基于线性稀疏模型和iHMM的群体异常事件检测

在群体异常检测中,人群特征感知主要提取个体的群体特性。提出了基于群特征的稀疏线性模型和无限隐马尔可夫(SLM-iHMM)方法检测人群异常事件。该方法通过统计模型整合空间和时间因素,基于SLM提取空间线索,从而在空间域中建立用于群特征提取的统计模型。时间线索在iHMM中被明确地编码,用于分析来自空间域的时间多尺度特征。关于UMN数据集的实验验证了该方法的可行性和有效性。

Spatial-Temporal Distribution Characteristics and Limiting Factors of Medium-low Yield Farmland in Tianjin

[Objective] This paper aimed to understand the area change and distribu- tion of medium-low yield farmland, and offered basis to the improvement of mediumlow farmland and its increase of grain production in Tianjin. [Method] Based on the statistical date of Tianjin and its relevant counties and districts, the yield standard was set up to classify high-yield, medium-yield and low-yield farmland in Tianjin. The author analyzed area change of medium-low yield farmland in six agricultural counties and districts （including Jixian County, Wuqing District, Baodi District, Ninghe County, Jinghai County and Dagang district of Binghai New Area） from 1980 to 2010. [Result] The results showed that the average yield of grain rose from 2 445 kg/hm^2 in 1980 to 5 130 kg/hm^2 in 2010, increasing 109.82%. The area of mediumlow yield farmland was reduced from 291 250.13 hm^2 in 1985 to 76 489.87 hm^2 in 2010, coming down 74%. In Tianjin, the area of medium-low yield farmland of 2010 accounted for 19% of the total farmland, of which the ratios of medium-low yield farmland of Jinghai County, Jixian County, Dagang district of Binghai New Area, Wuqing District, Baodi District and Ninghe County were 43.12%, 18.59%, 17.23%, 14.01%, 7.05% and 0, respectively. Low soil nutrient content, drought and water shortage, as well as soil salinization were the main yield limiting factors to mediumlow yield farmland in Tianjin in 2010. [Conclusion] The countermeasures to improve the medium-low yield farmland were proposed, involving enhancing the investment of the government, strengthening the construction of water conservancy infrastructure, further improving the soil fertility, as well as saline and alkaline land, optimizing the farming system and planting drought and salt tolerance crops, etc.

Spatial and Temporal Variability of N, P and K Balances for Agroecosystems in China

Nitrogen, phosphorus, and potassium balances for agroecosystems in China from 1993 to 2001 were calculated at national and provincial levels using statistical data and related parameters, and their spatial and temporal variabilities were analyzed with GIS to estimate the potential impacts of nutrient N, P and K surpluses or deficits to soil, water and air. At the national scale, the N and P balances from 1993 to 2001 showed a surplus, with the nitrogen surplus remaining relatively stable from 1997—2001. Although during this period the P surplus pattern was similar to N, it had smaller values and kept increasing as the use of phosphate fertilizer increased year by year. However, K was deficient from 1993 to 2001 even though from 1999 to 2001 the K deficit decreased. The spatial analysis revealed higher N surpluses in the more developed southeastern provinces and lowest in the western and northern provinces where there was less chemical fertilizer input. The serious K deficit mainly occurred in Shanghai and Beijing municipalities, Jiangsu, Zhejiang and Hubei provinces, and Xinjiang autonomous regions. For the years 1992, 1996 and 2001, N surpluses and K deficits had significant positive spatial correlations with per capita gross domestic product (GDP), per capita gross industrial output value, and per capita net income of rural households. This showed that the level of economic development played an important role on nutrient balances in the agroecosystems.

RLS channel estimation with adaptive forgetting factor in space-time coded MIMO-OFDM systems

Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares (RLS) channel estimation with adaptive forgetting factor in wireless space-time coded multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Because there are three different forgetting factor scenarios including adaptive, two-step and conventional ones applied to RLS channel estimation, this paper describes the principle of RLS channel estimation and analyzes the impact of different forgetting factor scenarios on the performances of RLS channel estimation. Simulation results proved that the RLS algorithm with adaptive forgetting factor (RLS-A) outperformed that with two-step forgetting factor (RLS-T) or with conventional forgetting factor (RLS-C) in both estimation accuracy and robustness over the multiple-input multiple-output (MIMO) channel, i.e., a wide-sense stationary uncorrelated scattering (WSSUS) and frequency-selective slowly fading channel. Hence, we can employ the RLS-A method by adjusting forgetting factor adaptively to track and estimate channel state parameters successfully in space-time coded MIMO-OFDM systems.

Temporal population dynamics of dinoflagellate Prorocentrum minimum in a semi-enclosed mariculture pond and its relationship to environmental factors and protozoan grazers

The ecological processes and interrelationships between protists,either autotrophic or heterotrophic,and environmental factors in mariculture ponds are largely unknown.This study investigated the temporal dynamics of potentially harmful dinoflagellate,Prorocentrum minimum (Pavillard) Schiller,and its relationship to physico-chemical factors and protozoan grazers over a complete cycle in a semi-enclosed shrimp-farming pond near Qingdao,Northern China.P.minimum occurred frequently in low numbers from June to August,followed by a sharp increase from the middle of August,reaching a single maximum peak value of 2.2×105 cells L-1 in October.Temporal variation in abundance was positively correlated with dissolved nitrogen,but showed a significant inverse relationship to abundance of the dominant ciliates,Tintinnopsis lohmanni and Askenasia stellaris.The results provide statistical evidence that the number of P.minimum increased with increasing nitrogen,and the suppression or shortening of algal bloom may be associated with protozoan grazers,such as Tintinnopsis lohmanni,in mariculture ponds.

Spatiotemporal Variations and Influencing Factors Analysis of PM_(2.5) Concentrations in Jilin Province,Northeast China

High PM_(2.5) concentrations and frequent air pollution episodes during late autumn and winter in Jilin Province have attracted attention in recent years. To describe the spatial and temporal variations of PM_(2.5) concentrations and identify the decisive influencing factors, a large amount of continuous daily PM_(2.5) concentration data collected from 33 monitoring stations over 2-year period from 2015 to 2016 were analyzed. Meanwhile, the relationships were investigated between PM_(2.5) concentrations and the land cover, socioeconomic and meteorological factors from the macroscopic perspective using multiple linear regressions(MLR) approach. PM_(2.5) concentrations across Jilin Province averaged 49 μg/m^3, nearly 1.5 times of the Chinese annual average standard, and exhibited seasonal patterns with generally higher levels during late autumn and over the long winter than the other seasons. Jilin Province could be divided into three kinds of sub-regions according to 2-year average PM_(2.5) concentration of each city. Most of the spatial variation in PM_(2.5) levels could be explained by forest land area, cultivated land area, urban greening rate, coal consumption and soot emissions of cement manufacturing. In addition, daily PM_(2.5) concentrations had negative correlation with daily precipitation and positive correlation with air pressure for each city, and the spread and dilution effect of wind speed on PM_(2.5) was more obvious at mountainous area in Jilin Province. These results indicated that coal consumption, cement manufacturing and straw burning were the most important emission sources for the high PM_(2.5) levels, while afforestation and urban greening could mitigate particulate air pollution. Meanwhile, the individual meteorological factors such as precipitation, air pressure, wind speed and temperature could influence local PM_(2.5) concentration indirectly.

Spatial and Temporal Pattern of Urban Smart Development in China and Its Driving Mechanism

Smart urban development is an inevitable choice, and is essential to overall strength improvement. It is important to explore an urban smart development path which unites smart growth with driving shrinkage perfectly in forming scientific and sustainable development concept and responding to new normal strategic opportunities. Based on statistic data of 294 prefecture-level cities and above in China from 2000 to 2015, we analyzed spatial and temporal evolution of urban smart development in China by constructing a dynamic fitting model of urban land expansion, population growth, and economic development as well as the coefficient of variation of urban smart development(CVSD). Further efforts were then made to consider differential distribution regularity of urban smart development so as to understand the driving mechanisms of heterogeneous classification of urban smart development in China from different scales and scale variation. Our results indicate that: 1) the disordered growth tendency of urban cities in China is overall well controlled in the middle, and late research and it mainly presented a doublet coexistence of shrinkage disordered cities and smart developing cities. It is particularly obvious that Northeast China and East China have regarded shrinkage disordered cities and smart developing cities as main development tendency separately. 2) Areas with basic stability and relative variation were relatively dispersed across the time period, but the proportion was far beyond areas with significant variation. It demonstrates a relative equilibrium spatial and temporal differential evolution pattern of prefecture-level cities and above in China, except for Tongling, Lanzhou and Chaoyang. 3) prefecture-level cities and above in China are mostly characterized by shrinkage disordered and smart development classification under the background of different scale and scale variation from 2000–2015; however, the spatial resonance relation is not obvious. 4) There are many interaction factors forming an important driving mechanism in developing the spatial and temporal pattern of urban smart development in China, including natural geographical factors, industrial structure adjustment, human capital radiation, regional traffic accessibility, and government decision-making intervention.

Spatio-temporal distribution of vegetation index and its influencing factors——a case study of the Jiaozhou Bay, China

The coastal zone is an area characterized by intense interaction between land and sea, high sensitivity to regional environmental changes, and concentrated human activities. Little research has investigated vegetation cover changes in coastal zones resulting from climate change and land-use change, with a lack of knowledge about the driving mechanism. Normalized diff erence vegetation index(NDVI) can be used as an indicator for change of the coastal environment. In this study, we analyzed the interannual changes and spatial distribution of NDVI in the coastal zone around Jiaozhou Bay in Qingdao, a coastal city undergoing rapid urbanization in northeast China. The underlying causes of NDVI variations were discussed in the context of climate change and land-use change. Results showed that the spatio-temporal distribution of NDVI displayed high spatial variability in the study area and showed a typical trend of gradually increasing from coastal to inland regions. The significant increase area of NDVI was mainly found in newly added construction land, extending along the coastline towards the inland. Land vegetation cover demonstrated a certain response relationship to sea-land climate change and land-based activities. The impact of land-based human activities was slightly greater than that of sea-land climate change for land vegetation cover. The results indicate that promoting ecological policies can build an ecological security framework of vegetation suitable for the resource characteristics of coastal cities. The framework will buf fer the negative ef fects of sea-land climate change and land-based human activities on vegetation cover and thereby achieve the balance of regional development and ecological benefits in the coastal zone.

Oribatid Use as Bioindicateur of Environment： Case of Galumna sp. and Scheloribates sp. （Acari： Oribatida）

Environmental characteristics are often the factors that determine the distribution of species in nature. However, species response vis-A-vis these factors differs. For a better understanding of the phenomenon, we have conducted this study which consists of following the spatio-temporal evolution of two species of Oribatida （Scheloribates sp. and Galumna sp.）. The sites which have been the subject of this study, are situated in different bioclimatic zones presenting a very different climatic, edaphic, nutritional, and altitudinal characteristics. The variability of ecological factors showed that the behavior of two species differs. Indeed, Scheloribates sp. is present in all sites except in Biskra whereas Galumna sp. is present only in sites belonging to humid and sub humid bioclimatic zones. Moreover, Scheloribates sp. appears more tolerant of environmental changes while Galumna sp. is more stringent and its presence is marked only in the sites where ecological conditions are better. Thus, it can be noted that the spatial and temporal distribution of oribatid is not only conditioned solely by environmental factors but also by intrinsic factors specific to each species. The specific behavior of Galumna sp. and the tolerance of Scheloribates sp. are interesting and can be the subject of bioindicator species that can inform us about the changes that effect whether natural or anthropogenic environment.

Temporal dynamics of phytoplankton communities in a semi-enclosed mariculture pond and their responses to environmental factors

Variations in physical-chemical factors, species composition, abundance and biomass of nano-and micro-phytoplankton assemblages, as well as their responses to environmental factors, were investigated over a complete cycle (6 months) in a semi-enclosed shrimp-farming pond near Qingdao, northern China. The aim was to establish the temporal patterns of phytoplankton communities and to evaluate protists as suitable bioindicators to water quality in mariculture systems. A total of 34 taxa with nine dominant species were identified, belonging to six taxonomic groups (dinoflagellates, diatoms, cryptophyceans, chlorophyceans, euglenophyceans and chrysophyceans). A single peak of protist abundance occurred in October, mainly due to chlorophyceans, diatoms and chrysophyceans. Two biomass peaks in July and October were primarily due to dinoflagellates and diatoms. Temporal patterns of the phytoplankton communities significantly correlated with the changes in nutrients, temperature and pH, especially phosphate, either alone or in combination with NO3-N and NH3-N. Species diversity, evenness and richness indices were clearly correlated with water temperature and/or salinity, whereas the biomass/abundance ratio showed a significant correlation with NO3-N. The results suggest that phytoplankton are potentially useful bioindicators to water quality in semi-enclosed mariculture systems.

Spatial-temporal Characteristics and Factors Influencing Commuting Activities of Middle-class Residents in Guangzhou City, China

The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium-short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed.

The Characteristics and Driving Factors of the Spatio-temporal Dynamic Evolution of Tourism Ecological Security in the Silk Road Economic Belt

The exploration of ecological safety in tourism sites can provide a concrete path for sustainable tourism development in a region.Based on the“Driver-Pressure-State-Impact-Response”(DPSIR)model,we constructed an index system for the evaluation of tourism ecological security(TES)in the Silk Road Economic Belt(SREB)from 2005 to 2020.This index system was used to explore the characteristics of spatial and temporal dynamic evolution with the help of entropy weight TOPSIS method,dynamic index of TES and Markov probability transfer matrix,and a standard deviational ellipse(SDE)model and GM(1,1)model were constructed for spatial pattern analysis and prediction.The results indicate four key aspects of this system.(1)In terms of spatiotemporal evolution,the tourism ecological safety index(TESI)of the SREB increased,the TES levels of the northwestern and southwestern provinces and cities differed significantly,and the quality conditions of TES in the southwestern provinces and cities were better than in the northwest.(2)In terms of dynamic evolutionary characteristics,the speed of change at each level of the SREB was slow,but the level of TES has improved.The TES level has not shifted by leaps and bounds,and the shifts in the level type show“path dependence”and“self-locking”effects.(3)In terms of spatial and temporal distribution patterns,the spatial pattern of TES in the SREB is a“northwest-southeast”movement trend,and the spatial distribution appeared as“aggregation”from 2005 to 2020.The prediction results show that the center of gravity of TES in the SREB will shift to the southeast from 2025 to 2035,and the spatial spillover effect will be reduced.(4)In terms of driving factors,the number of star-rated hotels,and the amounts of industrial wastewater emissions,tourism foreign exchange earnings,forest coverage,and other parameters are the key factors affecting TES,and the booming tourism industry requires the interconnection and interpenetration of various factors.The results of this study can provide a reference for tourism development and ecological environmental protection in the Silk Road Economic Belt.

Spatiotemporal evolution of prehistoric Neolithic-Bronze Age settlements and influencing factors in the Guanting Basin, northeast Tibetan Plateau

For almost two decades, the relationship between prehistoric natural disasters that struck the Guanting Basin in northeast Tibetan Plateau and the destruction of Lajia, an archeological site, has attracted scholarly attention and been widely discussed. Whereas most studies have focused on the impacts of disasters on a single site within the Guanting Basin, few have examined patterns of spatiotemporal evolution of human settlements from the Neolithic to the Bronze Age. Consequently, there is a lack of clarity on the processes and mechanisms underlying the evolution of prehistoric human-land relationships in the Guanting Basin. We therefore examined spatiotemporal variations in settlements in the Guanting Basin during the period, based on the locations, altitudes, and areas of archaeological sites. We found that four sites were located on the third terrace of the Yellow River during the late Yangshao period(5500–5000 cal yr BP) and distributed within a small area. During the period between the Majiayao and Qijia cultures(5300–3600 cal yr BP), the number of sites evidently increased and the scale and distribution of settlements expanded, with settlements generally shifting toward the lower elevation areas of the Guanting Basin.During the Xindian period(3400–2700 cal yr BP), the number and scale of sites showed a downward trend and the distribution of settlements contracted. The Xindian settlement underwent altitude-based spatial differentiation, with some groups moving to areas at higher altitudes and others remained in lower altitude areas. Moreover, we found that the number, scale, and distribution range of Neolithic and Bronze Age sites in the Guanting Basin were closely related to the evolution and distribution patterns of prehistoric cultures in the regions of Gansu and Qinghai, which were further affected by climate change and agricultural development. Furthermore, there is no evidence that the altitudinal distribution pattern of Neolithic and Bronze Age settlements in the Guanting Basin was influenced by paleofloods rather it was primarily influenced by changes in subsistence strategies.

The Spatio-temporal Evolution of Ski Resorts in the Beijing-Tianjin-Hebei Region:Characteristics and Influencing Factors

Ski resorts are one of the bases for the development of ice-snow sports and tourism,and they are also a hot topic of social concern.Taking 117 ski resorts in Beijing,Tianjin and Hebei as the research object,geospatial analysis methods such as kernel density and spatial autocorrelation were used to explore the spatial and temporal distribution patterns of the ski resorts.The geographic detector was used to deeply explore the underlying factors influencing the spatial and temporal distribution of ski resorts in terms of policy factors,natural factors and economic and social factors.This study found that the spatial and temporal distribution of ski resorts in the Beijing-Tianjin-Hebei Region showed a significant Olympic event-driven characteristic.From 2009 to 2021,the spatial pattern of Beijing-Tianjin-Hebei ski resorts has changed from“single-core development”,to a“single-core with multi-point”layout,and then to a“multi-core”layout.The spatial pattern has changed from agglomeration to diffusion.Cold and hot spots of the spatial and temporal characteristics in Beijing-Tianjin-Hebei ski resort have shifted from north to south,from the initial suburbs of Beijing to the southern cities of Baoding,Shijiazhuang,Xingtai and other cities in Hebei Province.The spatial and temporal distribution of Beijing-Tianjin-Hebei ski resorts has been influenced by many factors,from“GDP per capita”to“population density”to“policy quantity”,showing a shift from“Economic-driven”to“population-driven”to“policy-driven”processes.

Analysis of the Spatio-temporal Differentiation of Cultivated Land Pressure in the Pearl River-Xijiang Economic Zone and Its Influencing Factors

Cultivated land pressure is often used to reflect the shortage of cultivated land resources. By using the methods of the Cultivated Land Pressure Index, coefficient of variation and cold-hot spot analysis, this paper analyzes the spatial-temporal differentiation pattern and dynamic change processes of cultivated land pressure in the counties of the Pearl River-Xijiang Economic Zone from 2008 to 2017, and measures the factors which influence cultivated land pressure by using Principal Component Analysis. The results show that the cultivated land pressure in the Pearl River-Xijiang Economic Zone has been in a “high pressure” state, and the Cultivated Land Pressure Index has been rising continuously from 2008 to 2017. The coefficient of variation of the Cultivated Land Pressure Index in the Pearl River-Xijiang Economic Zone and various prefecture-level cities is fluctuating and rising, which indicates that the overall spatial differences in the cultivated land pressure in this region are expanding and polarization is obvious. In addition, the area where the municipal district of the provincial capital city is located is the core area of urban development and also the area with the greatest cultivated land pressure. The spatial pattern of cultivated land pressure cold-hot spots in the Pearl River-Xijiang Economic Zone is obviously heterogeneous, in which the Pearl River Economic Zone is the main hot spot gathering area and the Xijiang Economic Zone is the main cold spot gathering area. Farmers’ income, investment in fixed assets, GDP, population and other socio-economic factors are the main factors driving the changes in the cultivated land pressure in the Pearl River-Xijiang Economic Zone. Furthermore, farming production factors, such as the multiple cropping index and grain yield per unit area,will also have an important impact on the changes in the cultivated land pressure.

Spatial and Temporal Distribution Characteristics of Flower-viewing Tourism and Its Influencing Factors in China

Despite the rapid development of flower-viewing tourism in China in recent years,there is almost no systematic research on it.Therefore,this study analyzes the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China using the spatial statistical analysis methods and the geographic detector method.The study uses the Point-of-Interest data of flower-viewing tourist attractions from networks such as Qunar and Ctrip,the flower observation data from China Phenological Observation Network,Chinese network news,and Weibo,and the statistical data from yearbooks.The results are as follows:1)The spatial attribution type of flower-viewing tourism in China is aggregated into areas,including two high-density aggregated areas,three medium-density aggregated areas,and one general-density aggregated area.Furthermore,five major types of flower-viewing tourist attractions have formed several aggregated areas.2)The time of flower viewing in China starts from about February and lasts about eight months till October each year.Florescence and flowering time of different ornamental flowers in different regions are different.3)The spatial and temporal distribution characteristics of flower-viewing tourism in China are mainly affected by ornamental flower phenology,spatial distribution characteristics of flower-viewing resources,regional permanent population size,youth population size,female population size,regional GDP,and added value of the tertiary sector.These conclusions clarify the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China.They could provide a scientific basis and useful reference for the coordination and sustainable development of regional flower-viewing tourism in China.

Variability of Soil Salinity at Multiple Spatio-Temporal Scales and the Related Driving Factors in the Oasis Areas of Xinjiang,China

Located in the inland arid area of central Asia, salt-affected farmlands take up one third of the total irrigated land area in Xinjiang of Northwest China. Spatio-temporal variability of soil salinity and the underlying mechanism are fundamental problems challenging the sustainability of oasis agriculture in China. In this study, the data of total dissolved solids(TDS) measured for soil samples collected from 27 representative study areas in the oasis areas of Xinjiang were analyzed and the coefficient of variation(CV) and stratification ratio(SR) of TDS were used to describe the lateral and vertical soil salinity variations, respectively. Weekly, monthly,and annual changes in soil salinity were also summarized. Results showed that the top(0–20 cm) soil salinity was highly variable(CV> 75%) for most studied areas. Lateral variation of soil salinity was significantly correlated with the sampling interval; as a result, a maximum sampling interval of 0.9 m was found for reducing evaluation uncertainty. The top 0–20 cm soil salt accounted for about25.2% of the total salt in the 0–100 cm soil profile. The stratification ratio values(the ratio of TDS at the 20–40 cm depth to that at the 0–20 cm depth) were mostly smaller than 1 and on average 0.92, illustrating that the top 0–20 cm soil contained slightly more salt and a considerable amount of salt still existed in subsurface and deep horizons. Irrigation reduced top soil salinity by 0.52 g kg-1, or14.6%, within the first week. On average, the relative range of soil salinity, calculated to indicate monthly changes in soil salinity, was58.2% from May to September. A 27-year experiment indicated that cultivation increased soil salinity by 44.4% at a rate of 0.14 g kg-1year-1. At small spatio-temporal scales, soil salinity variation was mainly affected by anthropogenic factors, such as irrigation and land use. However, natural factors, including groundwater, topography, and climate conditions, mainly influenced soil salinity variation at large spatio-temporal scales. This study displayed the highly variable nature of soil salinity in space and time. Those driving factors identified in this study could provide guidelines for developing sustainable agriculture in the oasis areas and combating salinization in arid regions of China.