Dynamic Spatio-Temporal Modeling in Disease Mapping

Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex and this complexity has led many to oversimply and model the spatial and temporal dependencies independently. Unlike common practice, this study formulated a new spatio-temporal model in a Bayesian hierarchical framework that accounts for spatial and temporal dependencies jointly. The spatial and temporal dependencies were dynamically modelled via the matern exponential covariance function. The temporal aspect was captured by the parameters of the exponential with a first-order autoregressive structure. Inferences about the parameters were obtained via Markov Chain Monte Carlo (MCMC) techniques and the spatio-temporal maps were obtained by mapping stable posterior means from the specific location and time from the best model that includes the significant risk factors. The model formulated was fitted to both simulation data and Kenya meningitis incidence data from 2013 to 2019 along with two covariates;Gross County Product (GCP) and average rainfall. The study found that both average rainfall and GCP had a significant positive association with meningitis occurrence. Also, regarding geographical distribution, the spatio-temporal maps showed that meningitis is not evenly distributed across the country as some counties reported a high number of cases compared with other counties.

Spatio-temporal model for soil characteristic of reclamation land

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

The spatio-temporal models of periodic marketing in rural China

Periodic marketing is a unique and imporant socio-economic feature of Chinese ruraltowns, the economic, political, social and cultural centres in rural areas. Through two detailed casestudies in the North China Plain in 1990, mis paper examined the temporal and spatialcharacteristics, especially their interrelationship. of regional periodic market systems and theirrelationship with rural development in modern China. The distribution of periodic market-towns isfound to be on consumer convenience, and to have an apparent hierarchical structure and centralplace characteristics. Further, the spatial coordination system of periodic marketing has a reverserelationship of spatio-temporal synchronisation. Finally, this paper notes that periodic marketingimposes significant influence on rural development through conducting and controlling goods flow and population flow in rural economic system.

Modeling the Spatio-Temporal Dynamics of Local Context for a Contextualized Diffusion of Agroecological Intensification Options in Niger

Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view to sustainable development. The territorial scale of municipalities is not sufficient for this necessary contextualization;the scale of the “village terroir” seems to be a better option. This is the hypothesis we put forward in the framework of the Global Collaboration for Resilient Food Systems program (CRFS), i.e. local context is spatially defined by village terroir. The study is based on data collected through participatory mapping and surveys in “village terroirs” in three regions of Niger (Maradi, Dosso and Tillabéri). Then the links between farm managers and their cultivated land, as well as the spatio-temporal dynamics of local context are analyzed. This study provides evidence of the existence and functional usefulness of the village terroir for farmers, their land management and their activities. It demonstrates the usefulness of contextualizing agricultural options at this scale. Their analysis elucidates the links between “terroirs village” and the specific functioning of the agrosocio-ecosystems acting on each of them, thus laying the systemic and geographical foundations for a model of the spatio- temporal dynamics of “village terroirs”. This initial work has opened up new perspectives in modeling and sustainable development.

Improved spatio-temporal alignment measurement method for hull deformation

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

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

Infuence of urbanization on schistosomiasis infection risk in Anhui Province based on sixteen year’s longitudinal surveillance data:a spatio-temporal modelling study

Background Urbanization greatly afects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases.Schistosomiasis,a common parasitic disease transmitted by the snail Oncomelania hupensis,is mainly found in areas with population aggregations along rivers and lakes where snails live.Previous studies have suggested that factors related to urbanization may infuence the infection risk of schistosomiasis,but this association remains unclear.This study aimed to analyse the efect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China.Methods County-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected.The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)and the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite(NPP-VIIRS).The geographically and temporally weighted regression model(GTWR)was used to quantify the infuence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled.The regression coefcient of urbanization was tested for signifcance(α=0.05),and the infuence of urbanization on schistosomiasis infection risk was analysed over time and across space based on signifcant regression coefcients.Variables studied included climate,soil,vegetation,hydrology and topography.Results The mean regression coefcient for urbanization(0.167)is second only to the leached soil area(0.300),which shows that the urbanization is the most important infuence factors for schistosomiasis infection risk besides leached soil area.The other important variables are distance to the nearest water source(0.165),mean minimum temperature(0.130),broadleaf forest area(0.105),amount of precipitation(0.073),surface temperature(0.066),soil bulk density(0.037)and grassland area(0.031).The infuence of urbanization on schistosomiasis infection risk showed a decreasing trend year by year.During the study period,the signifcant coefcient of urbanization level increased from−0.205 to−0.131.Conclusions The infuence of urbanization on schistosomiasis infection has spatio-temporal heterogeneous.The urbanization does reduce the risk of schistosomiasis infection to some extend,but the strength of this infuence decreases with increasing urbanization.Additionally,the efect of urbanization on schistosomiasis infection risk was greater than previous reported natural environmental factors.This study provides scientifc basis for understanding the infuence of urbanization on schistosomiasis,and also provides the feasible research methods for other similar studies to answer the issue about the impact of urbanization on disease risk.

Spatio-temporal Evolution Characteristics and Driving Forces of Winter Urban Heat Island:A Case Study of Rapid Urbanization Area of Fuzhou City,China

Under the influence of anthropogenic and climate change,the problems caused by urban heat island(UHI)has become increasingly prominent.In order to promote urban sustainable development and improve the quality of human settlements,it is significant for exploring the evolution characteristics of urban thermal environment and analyzing its driving forces.Taking the Landsat series images as the basic data sources,the winter land surface temperature(LST)of the rapid urbanization area of Fuzhou City in China was quantitatively retrieved from 2001 to 2021.Combing comprehensively the standard deviation ellipse model,profile analysis and GeoDetector model,the spatio-temporal evolution characteristics and influencing factors of the winter urban thermal environment were systematically analyzed.The results showed that the winter LST presented an increasing trend in the study area during 2001–2021,and the winter LST of the central urban regions was significantly higher than the suburbs.There was a strong UHI effect from 2001 to 2021with an expansion trend from the central urban regions to the suburbs and coastal areas in space scale.The LST of green lands and wetlands are significantly lower than croplands,artificial surface and unvegetated lands.Vegetation and water bodies had a significant mitigation effect on UHI,especially in the micro-scale.The winter UHI had been jointly driven by the underlying surface and socio-economic factors in a nonlinear or two-factor interactive enhancement mode,and socio-economic factors had played a leading role.This research could provide data support and decision-making references for rationally planning urban layout and promoting sustainable urban development.

Spatio-temporal Heterogeneity in the Performance of Rural Revitalization in Chifeng City of China:Based on a Range-wide EBM-GML Model

To solve the problems of rural revitalization performance research,a quantitative model of non-oriented range-wide EBM(Epsilon-Based Measure)-GML(Global-Malmquist)based on VRS(Variable Returns to Scale)conditions including non-desired outputs is constructed.A comprehensive spatio-temporal heterogeneity research index system of rural revitalization performance is also constructed.Taking the typical rural in Chifeng City as an example,the panel data from 2016-2020 are selected for empirical analysis,the conclusions and countermeasures are suggested as follows:1)In general,the rural revitalization performance of Chifeng City increases significantly during the five-year period,with significant spatio-temporal heterogeneity.The overall analysis shows that the overall performance value of rural revitalization in Chifeng City is 0.683 from 2016 to 2020.The highest performance value is 1 and the lowest performance value is 0.389.The performance growth rate increases year by year,with an average annual growth rate of 4.46%.2)From 2016 to 2020,the GML index of rural revitalization performance in Chifeng City is 1.174,showing an increasing trend.Based on the range of change of GML index,Chifeng City can be classified into three types:Continuous improvement,fluctuating improvement and fluctuating decline.3)Niujiayingzi,Guandongche,Zhaidamu,and Qiangangtai rural have the highest degree of technological progress.

Spatio-temporal epidemic type aftershock sequence model for Tangshan aftershock sequence

Shallow earthquakes usually show obvious spatio-temporal clustering patterns. In this study, several spatio-temporal point process models are applied to investigate the clustering characteristics of the well-known Tangshan sequence based on classical empirical laws and a few assumptions. The relative fit of competing models is compared by Akalke Information Criterion. The spatial clustering pattern is well characterized by the model which gives the best fit to the data. A simulated aftershock sequence is generated by thinning algorithm and compared with the real seismicity.

Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences

Human Activity Recognition(HAR)is an active research area due to its applications in pervasive computing,human-computer interaction,artificial intelligence,health care,and social sciences.Moreover,dynamic environments and anthropometric differences between individuals make it harder to recognize actions.This study focused on human activity in video sequences acquired with an RGB camera because of its vast range of real-world applications.It uses two-stream ConvNet to extract spatial and temporal information and proposes a fine-tuned deep neural network.Moreover,the transfer learning paradigm is adopted to extract varied and fixed frames while reusing object identification information.Six state-of-the-art pre-trained models are exploited to find the best model for spatial feature extraction.For temporal sequence,this study uses dense optical flow following the two-stream ConvNet and Bidirectional Long Short TermMemory(BiLSTM)to capture longtermdependencies.Two state-of-the-art datasets,UCF101 and HMDB51,are used for evaluation purposes.In addition,seven state-of-the-art optimizers are used to fine-tune the proposed network parameters.Furthermore,this study utilizes an ensemble mechanism to aggregate spatial-temporal features using a four-stream Convolutional Neural Network(CNN),where two streams use RGB data.In contrast,the other uses optical flow images.Finally,the proposed ensemble approach using max hard voting outperforms state-ofthe-art methods with 96.30%and 90.07%accuracies on the UCF101 and HMDB51 datasets.

Constructing a raster-based spatio-temporal hierarchical data model for marine fisheries application

Marine information has been increasing quickly. The traditional database technologies have disadvantages in manipulating large amounts of marine information which relates to the position in 3-D with the time. Recently, greater emphasis has been placed on GIS （geographical information system）to deal with the marine information. The GIS has shown great success for terrestrial applications in the last decades, but its use in marine fields has been far more restricted. One of the main reasons is that most of the GIS systems or their data models are designed for land applications. They cannot do well with the nature of the marine environment and for the marine information. And this becomes a fundamental challenge to the traditional GIS and its data structure. This work designed a data model, the raster-based spatio-temporal hierarchical data model （RSHDM）, for the marine information system, or for the knowledge discovery fi＇om spatio-temporal data, which bases itself on the nature of the marine data and overcomes the shortages of the current spatio-temporal models when they are used in the field. As an experiment, the marine fishery data warehouse （FDW） for marine fishery management was set up, which was based on the RSHDM. The experiment proved that the RSHDM can do well with the data and can extract easily the aggregations that the management needs at different levels.

Relationship between spatio-temporal evolution of soil pH and geological environment/surface cover in the eastern Nenjiang River Basin of Northeast China during the past 30 years

To illuminate the spatio-temporal variation characteristics and geochemical driving mechanism of soil pH in the Nenjiang River Basin,the National Multi-objective Regional Geochemical Survey data of topsoil,the Second National Soil Survey data and Normalized Difference Vegetation Index(NDVI)were analyzed.The areas of neutral and alkaline soil decreased by 21100 km^(2)and 30500 km^(2),respectively,while that of strongly alkaline,extremely alkaline,and strongly acidic soil increased by 19600 km^(2),18200 km^(2),and 15500 km^(2),respectively,during the past 30 years.NDVI decreased with the increase of soil pH when soil pH>8.0,and it was reversed when soil pH<5.0.There were significant differences in soil pH with various surface cover types,which showed an ascending order:Arbor<reed<maize<rice<high and medium-covered meadow<low-covered meadow<Puccinellia.The weathering products of minerals rich in K_(2)O,Na_(2)O,CaO,and MgO entered into the low plain and were enriched in different parts by water transportation and lake deposition,while Fe and Al remained in the low hilly areas,which was the geochemical driving mechanism.The results of this study will provide scientific basis for making scientific and rational decisions on soil acidification and salinization.

Spatio-Temporal Changes in the Rice Planting Area and Their Relationship to Climate Change in Northeast China: A Model-Based Analysis

Rice is one of the most important grain crops in Northeast China （NEC） and its cultivation is sensitive to climate change. This study aimed to explore the spatio-temporal changes in the NEC rice planting area over the period of 1980-2010 and to analyze their relationship to climate change. To do so, the CLUE-S （conversion of land use and its effects at small region extent） model was ifrst updated and used to simulate dynamic changes in the rice planting area in NEC to understand spatio-temporal change trends during three periods： 1980-1990, 1990-2000 and 2000-2010. The changing results in individual periods were then linked to climatic variables to investigate the climatic drivers of these changes. Results showed that the NEC rice planting area expanded quickly and increased by nearly 4.5 times during 1980-2010. The concentration of newly planted rice areas in NEC constantly moved northward and the changes were strongly dependent on latitude. This conifrmed that climate change, increases in temperature in particular, greatly inlfuenced the shift in the rice planting area. The shift in the north limit of the NEC rice planting area generally followed a 1＆#176;C isoline migration pattern, but with an obvious time-lag effect. These ifndings can help policy makers and crop producers take proper adaptation measures even when exposed to the global warming situation in NEC.

Theoretical analysis of the spatio-temporal evolution of the bulk-strain field based on a rheologic inclusion model

Based on the theoretical expression of the three-dimension rheologic inclusion model, we analyze in detail the spatio-temporal changes on the ground of the bulk-strain produced by a spherical rheologic inclusion in a semi-infinite rheologic medium. The results show that the spatio-temporal change of bulk-strain produced by the hard inclusion has three stages of different characteristics, which are similar to most of those geodetic deformation curves, but those by a soft inclusion do not. The α-stage is a long stage in which the precursors in both the near source region and the far field develop from the focal region to the periphery. The β-stage indicates a very rapid propagation of the precursors, so that they almost appear everywhere. During the γ-stage, the precursors in the far-field converge from the periphery, and the precursors in the near source region develop outwards. The theoretical results have been used to explain tentatively the stage characteristics of the spatio-temporal change of earthquake precursors.

Estimation of ocean primary productivity and its spatio-temporal variation mechanism for East China Sea based on VGPM model

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K 490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m 2 /d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m 2 /a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area.

耦合优化蚁群算法与P-Median model的选址模型设计

为节省城建部门对于公共体育设施的投入成本以及提高城市人民生活质量,以运动场所优化选址为例,提出一种新型设施选址模型。该模型主要基于P-Median model(最小化阻抗模型)根据需求点数量从全部候选设施选址中选择设施空间位置,让用户达到离自己最近设施距离成本总和最小的目的,对选址的基本原则和实际情况提出要求,构造目标函数用于优化后蚁群算法求解进行选址工作。优化蚁群算法实现基于Python语言模块,通过改进蚁群原始信息素,提升原有算法的收敛速度,求出目标函数最优解,可以很好地模拟对于运动场所的选址。用二者耦合进行优势互补所设计的选址模型来搜寻研究区蚁群信息素浓度残留最大的栅格像元,从而确定未被已有设施点服务半径覆盖的最佳设施点建立位置。实验结果表明,该新型选址模型相较于最小化阻抗模型与最大化覆盖模型,新增优化设施点使整体服务半径覆盖率分别高出10.42%和6.95%,适合求解较为精确且小规模空间下的选址问题。

Spatio-temporal Changes in Water Conservation Ecosystem Service During 1990–2019 in the Tumen River Basin, Northeast China

The water conservation(WC) function of ecosystems is related to regional ecological security and the sustainable development of water resources, and the assessment of WC and its influencing factors is crucial for ecological and water resource management.The Tumen River Basin(TRB) is located in the core of the Northeast Asian ecological network and has been experiencing severe ecological crises and water shortages in recent years due to climate change and human activities. However, these crises have not been fully revealed to the extent that corresponding scientific measures are lacking. This study analyzed the spatial and temporal evolution characteristics and drivers of WC in the TRB from 1990 to 2019 based on the water yield module of the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST) model. The results showed that: 1) under the combined effect of nature and socioeconomics, the WC depth of the TRB has slowly increased at a rate of 0.11 mm/yr in the past 30 years, with an average WC depth of 36.14 mm. 2) The main driving factor of the spatial variation in WC is precipitation, there is a significant interaction between precipitation and velocity, the interaction between each factor is higher than the contribution of a single factor, and the interactions between factors all have nonlinear enhancement and two-factor enhancement. 3) Among the seven counties and municipalities in the study area, the southern part of Helong City and the southeastern part of Longjing City are extremely important areas for WC(> 75 mm), and they should be regarded as regional water resources and ecological priority protection areas. It is foreseen that under extreme climate conditions in the future, the WC of the watershed is under great potential threat, and protection measures such as afforestation and forestation should begin immediately. Furthermore, the great interannual fluctuations in WC depth may place more stringent requirements on the choice of time scales in the ecosystem service assessment process.

Mshpy23:a user-friendly,parameterized model of magnetosheath conditions

Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind−Magnetosphere−Ionosphere Link Explorer(SMILE)will observe magnetosheath and its boundary motion in soft X-rays for understanding magnetopause reconnection modes under various solar wind conditions after their respective launches in 2024 and 2025.Magnetosheath conditions,namely,plasma density,velocity,and temperature,are key parameters for predicting and analyzing soft X-ray images from the LEXI and SMILE missions.We developed a userfriendly model of magnetosheath that parameterizes number density,velocity,temperature,and magnetic field by utilizing the global Magnetohydrodynamics(MHD)model as well as the pre-existing gas-dynamic and analytic models.Using this parameterized magnetosheath model,scientists can easily reconstruct expected soft X-ray images and utilize them for analysis of observed images of LEXI and SMILE without simulating the complicated global magnetosphere models.First,we created an MHD-based magnetosheath model by running a total of 14 OpenGGCM global MHD simulations under 7 solar wind densities(1,5,10,15,20,25,and 30 cm)and 2 interplanetary magnetic field Bz components(±4 nT),and then parameterizing the results in new magnetosheath conditions.We compared the magnetosheath model result with THEMIS statistical data and it showed good agreement with a weighted Pearson correlation coefficient greater than 0.77,especially for plasma density and plasma velocity.Second,we compiled a suite of magnetosheath models incorporating previous magnetosheath models(gas-dynamic,analytic),and did two case studies to test the performance.The MHD-based model was comparable to or better than the previous models while providing self-consistency among the magnetosheath parameters.Third,we constructed a tool to calculate a soft X-ray image from any given vantage point,which can support the planning and data analysis of the aforementioned LEXI and SMILE missions.A release of the code has been uploaded to a Github repository.

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。