestern border areas grows relatively fast,with industrial force and transportation force,market force and administrative force as the main driving forces respectively.Tibet border area has the lowest urbanization rate and growth rate,as the driving force of urbanization with strong contribution has not yet formed in Tibet.In the northeastern and northern border areas,the contribution of transportation force to urbanization is greater than other forces,and its interaction with market and industry has obvious effects.
基金supported by the National Key Research and Development Program of China[grant number 2017YFB0503601]。
文摘The dockless bike-sharing system has rapidly expanded worldwide and has been widely used as an intermodal transport to connect with public transportation.However,higher flexibility may cause an imbalance between supply and demand during daily operation,especially around the metro stations.A stable and efficient rebalancing model requires spatio-temporal usage patterns as fundamental inputs.Therefore,understanding the spatio-temporal patterns and correlates is important for optimizing and rescheduling bike-sharing systems.This study proposed a dynamic time warping distance-based two-dimensional clustering method to quantify spatio-temporal patterns of dockless shared bikes in Wuhan and further applied the multiclass explainable boosting machine to explore the main related factors of these patterns.The results found six patterns on weekdays and four patterns on weekends.Three patterns show the imbalance of arrival and departure flow in the morning and evening peak hours,while these phenomena become less intensive on weekends.Road density,living service facility density and residential density are the top influencing factors on both weekdays and weekends,which means that the comprehensive impact of built-up environment attraction,facility suitability and riding demand leads to the different usage patterns.The nonlinear influence universally exists,and the probability of a certain pattern varies in different value ranges of variables.When the densities of living facilities and roads are moderate and the relationship between job and housing is relatively balanced,it can effectively promote the balanced usage of dockless shared bikes while maintaining high riding flow.The spatio-temporal patterns can identify the associated problems such as imbalance or lack of users,which could be mitigated by corresponding solutions.The relative importance and nonlinear effects help planners prioritize strategies and identify effective ranges on different patterns to promote the usage and efficiency of the bike-sharing system.
文摘In this study,we employed a number of geospatial techniques to examine the spatiotemporal patterns and changes of environmental attitudes and place attachment values in the Gauteng province of South Africa.The data were obtained from the Gauteng City Region Observatory’s Quality of Life Survey collected at three separate points in time,namely 2013,2015,and 2017.Results indicated that wards(smallest administrative and analysis units)located on the urban periphery of Gauteng,which are generally less affluent,largely held more negative environmental attitudes and place attachment values during the three time periods.In contrast,centrally located wards,which are generally more affluent,expressed more positive environmental attitudes but less place attachment values,especially in 2017.The findings of this research not only highlight the complex spatio-temporal distribution of environmental attitudes and place attachment values throughout Gauteng but also empha-size the need for spatially targeted state interventions for future environmental planning within the province.
基金Major State Basic Research Development Program of China,No.2015CB452706
文摘Hengduan Mountains offer land space for a variety of ecological services. However, the sustainable development and management of land space has been challenged by increased human activities in recent years. This paper performs the spatial pattern analysis of the quantitative and structural changes of various landscapes at different altitudes, and uses the land use data in 1990, 2000, 2010 and 2015 to reveal how various land patterns have changed. The results show that, within the production-living-ecological space schema, the ecological space dominates Hengduan Mountains, while the production and living space was mainly distributed in south region. During 1990-2015, the production-living-ecological spatial changes had been gradually accelerated and the regional differences had become more prominent. The agricultural production space had continuously decreased by 1132.31 km^2, and the industrial and mining production space had rapidly increased by 281.4 km^2 during 1990-2015. The living space had steadily increased, and the ecological space had increased with fluctuations. The land space pattern in Hengduan Mountains was greatly restricted by the terrain, such as altitude and slope. The implementations of China Western Development Strategy and the Returning Farmland to Forest Program had favorably promoted the changes of land spatial pattern in Hengduan Mountains.
基金National Natural Science Foundation of China,No.42201311Natural Science Foundation of Shandong Province,No.ZR2022QD132+1 种基金Fundamental Research Funds for the Central Universities,No.202013012Rural Revitalization Project of Ocean University of China,No.ZX2024007。
文摘In recent years,tourism has emerged as a significant driver of economic development in China’s border regions.The study utilizes various methods,such as the super-efficiency SBM model,spatial variability,cold and hot spot analysis,and Geo-Detector approach,to measure and describe the spatial and temporal evolution patterns of land border tourism efficiency and its influencing factors.The findings reveal that the Dai autonomous prefecture of Xishuangbanna has the highest border tourism efficiency of 1.6207,while Ngari prefecture has the lowest tourism efficiency with a value of only 0.0365 at the prefecture level during the period 2010-2019.The southwest and northwest regions of China are high-and low-level agglomeration areas respectively,indicating varying levels of border tourism development.Additionally,the study identifies an upward trend in China’s border tourism efficiency from 2010-2019.The southwest region emerges as a hotspot and the most active region,while the northwest and northeast regions are considered cold spots with ample room for improvement.Furthermore,the density of transportation facilities,national vulnerability,cultural proximity,the number of border ports,and market opportunity are crucial factors influencing the spatial and temporal pattern of border tourism efficiency in China.
基金National Natural Science Foundation of China, No.40131010
文摘With the rapid economic development during the last 30 years in China, more and more disparities have emerged among different regions. It has been one of the hot topics in the fields of physical geography and economic geography, and also has been the task for Chinese government to handle. Nevertheless, to quantitatively assess the impacts of physio-geographical patterns （PGP） on the regional development disparity has been ignored for a long time. In this paper, a quantitative method was adopted to assess the marginal effects of the PGP on spatio-temporal disparity using the partial determination coefficients. The paper described the construction of the evaluation model step by step following its key scientific thinking. Total GDP, per capita GDP, primary industrial output value and secondary industrial output value were employed in this study as the indicators to reflect the impacts of PGP on the regional development disparity. Based on the evaluation methods built by researchers, this study firstly analyzed the temporal impacts of the PGP on spatio-temporal disparity of the regional development in China during the past 50 years, and then explained the spatial differences at each development stage. The results show that the spatio-temporal disparity in China is highly related to the PGP, and that the marginal contribution rate could be employed as an effective way to quantitatively assess the impact of the PGP on spatio-temporal disparity of the regional development.
基金Under the auspices of the National Natural Science Foundation of China(No.41771138)。
文摘Improving comprehensive agricultural productivity is an important measure to realize agricultural modernization.Based on the data from Jilin Statistical Yearbook,this study analyzed the spatial and temporal characteristics of comprehensive agricultural productivity discrepancy in the main agricultural production areas of Jilin Province,China.The comprehensive agricultural productivity of 25 county-level administrative units were evaluated by a comprehensive index system based on five aspects which included 20 indicators from 2004 to 2017.The pattern of the discrepancy was analyzed by the spatial differentiation indices and spatial convergence theory.The results were as follows:1) the overall comprehensive agricultural productivity was in a ’W-type’ rising trend;2) the discrepancy was in’inverted W-type’ trend;3) the spatial distribution characteristics were mainly discrete plaque and ’inverted V-type’;4) the formation of differences was forced by a combination of internal and external driving forces.Our study demonstrates the effectiveness of rising agricultural productivity and the level of economic and social developments in different counties in Jilin Province.
基金This work is supported by the National Natural Science Foundation of China （NSFC, nos. 61340046）, the National High Technology Research and Development Programme of China （863 Programme, no. 2006AA04Z247）, the Scientific and Technical Innovation Commission of Shenzhen Munici-pality （nos. JCYJ20130331144631730）, and the Specialized Research Fund for the Doctoral Programme of Higher Edu- cation （SRFDP, no. 20130001110011）.
文摘Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation efficiency, cluttered backgrounds and intro-variability among same type of actions. Spatio-temporal interest point （STIP） based methods have shown promising results to tackle human action classification in complex scenes efficiently. However, the state-of-the-art works typically utilize bag-of-visual words （BoVW） model which only focuses on the word distribution of STIPs and ignore the distinctive character of word structure. In this paper, the distribution of STIPs is organized into a salient directed graph, which reflects salient motions and can be divided into a time salient directed graph and a space salient directed graph, aiming at adding spatio-temporal discriminant to BoVW. Generally speaking, both salient directed graphs are constructed by labeled STIPs in pairs. In detail, the ＂directional co-occurrence＂ property of different labeled pairwise STIPs in same frame is utilized to represent the time saliency, and the space saliency is reflected by the ＂geometric relationships＂ between same labeled pairwise STIPs across different frames. Then, new statistical features namely the Time Salient Pairwise feature （TSP） and the Space Salient Pairwise feature （SSP） are designed to describe two salient directed graphs, respectively. Experiments are carried out with a homogeneous kernel SVM classifier, on four challenging datasets KTH, ADL and UT-Interaction. Final results confirm the complementary of TSP and SSP, and our multi-cue representation TSP ＋ SSP ＋ BoVW can properly describe human actions with large intro-variability in real-time.
基金Projects(41601424,41171351)supported by the National Natural Science Foundation of ChinaProject(2012CB719906)supported by the National Basic Research Program of China(973 Program)+2 种基金Project(14JJ1007)supported by the Hunan Natural Science Fund for Distinguished Young Scholars,ChinaProject(2017M610486)supported by the China Postdoctoral Science FoundationProjects(2017YFB0503700,2017YFB0503601)supported by the National Key Research and Development Foundation of China
文摘Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.
文摘Nowadays, wildlife road mortality is acknowledged as a main source of threatening long-term survival of wildlife. This paper as the first to analysis wild life vehicle collisions in Iran, aims to reconstruct and interpret the spatio-temporal patterns of WVCs on Asiaei highway in Golestan National Park (GNP). With the collaboration of environmental protection department of GNP, we identified about 1900 WVC Records involving 34 different species of mammals, birds, reptiles and amphibians between 2004 and 2013. Mammals were involved in more than 50% of overall WVCs, among which wild boar (Sus scrofa), Golden Jackal (Canis aureus), Red Fox (Vulpes vulpes), hedgehog (Erinaceus concolor), stone marten (Martes foina) and porcupine (Hystrix indica) were involved in more than 90% of mammals’ mortalities;So, we focused on analyzing spatio-temporal pattern of vehicle collisions of these six mammal species. During the study period, these species have undergone 95% increase in road mortalities, averagely. Detailed temporal analyses exhibited an increasing trend of road mortalities from spring to summer and then a reducing one to late winter. It was shown that a large number of collisions occurred in holiday periods when recreational trips considerably increased the traffic volume of Asiaei highway. Preliminary inspection of spatial patterns using Kernel density analysis revealed six collision hotspots, mostly located in the road bends with densely forested land cover on both sides;the promenades along the road seemed to play a significant role too. Scale dependency analyses of collision patterns, demonstrated clustering pattern at micro scales less than 10 km, randomness at meso scales 10 - 20 km and both regularity and clustering at macro scales more than 20 km. This paper suggests that road mortality of common species in GNP is a momentous issue, which needs to be considered by relevant governmental and public organizations. We also emphasize that the analyses of spatial and temporal patterns of WVCs are fundamentals to plan for mitigate wildlife road mortality.
文摘In crime science, understanding the dynamics and interactions between crime events is crucial for comprehending the underlying factors that drive their occurrences. Nonetheless, gaining access to detailed spatiotemporal crime records from law enforcement faces significant challenges due to confidentiality concerns. In response to these challenges, this paper introduces an innovative analytical tool named “stppSim,” designed to synthesize fine-grained spatiotemporal point records while safeguarding the privacy of individual locations. By utilizing the open-source R platform, this tool ensures easy accessibility for researchers, facilitating download, re-use, and potential advancements in various research domains beyond crime science.
基金Foundation： National Natural Science Foundation of China, No.41171328, No.41201184, No.41101537 National Basic Program of China, No.2010CB951502
文摘Understanding crop patterns and their changes on regional scale is a critical re- quirement for projecting agro-ecosystem dynamics. However, tools and methods for mapping the distribution of crop area and yield are still lacking. Based on the cross-entropy theory, a spatial production allocation model （SPAM） has been developed for presenting spa- tio-temporal dynamics of maize cropping system in Northeast China during 1980-2010. The simulated results indicated that （1） maize sown area expanded northwards to 48~N before 2000, after that the increased sown area mainly occurred in the central and southern parts of Northeast China. Meanwhile, maize also expanded eastwards to 127°E and lower elevation （less than 100 m） as well as higher elevation （mainly distributed between 200 m and 350 m）; （2） maize yield has been greatly promoted for most planted area of Northeast China, espe- cially in the planted zone between 42°N and 48°N, while the yield increase was relatively homogeneous without obvious longitudinal variations for whole region; （3） maize planting density increased gradually to a moderately high level over the investigated period, which reflected the trend of aggregation of maize cultivation driven by market demand.
基金Under the auspices of the Tang Scholar Program of Northwest University(No.2016)
文摘Attended collection and delivery points are vital components of ‘last-mile logistics’.Based on point of interest(POI) data for Cainiao Stations and China Post stations in Changsha City, China, this paper provides a detailed exploration of the basic features, spatial distribution, and location influencing factors of attended collection and delivery points.Specifically, analyses of the types, service objects and location distributions of the attended collection and delivery points alongside a discussion of their spatial pattern and influencing factors provides a reference for their general geographic layout and characteristics.The findings of this study indicate that: 1) The main mode of operation of attended collection and delivery points is franchises, with other modes of operation rely on supermarkets and other individual shop types.2) The main service targets of attended collection and delivery points are communities, schools, and businesses, followed by townships, enterprises, scenic spots, and administrative units.3) Approximately 77.44% of the attended collection and delivery points are located near the exits of service areas;others are situated in the centre of the service areas.For the Cainiao Stations, 80% are located within 125 m of the exit;for the China Post stations, 80% are located within 175 m of the exit.4) The spatial distribution of the attended collection and delivery points in Changsha is unbalanced, with ‘more centre and fewer surrounding’.The centre is an ‘inverted triangle’, and the edge is an ‘orphan’, showing a northwest-southeast orientation and symmetrical along the axis.The layout of the attended collection and delivery points forms three core areas, and the number of sites decreases with the distance from the core.5) The number and distribution of the attended collection and delivery points are strongly consistent with the regional economic development level, population, and roadway system traffic convenience.Most attended collection and delivery points are on residential, scientific and educational, and commercial and financial land.
基金supported by Geological Survey of Canada and China University of Geosciences (Wuhan)
文摘The relationship between fractal point pattern modeling and statistical methods of pa- rameter estimation in point-process modeling is reviewed. Statistical estimation of the cluster fractal dimension by using Ripley＇s K-function has advantages in comparison with the more commonly used methods of box-counting and cluster fractal dimension estimation because it corrects for edge effects, not only for rectangular study areas but also for study areas with curved boundaries determined by re- gional geology. Application of box-counting to estimate the fractal dimension of point patterns has the disadvantage that, in general, it is subject to relatively strong ＂roll-off＂ effects for smaller boxes. Point patterns used for example in this paper are mainly for gold deposits in the Abitibi volcanic belt on the Canadian Shield. Additionally, it is proposed that, worldwide, the local point patterns of podiform Cr, volcanogenic massive sulphide and porphyry copper deposits, which are spatially distributed within irregularly shaped favorable tracts, satisfy the fractal clustering model with similar fractal dimensions. The problem of deposit size （metal tonnage） is also considered. Several examples are provided of cases in which the Pareto distribution provides good results for the largest deposits in metal size-frequency distribution modeling.
基金supported by National Natural Science Foundation of China(No.61103123)Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry
文摘Most of the exist action recognition methods mainly utilize spatio-temporal descriptors of single interest point while ignoring their potential integral information, such as spatial distribution information. By combining local spatio-temporal feature and global positional distribution information(PDI) of interest points, a novel motion descriptor is proposed in this paper. The proposed method detects interest points by using an improved interest point detection method. Then, 3-dimensional scale-invariant feature transform(3D SIFT) descriptors are extracted for every interest point. In order to obtain a compact description and efficient computation, the principal component analysis(PCA) method is utilized twice on the 3D SIFT descriptors of single frame and multiple frames. Simultaneously, the PDI of the interest points are computed and combined with the above features. The combined features are quantified and selected and finally tested by using the support vector machine(SVM) recognition algorithm on the public KTH dataset. The testing results have showed that the recognition rate has been significantly improved and the proposed features can more accurately describe human motion with high adaptability to scenarios.
基金Supported by the National Natural Science Foundation of China （40971275, 50811120111）
文摘Based on spatio-temporal correlativity analysis method, the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented. The asynchronous correlative characteristics of gas migration in working face airflow direction are qualitatively analyzed. The calculation method of asynchronous correlation delay step and the prediction and inversion formulas of gas concentration changing with time and space after gas emission in the air return roadway are provided. By calculating one hundred and fifty groups of gas sensors data series from a coal mine which have the theoretical correlativity, the correlative coefficient values range of eight kinds of data anomaly is obtained. Then the gas moni- toring data anomaly identification algorithm based on spatio-temporal correlativity analysis is accordingly presented. In order to improve the efficiency of analysis, the gas sensors code rules which can express the spatial topological relations are sug- gested. The experiments indicate that methods presented in this article can effectively compensate the defects of methods based on a single gas sensor monitoring data.
文摘Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.
基金The National Natural Science Foundation of China(No.41471371)
文摘In order to detect the traffic pattern of moving objects in the city more accurately and quickly, a parallel algorithm for detecting traffic patterns using stay points and moving features is proposed. First, the features of the stay points in different traffic patterns are extracted, that is, the stay points of various traffic patterns are identified, respectively, and the clustering algorithm is used to mine the unique features of the stop points to different traffic patterns. Then, the moving features in different traffic patterns are extracted from a trajectory of a moving object, including the maximum speed, the average speed, and the stopping rate. A classifier is constructed to predict the traffic pattern of the trajectory using the stay points and moving features. Finally, a parallel algorithm based on Spark is proposed to detect traffic patterns. Experimental results show that the stay points and moving features can reflect the difference between different traffic modes to a greater extent, and the detection accuracy is higher than those of other methods. In addition, the parallel algorithm can increase the speed of identifying traffic patterns.
