Exploring nationally and regionally defined models for large area population mapping

Interactions between humans, diseases, and the environment take place across a range of temporal and spatial scales, making accurate, contemporary data on human population distributions critical for a variety of disciplines. Methods for disaggregating census data to finer-scale, gridded population density estimates continue to be refined as computational power increases and more detailed census, input, and validation datasets become available. However, the availability of spatially detailed census data still varies widely by country. In this study, we develop quantitative guidelines for choosing regionally-parameterized census count disaggregation models over country-specific models. We examine underlying methodological considerations for improving gridded population datasets for countries with coarser scale census data by investigating regional versus country-specific models used to estimate density surfaces for redistributing census counts. Consideration is given to the spatial resolution of input census data using examples from East Africa and Southeast Asia. Results suggest that for many countries more accurate population maps can be produced by using regionally-parameterized models where more spatially refined data exists than that which is available for the focal country. This study highlights the advancement of statistical toolsets and considerations for underlying data used in generating widely used gridded population data.     

Population at risk: using areal interpolation and Twitter messages to create population models for burglaries and robberies

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.     

基于土地利用类型提高人口格网数据空间精度的方法

高空间精度的人口格网数据具有空间分辨率高、人口空间分布特征准确的特点,在受灾人群估计、城市规划建设等领域有广泛的应用。针对已有的公开人口格网数据集(如WorldPop世界人口格网数据集)存在人口空间分布特征在小尺度上刻画不准确、空间分辨率较低的问题,本文使用东营市土地利用类型数据,结合地类权重和面积权重对WorldPop数据进行空间精度优化,获得东营市东营区黄河路街道25 m人口格网数据。相较于WorldPop数据,经过本文方法处理后的数据集空间分辨率更优,在可视化对比中,能够更准确地刻画人口分布特征,并在各地类人口占比统计中人口空间分布与用地单元分布一致性更高。该方法为获取小区域高空间精度人口格网数据提供了一种新思路。     

人口普查地理区域自动划分技术研究

针对中国现阶段人口普查模式和基础地理数据的拥有现状,该文总结归纳了国际上现有人口普查地理区域划分的技术和方法,比较了它们各自的优缺点,提出了基于Delaunay三角网对人口普查区域自动划分的技术。介绍了Delaunay三角网的特性及其空间划分的理论基础,论述了基于Delaunay三角网的人口普查区域划分技术、方法、过程和步骤,最后给出了该技术实验和应用实例。     

Some issues on urban census GIS designing

This paper first briefly looks back on the history of census GIS around the world, and then summarizes some preponderances of developing urban census GIS in China. And then a three-tier construction architecture for the urban census GIS is proposed. Finally, using the illustration of the census data of Guangzhou city, the paper analyzes and elaborates some issues on the urban census GIS designing, such as data management, data warehouse building, and data analysis.     

SOME ISSUES ON URBAN CENSUS GIS DESIGNING

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基于GIS的城市人口空间分布模型与应用——以长春市区为例

本文主要研究城市人口空间分布模型在长春市区的应用,目的在于模拟长春市区人口的空间分布情况。本文参考前人研究的基于城镇面积的城市人口密度系数模型,同时考虑交通网对城市人口分布的影响,提出适合长春市区人口空间分布的模型,生成100m(100m网格的人口数据空间分布图。为验证该模型的准确性,将建模所得数据与人口统计数据以街道为单位进行对比,发现模拟结果与调查数据基本相符。     

福建县域人口流动空间差异分析

针对当前国内对人口流动空间分布问题常采用的单一指标以及数理统计方法、忽略了空间效应、很难正确识别人口流动地域类型以及空间分布模式的问题,提出了一种以县域以人口净迁移率为横坐标和以人口总迁移率为纵坐标的复合指标法。首先对2010-2013年福建省85个县域的人口流动地域类型进行了测度和划分;随后,为进一步探索人口流动集聚程度,采用探索性空间数据分析方法进行了量化分析。结果表明:福建省县域人口流动空间分布差异显著;福建省县域人口流动的地理集聚特征显著且存在明显的正相关关系,并且"低-低"类型分布占据主要地位。研究结果为发现福建省县域人口流动空间模式,更好地为人口流动区域差异进行量化分析提供了强有力的支撑。     

人口信息空间可视化系统设计研究

人口问题始终是我国乃至世界关注的重大社会发展问题,因此将人口信息进行空间化总结和表达,并对这些信息进行深层次开发和应用就显得尤为重要。本文探讨了人口信息空间可视化的必要性和重要性及人口信息空间可视化系统设计中的关键科学与技术问题,提出了人口信息空间可视化系统设计框架、系统功能模块和数据库结构。结合第五次人口普查信息设计和制作了《中华人民共和国人口电子地图集》,图集提供1 0个图组共计近2 0 0幅地图和近1 0 0 0个分省、分地区和分县人口指标以及强大的系统功能,形成交互的人口空间认知的可视化环境,形象地表达了人口的地区差异、分布特征;揭示了人口要素间的相互关系以及与区域各种要素制约关系,提高对我国人口问题的空间认知水平。     

基于扩展空间句法的城区人口密度估算方法

城市人口密度是人口空间分布的重要指标,对城市交通、安全、规划和管理都有着重要意义。针对传统的人口密度估算方法在数据要求、可操作性以及精度方面的不足,本文提出一种基于扩展空间句法的城市人口密度估算方法。该方法通过城市空间可达性与城市行人流量的相关关系,估算城市人口密度的空间分布情况。经过实验验证表明,与传统估算方法相比,该方法需要的人口统计数据较少,可操作性强,与G IS软件无缝融合,通过反距离权重法(IDW)可使模拟估算结果连续,试验验证表明该方法适用于城镇地区人口密度估算。     

协同遥感信息与统计信息的人口空间格局分析

针对人口空间格局分布分析不足的问题,借助遥感信息与基本统计信息,引入人口地理集中度、探索性空间数据分析和地理加权回归模型,定量地分析了特征因子在市域范围上的空间异质性。人口集中指数与Moran指数能有效地反映空间事物之间的密切作用关系,在产业空间分布中能较好地评价集聚效应,反映空间分布状态。以长江经济带为研究区域,对人口空间分布进行了研究,得出了“圈层集中-东西对立-南北差异-四周分散”的分布特征,并从经济、社会、环境、土地利用方面分析原因,为人口合理增长和资源分配提供了参考。     

贫困人口社会空间结构分析方法研究

以贫困人口为例进行人口的社会空间结构分析,挖掘贫困人口空间结构的特征和规律,发现其具有空间差异的社会特征,为掌握贫困状况的态势和扶贫工作的进展,指导人口与资源在空间上的优化配置提供决策支持。     

夜间灯光数据支持下的广州市人口空间化

了解区域人口的空间分布,能够为城市精细化管理和城市规划提供有力的支撑数据,对提高城市发展水平有重要的现实意义。为此,本文以“珞珈一号”(LJ-1 01)夜间灯光(NTL)影像为基础数据,以广州市为研究区,结合人口估算模型等方法,开展基于NTL数据的人口空间化研究。结果表明:LJ-1 01 NTL数据能够有效地应用于人口空间化研究。人口空间化后,广州市人口分布具有显著的“一主中心,多核心”的特征,各区域内部的人口分布差异可被清晰地展示与区分。本文结果对城市规划与城市管理具有一定价值的辅助支撑作用。     

人口GIS在天津市人口社会空间结构研究中的应用

阐述了应用人口GIS进行天津市人口社会空间结构研究的方法,概括出影响天津市人口社会空间结构的四个主要因素,并对天津市人口社会空间结构进行分区。天津市的人口空间结构可以分成行政、金融、商业、文化中心区,工业居住混杂区,工业、农业混合区和农业人口居住区,且四个分区成同心圆模式分布。     

大数据时代的空间分析

目的 近年来,大数据越来越多地被用来描述正在到来的信息爆炸的时代,也引起了产学研政府部门的高度重视。首先综述了大数据和空间大数据的特点和最新发展。其次,从GIS基础理论方法的角度回顾和评述了空间分析、空间建模和空间优化等三个地理信息科学的核心议题。在此基础上,引申出空间理论方法背后隐含的空间哲学和空间思维。最后指出了大数据时代地理信息科学发展的机遇与挑战。     

Analysis of population dynamics using satellite remote sensing and US census data

The population dynamics from 1991 to 2006 for the seven-county Twin Cities Metropolitan Area (TCMA), Minnesota, USA, was analysed in this study. Per cent impervious surface areas (%ISA) for 1991, 1999 and 2006 were derived from Landsat Thematic Mapper (TM) images and were modified using two different masking methods. The modified %ISA images of 1991 and 1999 were correlated with 1990 and 2000 census block group data of the ‘two highly developed counties’, ‘five suburban counties’ and ‘all seven counties.’ Populations of both years were then modelled, assessed and compared. Next, the statistical models based on the 1999 %ISA and 2000 census data were applied to the 2006 residential %ISA image to estimate the 2006 population. These 2006 estimates were compared with census county-level population projections for 2006. In comparison to Method A, which uses ‘adjusted %ISA images’ by masking out highway centrelines and areas that have greater than 75% imperviousness, Method B based on ‘pure residential %ISA image’ has higher coefficient of determination (R ²) and much lower, consistent mean absolute relative errors (MARE). For both methods, the strongest R ² and lowest MARE values between modelled population density and true density were found in the five-county model, followed by the seven-county model. The two-county model ranks last in terms of model performance for both years. In general, populations for the two highly developed counties were underestimated whereas the opposite was true for the five suburban counties. Population was most accurately estimated based on data from counties with the same or similar characteristics. By comparing the 1990/1991 and 1999/2000 models, we also found that the rate of population density per unit of impervious surface declined from 1991 to 1999. High accuracy was achieved when applying the 1999/2000 model to predict the 2006 population, suggesting that the relationship between per cent imperviousness and population density were relatively stable between 1999 and 2006.     

城市基础地理空间勘测数据共享平台设计

利用原有平台进行城市基础地理空间勘测数据共享时,元数据数量过大,无法对元数据进行管理,请求次数在160次以内数据服务响应时间较长,因此需要设计一种新的城市基础地理空间勘测数据共享平台.该平台共由八个模块构成,包括服务器模块、基础地理空间勘测数据管理模块、基础地理空间勘测数据处理模块、网络服务模块、地图操作模块、元数据管...     

Big spatial data for urban and environmental sustainability

ABSTRACT

Eighty percent of big data are associated with spatial information, and thus are Big Spatial Data (BSD). BSD provides new and great opportunities to rework problems in urban and environmental sustainability with advanced BSD analytics. To fully leverage the advantages of BSD, it is integrated with conventional data (e.g. remote sensing images) and improved methods are developed. This paper introduces four case studies: (1) Detection of polycentric urban structures; (2) Evaluation of urban vibrancy; (3) Estimation of population exposure to PM2.5; and (4) Urban land-use classification via deep learning. The results provide evidence that integrated methods can harness the advantages of both traditional data and BSD. Meanwhile, they can also improve the effectiveness of big data itself. Finally, this study makes three key recommendations for the development of BSD with regards to data fusion, data and predicting analytics, and theoretical modeling.     

Characterizing European urban settlements from population data: a cartographic approach

ABSTRACT

The cartographic identification and characterization of urban settlements is problematic, particularly in varied areas or in large geographical extensions. This is due to the divergence between morphological area structures and data attribution, which is generally available at the level of administrative units. Most existing experiences focus on small regions or use indirect data, from which only indirect information can be derived. This paper proposes an identification of urban settlements in the European Union space, which combines urban population and shape through geographic information system (GIS) techniques. For that purpose, 1 km² cells with associated population data are used. A procedure is developed establishing three different types of urban settlements, according to population and population density values: high-density urban clusters, small and medium-sized towns, and very small towns. A validation of this procedure is performed using direct survey from local experts in 10 selected study areas. The final results show that 78,307 urban settlements can be identified: 88.17% of them are classified as “very small towns,” 10.75% as “small and medium-sized towns,” and 1.08% as high-density urban clusters. This exercise generates new information for the European Union and surrounding countries, and yields the basis for further research. All GIS operations are performed using vector layers, which is not usual in large-area regional studies.     

基于多源空间数据的山区人口分布模拟

人口资源是制约山区发展的关键因素,其分布状况在一定程度上反映和决定了山区的资源环境安全状况和社会经济发展水平.在分析川滇黔接壤地区山区人口分布影响因素的基础上结合已有方法,构建了适合山区人口数据空间化的模型.以2007年人口统计数据为基础,以居民点作为人口分布指示因子,利用GIS软件工具,分析了居民点分布与地貌形态、土地利用、道路以及水系间的关系.基于多源空间数据融合的思想,引进了居民点缓冲区的概念,以较客观的赋权方式确定影响因子权重,实现山区人口统计数据的空间化.结果表明,通过融合产生的人口密度与乡镇级人口密度的相关性均在0.80以上,结果可靠,为进一步分析山区人口分布格局提供了重要的基础数据.