共查询到17条相似文献，搜索用时 225 毫秒
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朝鲜人口统计数据空间化是解决朝鲜统计数据与自然要素数据融合分析的重要途径。基于朝鲜市郡级人口普查数据,将GIS空间分析技术与统计学方法相结合,分析了朝鲜人口密度与空间因子的关系,采用多元回归的方法建立了朝鲜人口密度空间化模型,在GIS平台中实现了朝鲜人口密度的空间格网化模拟,并利用地理探测器对影响朝鲜人口密度空间分布因素的决定力进行了有效探测。结果表明,多元回归模型拟合精度达到0.769,生成的栅格人口密度数据与朝鲜三级行政区人口统计数据保持一致。同时,影响该地区人口密度的因子依次为道路网密度、居民点密度、居民地指数、海拔、坡度和耕地指数。 相似文献
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基于GIS的区域人口密度空间分布模拟——以张家界市永定区为例 总被引：1，自引：0，他引：1
人口统计数据空间化是解决统计数据与自然要素数据融合分析的有效途径。本文以张家界市永定区为研究单元,对小尺度区域的人口密度空间分布模拟进行了初步研究。文章根据2005年《永定区统计年鉴》所统计的人口数据,分析了永定区各乡镇平均人口密度与土地利用类型指数及地形指数(平均高程和平均坡度)之间的相关性。基于相关性分析,以GIS软件与SPSS统计软件为工具,运用多元回归的思想建立了人口数据空间化模型,同时生成了永定区250m×250m空间分辨率的栅格人口密度图。结果表明,模型模拟的精度较高,模拟过程具有较强的可操作性,可为县域尺度人口空间分布的应用研究提供借鉴。同时,研究结果为永定区推进城市化进程,提高人口、资源和环境的科学管理提供了理论基础。 相似文献
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分析了常用的表示人口分布的方法及其不足,提出了将人口统计数据空间分布化的方法,将研究区域划分为一定分辨率的格网,用距离衰减函数将人口密度估计值分配到每个格网上,每个格网上的人口是均匀分布的,随着格网分辨率的提高,就可以模拟出符合人口详细分布的人口密度空间连续分布模型,并通过实验说明该方法是可行的. 相似文献
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基于神经网络和GIS的广西都安县人口数据空间化研究 总被引：1，自引：0，他引：1
人口数据的空间化是进行小尺度地理分析的基础,本文在分析土地利用与人口分布关系的基础上,发现耕地、居民点以及水域是影响人口分布的主要因素,在GIS中对人口及其土地利用等数据进行分析,同时,利用BP神经网络非线性模型,对广西都安县人口数据进行空间化研究.通过神经网络的模拟和数据的调整,最终生成的栅格人口分布与实际的分布保持大体一致. 相似文献
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一种人口连续分布模型的研究 总被引：3，自引：0，他引：3
分析了常用的表示人口分布的方法及其不足，提出了将人口统计数据空间分布化的方法，将研究区域划分为一定分辨率的格网，用距离衰减函数将人口密度估计值分配到每个格网上，每个格网上的人口是均匀分布的，随着格网分辨率的提高，就可以模拟出符合人口说细分布的人口密度空间连续分布模型，并通过实验说明该方法是可行的。 相似文献
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人口统计数据的空间化能真实地反映人口空间分布情况,对研究人口分布的区域差异及其发展过程起指导作用,在此过程中,空间化格网尺度效应影响着模型的精度。为探究人口空间化的尺度适宜性问题,本文以四川省为研究区域,基于全球地表覆盖数据(Globle Land 30,GL30)及其派生的网格数据,对四川省2010年人口普查统计数据进行了人口空间化模型的尺度效应探究。通过基于人口密度、地表覆盖类型实现了研究区域的二次分区,实现了模型精度的提高。在此基础上,探究了县级尺度上在30 m、240 m、450 m、660 m、870 m、1 080 m 6个网格尺度上人口空间化的精度,得出县级尺度上在450 m网格尺度下,人口空间化精度最优。 相似文献
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基于2010年《山东统计年鉴》和全国第六次人口普查数据,本文以县域为研究单元,通过空间自相关分析人口的空间分布模式,运用因子分析和Pearson相关分析探究人口空间分布模式的影响因素。研究结果表明:山东省人口分布呈现"东北-西南"的空间分布模式,人口空间分布整体上呈现显著的空间集聚,主要集中在青岛市的中心城区;经济增长因素和地形条件是山东省人口空间分布模式形成的主要推动力。 相似文献
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Serkan Ural Ejaz Hussain Jie Shan 《International Journal of Applied Earth Observation and Geoinformation》2011
Geospatial distribution of population at a scale of individual buildings is needed for analysis of people's interaction with their local socio-economic and physical environments. High resolution aerial images are capable of capturing urban complexities and considered as a potential source for mapping urban features at this fine scale. This paper studies population mapping for individual buildings by using aerial imagery and other geographic data. Building footprints and heights are first determined from aerial images, digital terrain and surface models. City zoning maps allow the classification of the buildings as residential and non-residential. The use of additional ancillary geographic data further filters residential utility buildings out of the residential area and identifies houses and apartments. In the final step, census block population, which is publicly available from the U.S. Census, is disaggregated and mapped to individual residential buildings. This paper proposes a modified building population mapping model that takes into account the effects of different types of residential buildings. Detailed steps are described that lead to the identification of residential buildings from imagery and other GIS data layers. Estimated building populations are evaluated per census block with reference to the known census records. This paper presents and evaluates the results of building population mapping in areas of West Lafayette, Lafayette, and Wea Township, all in the state of Indiana, USA. 相似文献
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《制图学和地理信息科学》2013,40(2):103-121
This paper describes techniques to compute and map dasymetric population densities and to areally interpolate census data using dasymetrically derived population weights. These techniques are demonstrated with 1980-2000 census data from the 13-county Atlanta metropolitan area. Land-use/land-cover data derived from remotely sensed satellite imagery were used to determine the areal extent of populated areas, which in turn served as the denominator for dasymetric population density computations at the census tract level. The dasymetric method accounts for the spatial distribution of population within administrative areas, yielding more precise population density estimates than the choroplethic method, while graphically representing the geographic distribution of populations. In order to areally interpolate census data from one set of census tract boundaries to another, the percentages of populated areas affected by boundary changes in each affected tract were used as adjustment weights for census data at the census tract level, where census tract boundary shifts made temporal data comparisons difficult. This method of areal interpolation made it possible to represent three years of census data (1980, 1990, and 2000) in one set of common census tracts (1990). Accuracy assessment of the dasymetrically derived adjustment weights indicated a satisfactory level of accuracy. Dasymetrically derived areal interpolation weights can be applied to any type of geographic boundary re-aggregation, such as from census tracts to zip code tabulation areas, from census tracts to local school districts, from zip code areas to telephone exchange prefix areas, and for electoral redistricting. 相似文献
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基于扩展空间句法的城区人口密度估算方法 总被引：1，自引：0，他引：1
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。 相似文献
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Thomas Alan Morton 《国际地球制图》2013,28(2):143-163
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. 相似文献
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随着城市化发展的推进,城市人口密度越大,越来越多的人涌入城市。在城市人口密度大的当今社会,一些因素往往会引起局部地区人口密度增加,形成局部人口密集区域。引起人口密度增加的因素很多,教育文化产业就是原因之一。近年来对于人口密度的分析,主要是通过对DMSP/OLS夜间灯光数据进行分析,对人口密度影响因素的研究很少。而本文通过热力图和灯光数据对人口密度进行分析,确定教育文化产业分布情况对人口密度有着重要的影响。 相似文献
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为揭示城镇化背景下武汉市人口时序增长趋势和人口空间分布格局演变特征,本文基于1990年第四次、2000年第五次、2010年第六次全国人口普查和2014年武汉市人口普查数据,运用统计学原理和GIS空间分析方法,分析了武汉市人口增长的时空变化规律;应用人口密度空间分布的数学模型,得到武汉市人口空间分布格局的演变趋势。人口增长研究表明:1990年以后,武汉市人口数量迅速增长,总体上形成了中心聚集、外围扩散的空间发展格局。空间分布研究表明:1)武汉市的人口密度分布更加符合Clark模型,主城区Smeed模型拟合效果更好。近25年来,武汉市城镇化进程迅速,人口向主城区聚集。随着时间发展,主城区逐步呈现初级阶段的郊区化。2)武汉市主城区人口空间分布已经出现多中心化的趋势,并且已经有两个街道发育成为人口次中心。研究结果可为武汉市人口相关决策的制定和城市结构调整提供参考依据,有助于认识我国中部崛起城市的发展规律,为其他城市的发展和规划提供参考和借鉴。 相似文献