资源简介

摘要： 基于土地利用数据的人口统计数据空间化方法,在处理过程中会出现同一土地利用类型下人口难以细分的情况,从而影响人口空间数据精度。引入夜间灯光信息并提出了一种基于夜间灯光强度对城镇居民地再分类的人口空间化方法,以改善人口空间数据精度。基于DMSP/OLS夜间灯光及土地利用数据,以长江中游4省为研究区进行方法试验。研究结果显示:利用夜间灯光数据对城镇居民地再分类后,各分区模型的调整R2都提高到了0.8以上,人口空间数据总体平均相对误差较重分类前降低了12.32%。说明该方法在提高传统人口数据空间化模型精度的基础上能够细化城镇居民地人口空间分布。 关键词： 人口数据空间化;  城镇居民用地;  DMSP/OLS     Abstract: Precious studies have approveds the advantages in remotely sensed land cover to stimulate spatial distribution of population.However,these studies also showed the shortcomings in revealing the details of population distribution within a single land-use type.This study presents a method which can improve the spatial distributing of census data:re-classification of urban residential areas.By using DMSP/OLS night\|light imagery data as an information source indicated the urbanization level,the urban residential land-use data in the middle reaches of the Yangtze River which were reclassified under the support of GIS technology.based on the population regionalization,a linear regression models were established with integrating the reclassified urban residential land\|use data with the rural residential land\|use data.Then the models were employed to estimate the population distribution in the middle reaches of the Yangtze River in 2010.The results showed that the urban residential land\|use data reclassified by the night\|time imagery offered urban population distribution with a better accuracy,with R2 of partition models raised 0.8 and the overall average relative error reduced by 12.32%.Compared with the conventional statistical regression method,the modified model can improve the spatial accuracy of population data at county scale.

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