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1.
2019年末至2020年初新型冠状病毒(COVID-19)的快速传播对中国与世界的公共卫生带来巨大的挑战。如何科学合理地评估新型冠状病毒传播风险并制定相应防疫管控措施,是各国所面临的难题,也是科学防治与精准施策的重要依据之一。作为我国最重要的城市群之一,粤港澳大湾区受本次新型冠状病毒影响较大,且春节假期后大量的复工回流人口进一步带来潜在的传播风险。本文面向粤港澳大湾区新型冠状病毒传播风险评估的紧迫需求,结合大湾区多源城市时空大数据与流行病动力学模型,构建适宜大湾区的改进模型,并对新型冠状病毒在大湾区的传播风险和各类防疫管控措施效果进行评估与模拟。首先,引入动态复工回流人口和聚集热点改进现有动力学模型(SEIR模型),对现有动力学模型在不同空间评估单元的传播参数进行纠偏,加强模型在大湾区评估中的适宜性;利用手机信令等多源城市大数据,构建更精细化的人口、疾病流动矩阵和相应的传染病动力学模型,以满足各级防疫部门精细化(如村(社区)级)风险评估的迫切需求。模拟结果表明,相对经典SEIR模型,改进模型在大湾区的传播风险评估中具有更强的适宜性;大湾区高强度的人口流动为病毒的传播带来较高的风险;防疫部门所采取各类管控措施对病毒在大湾区的传播具有较强的抑制作用。 相似文献
2.
Current methods for estimating the incidence and prevalence of non‐legal drug use tend to be retrospective and are not capable of forecasting spatial characteristics. This paper details the development of a GIS model for forecasting and displaying spatio‐temporal trends in non‐legal drug use. It builds upon a current model that estimates levels of drug use, using GIS to develop and visualise the spatial dimension and to predict levels of use for unknown locations using radial basis functions with a thin spline interpolator. The model is calibrated against known data for the onset and spread of heroin use. Results of validation and cross validation of the interpolated surfaces give some confidence to the accuracy of the method. It provides a first stage in a process to develop more complex models that might be used to examine the introduction of new drug use practices, socio‐economic characteristics of different drug use habits, harm reduction measures or to further examine the role of space in the spread of drug use. 相似文献
3.
Tara Sharma Jeff Carmichael Brian Klinkenberg 《Journal of the Indian Society of Remote Sensing》2005,33(2):353-363
The transition to agricultural sustainability involves difficult choices and an understanding of the complex trade-offs associated
with agricultural activities. Decision support tools and techniques assist in making the informed decisions for a transition
to sustainable agriculture. Georgia Basin — Quite Useful Ecosystem Scenario Tool (GB-QUEST) is a computer-based, user-friendly
tool that has been developed to look at the future sustainability scenarios of the Georgia Basin in British Columbia. The
objective of this paper is to describe the agricultural model that has been developed for implementation in GB-QUEST. We present
its framework, spatial methodology for land-use simulation, and the initial results of its application.
The agriculture model is a spatial model that examines the social, economic and environmental consequences of user-defined
agricultural development strategies. The model simulates changes in the Georgia Basin from the year 2000 to 2040 in decadal
steps. User choices of local and global development factors, along with their "worldview" choices, are important inputs in
the model that determine the effects on environmental and socio-economic systems. The model has two components — Generation
of land-use scenarios, and Development of Indicator models. The first component uses cell-based spatial algorithms to simulate
likely changes/conversions in land-use up to the year 2040. The approach used here integrates the functionality of Multi-Criteria
Evaluation (MCE) and Cellular Automata (CA) techniques in order to simulate the land-use conversions. It uses Geographic Information
Systems (GIS) and remote sensing techniques for creating, storing and deriving the data sets required for the model. The second
component develops the indicator models for relating scenario variables to socio-economic and environmental variables such
as physical and economic yields, economic operation costs and nutrient surplus per unit area. These indicator models are used
to evaluate land-use scenarios generated by the users. The model encourages understanding of sustainability, by allowing one
to explore different possible scenarios of the future for their environmental and socio-economic consequences. 相似文献
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回顾了两种类型的时空数据模型，发展了面向对象的规划道路中线时空数据模型，进一步实现了对规划道路中线对象的查询及更新维护。该模型具有充分利用GIS已有的空间分析和方便实现时态分析的功能，同时也具有数据维护和历史数据恢复方便简单，空间信息没有冗余，时态信息冗余小，且能表达变化原因等特点。 相似文献
6.
以手足口病为例,介绍了地理信息的空间统计技术在传染病时空传播规律研究中的应用,包括传染病空间分布模式研究、传染病聚集性分析、传染病扩散传播模式分析、传染病发病率空间自相关分析及传染病发病率空间回归模型预测方面的研究,为传染病防治决策提供科学依据,具有一定的实用性。 相似文献
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8.
Bayesian networks and agent-based modeling approach for urban land-use and population density change: a BNAS model 总被引：1，自引：0，他引：1
Land-use change models grounded in complexity theory such as agent-based models (ABMs) are increasingly being used to examine evolving urban systems. The objective of this study is to develop a spatial model that simulates land-use change under the influence of human land-use choice behavior. This is achieved by integrating the key physical and social drivers of land-use change using Bayesian networks (BNs) coupled with agent-based modeling. The BNAS model, integrated Bayesian network–based agent system, presented in this study uses geographic information systems, ABMs, BNs, and influence diagram principles to model population change on an irregular spatial structure. The model is parameterized with historical data and then used to simulate 20 years of future population and land-use change for the City of Surrey, British Columbia, Canada. The simulation results identify feasible new urban areas for development around the main transportation corridors. The obtained new development areas and the projected population trajectories with the“what-if” scenario capabilities can provide insights into urban planners for better and more informed land-use policy or decision-making processes. 相似文献
9.
The purpose of this paper is to suggest estimators for the parameters of spatial models containing a spatially lagged dependent
variable, as well as spatially lagged independent variables, and an incomplete data set. The specifications allow for nonstationarity,
and the disturbance process of the model is specified non-parametrically. We consider various scenarios concerning the pattern
of missing data points. One estimator we suggest is based on a smaller but complete subset of the sample; another is based
on a larger but incomplete subset of the sample. We give large sample results for both of these cases. 相似文献
10.
High spatial resolution mapping of natural resources is much needed for monitoring and management of species, habitats and landscapes. Generally, detailed surveillance has been conducted as fieldwork, numerical analysis of satellite images or manual interpretation of aerial images, but methods of object-based image analysis (OBIA) and machine learning have recently produced promising examples of automated classifications of aerial imagery. The spatial application potential of such models is however still questionable since the transferability has rarely been evaluated.We investigated the potential of mosaic aerial orthophoto red, green and blue (RGB)/near infrared (NIR) imagery and digital elevation model (DEM) data for mapping very fine-scale vegetation structure in semi-natural terrestrial coastal areas in Denmark. The Random Forest (RF) algorithm, with a wide range of object-derived image and DEM variables, was applied for classification of vegetation structure types using two hierarchical levels of complexity. Models were constructed and validated by cross-validation using three scenarios: (1) training and validation data without spatial separation, (2) training and validation data spatially separated within sites, and (3) training and validation data spatially separated between different sites.Without spatial separation of training and validation data, high classification accuracies of coastal structures of 92.1% and 91.8% were achieved on coarse and fine thematic levels, respectively. When models were applied to spatially separated observations within sites classification accuracies dropped to 85.8% accuracy at the coarse thematic level, and 81.9% at the fine thematic level. When the models were applied to observations from other sites than those trained upon the ability to discriminate vegetation structures was low, with 69.0% and 54.2% accuracy at the coarse and fine thematic levels, respectively.Evaluating classification models with different degrees of spatial correlation between training and validation data was shown to give highly different prediction accuracies, thereby highlighting model transferability and application potential. Aerial image and DEM-based RF models had low transferability to new areas due to lack of representation of aerial image, landscape and vegetation variation in training data. They do, however, show promise at local scale for supporting conservation and management with vegetation mappings of high spatial and thematic detail based on low-cost image data. 相似文献
11.
Population at risk of crime varies due to the characteristics of a population as well as the crime generator and attractor places where crime is located. This establishes different crime opportunities for different crimes. However, there are very few efforts of modeling structures that derive spatiotemporal population models to allow accurate assessment of population exposure to crime. This study develops population models to depict the spatial distribution of people who have a heightened crime risk for burglaries and robberies. The data used in the study include: Census data as source data for the existing population, Twitter geo-located data, and locations of schools as ancillary data to redistribute the source data more accurately in the space, and finally gridded population and crime data to evaluate the derived population models. To create the models, a density-weighted areal interpolation technique was used that disaggregates the source data in smaller spatial units considering the spatial distribution of the ancillary data. The models were evaluated with validation data that assess the interpolation error and spatial statistics that examine their relationship with the crime types. Our approach derived population models of a finer resolution that can assist in more precise spatial crime analyses and also provide accurate information about crime rates to the public. 相似文献
12.
The transmission of respiratory diseases such as COVID-19 is exacerbated in densely populated urban areas and crowded indoor settings. Despite the majority of transmissions occurring in such settings, controlling viral spread through individual-level contacts indoors remains challenging. Experimental studies have investigated the transmission patterns of respiratory behaviors such as coughing or sneezing in controlled spatial environments. However, the effects of dynamic movement and spatial structures have been ignored, making it difficult to apply findings to urban policy and planning. To address this gap, we developed agent-based simulations to investigate individual virus inhalation patterns across multiple scenarios in a symmetrical and formulaic indoor space. We conducted sensitivity analysis using regression emulator models to identify significant factors for viral transmission. Our results indicate positive associations with viral transmission in descending order of: (1) stay time; (2) encounter frequency; and (3) initial infected population; while negative associations are: (4) mask wearing; (5) distance to infected people; (6) nearest infected people's mask wearing; and (7) distance to entrance. We also found that narrow passages between obstacles increase virus transmission from breathing. Furthermore, we conducted a case study to investigate the potential of reducing the amount of individually inhaled virus by controlling behaviors and spatial environments. Our findings suggest that mask wearing and reduced stay time can substantially reduce transmission risk, while a large number of contacts and high grouping time result in the growth of the infected population at a certain threshold. These results provide guidance for decision makers to formulate guidelines for curbing the spread of respiratory diseases in indoor spaces. 相似文献
13.
数字制图与GIS空间分析由于应用不同导致相应软件和数据不能共享,其根本原因是二者采用了不同的空间数据模型。在分析面向数字制图数据模型和面向GIS空间分析数据模型的特征基础上,提出了一种一体化的空间数据模型。该模型以面向GIS空间分析数据模型为主,面向数字制图数据模型为辅,在几何层次融合了拓扑数据模型和实体数据模型。最后,设计和开发了相应的原型系统,验证了模型的合理性和可行性。 相似文献
14.
GIS中面向对象时空数据模型 总被引：105，自引：4，他引：105
由于当前的地理信息系统软件难以处理时态现象，时态数据模型已忧为ＧＩＳ领域的一个研究热点。许多学者提出了多种时态数据模型。本文作者在提出了矢量栅格一体化的面向对象数据模型之后，再一次对时态问题进行了分析研究，净面向对象的数据模型扩充到时间维。有三种方法表达空间对象的历史变化。第一种是将版本信息记录在关系表上；第二种是将版本信息标记在记录上；第三种是将版本信息标记在属性上。本文采用面向对象的方法，将版 相似文献
15.
Enhancing a GIS Cellular Automata Model of Land Use Change: Bayesian Networks, Influence Diagrams and Causality 总被引：1，自引：0，他引：1
Cellular Automata (CA) models at present do not adequately take into account the relationship and interactions between variables. However, land use change is influenced by multiple variables and their relationships. The objective of this study is to develop a novel CA model within a geographic information system (GIS) that consists of Bayesian Network (BN) and Influence Diagram (ID) sub‐models. Further, the proposed model is intended to simplify the definition of parameter values, transition rules and model structure. Multiple GIS layers provide inputs and the CA defines the transition rules by running the two sub‐models. In the BN sub‐model, land use drivers are encoded with conditional probabilities extracted from historical data to represent inter‐dependencies between the drivers. Using the ID sub‐model, the decision of changing from one land use state to another is made based on utility theory. The model was applied to simulate future land use changes in the Greater Vancouver Regional District (GVRD), Canada from 2001 to 2031. The results indicate that the model is able to detect spatio‐temporal drivers and generate various scenarios of land use change making it a useful tool for exploring complex planning scenarios. 相似文献
16.
城市人口是构成城市的社会主体,是城市发展中最为活跃的因素。城市人口时空分布是城市管理需要掌握的重要信息。正确、精细化的城市人口分布数据对于城市运行与规划、城市经济发展和人民生活具有极为重要的意义,因此城市人口时空分布估计是城市地理学需要解决和研究的热点问题之一。本文以城市人口时空分布估计的关键点为核心,从以下几个方面展开综述:①空间分布单元划分方法,即城市人口分布的空间划分方式;②主要的模型和方法,从模型思想发展过程和估计对象的角度总结了6类方法并进行详细阐述;③估计结果在城市发展中的主要应用。在此基础上,本文指出了目前人口时空分布研究在空间单元构建、建模数据、建模思想和结果验证上存在的问题,同时探讨了未来的研究方向。 相似文献
17.
GIS技术在无线电波场强分析中的应用研究 总被引：2，自引：0，他引：2
无线电波场强分析在广播电视台站规划中是一项重要的工作,采用传统的电波传播模型进行场强预测时,相关的计算大多依据纸质地图用手工进行,工作强度高,结果精确性低。本文结合地理信息系统(GIS)的空间数据管理、数字地形分析等技术,构建台站与发射机实体对象,基于地理空间信息环境实现了典型电波传播场强分析模型,提高了场强计算的效率和空间位置精度,同时将人口分布信息应用到模型中,增强了台站规划的科学性;最后讨论了GIS技术在电波传播模型中进一步应用的前景。 相似文献
18.
结合平面坐标转换四参数模型及误差传播定律,对转换参数的误差及不同空间分布的点位转换精度进行分析,得到任意点处转换误差的求解模型。最后,利用模拟数据通过对公共点引入不同级别的误差来验证本文方法的正确性。 相似文献
19.
Calibration of cellular automata models using differential evolution to simulate present and future land use 
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下载免费PDF全文 A key issue in cellular automata (CA) modeling is the minimization of the differences between the actual and simulated patterns, which can be mathematically formulated as an objective function. We develop a new hybrid model (termed DE‐CA) by integrating differential evolution (DE) into CA to solve the objective function and retrieve the optimal CA parameters. Constrained relations among factors were applied in DE to generate different sets of CA parameters for prediction of future scenarios. The DE‐CA model was calibrated using historical spatial data to simulate 2016 land use in Kunming and predict multiple scenarios to the year 2026. Assessment of quantitative accuracy shows that DE‐CA yields 92.4% overall accuracy, where 6.8% is the correctly captured urban growth; further, the model reported only 5.0% false alarms and 2.6% misses. Regarding the simulation ability, our new CA model performs as well as the widely applied genetic algorithm‐based CA model, and outperforms both the logistic regression‐based CA model and a no‐change NULL model. We projected three possible scenarios for the year 2026 using DE‐CA to adequately address the baseline urban growth, environmental protection and urban planning to show the strong prediction ability of the new model. 相似文献
20.
The hierarchid tessellation model belongs to a class of spatial data models based on the recursive decomposition of space. The quadtree is one such tessellation and is characterized by square cells and a 1:4 decomposition ratio. To relax these constraints in the tessellation, a generalized hierarchical tessellation data model, called Adaptive Recursive Tessellations (ART), has been proposed. ART increases flexibility in the tessellation by the use of rectangular cells and variable decomposition ratios. In ART, users can specify cell sizes which are intuitively meaningful to their applications, or which can reflect the scales of data. ART is implemented in a data structure called Adaptive Recursive Run-Encoding (ARRE), which is a variant of two-dimensional run-encoding whose running path can vary with the different tessellation structures incorporated in an ART model. Given the recognition of the benefits of implementing statistical spatial analysis in GIS, the use of hierarchical tessellation models such as ART in spatial analysis is discussed. Three examples are introduced to show how ART can: (1) be applied to solve the quadrat size problem in quadrat analysis of point patterns; (2) act as the data model in the variable resolution block kriging technique for geostatistical data to reduce variation in kriging error; and (3) facilitate the evaluation of spatial autocorrelation for area data at multiple map resolutions via the construction of a connectivity matrix for calculating spatial autocorrelation indices based on ARRE. 相似文献