spatialization of statistical population DMSP/OLS NDVI human

  本文关键词：基于多源遥感数据及DEM的人口统计数据空间化——以浙江省为例，由笔耕文化传播整理发布。

基于多源遥感数据及DEM的人口统计数据空间化——以浙江省为例

MODELING POPULATION DENSITY USING MULTI-SENSOR REMOTE SENSING DATA AND DEM. A CASE STUDY OF ZHEJIANG PROVINCE

[1] [2] [3] [4]

YANG Xu-chao1 , GAO Da-wei2 , DING Ming-jun3 , LIU Lin-shan4 （1. Zhejiang Institute of Meteorological Sciences, Hangzhou 310008, China; 2. Zheiiang Province Climate Center,

[1]浙江省气象科学研究所,浙江杭州310008; [2]浙江省气候中心,浙江杭州310017; [3]江西师范大学鄱阳湖湿地与流域研究教育部重点实验室,江西南昌330022; [4]中国科学院地理科学与资源研究所,北京100101

文章摘要：利用DMSP／OLS遥感夜间灯光数据进行人口等社会经济数据的空间化时，往往受到其较低的空间分辨率、像元过饱和以及像元溢出现象的影响。植被指数（如NDVI）与不透水面呈负相关关系，与夜间灯光数据在反映人类活动、提取建成区方面可以互补，将这两种数据融合可以有效减少夜灯数据像元过饱和等因素引起的误差。通过进一步融合DEM数据对基于DMSP／OLS夜间灯光数据和NDVI构建的人居指数进行了海拔修正，基于修正后的人居指数与统计人口之间很强的线性相关建立人口空间化模型，获得2010年浙江省1kmXlkm分辨率下的人口密度空间分布。模拟结果显示，，浙江省平均人口密度为515人／km。，模拟的平均相对误差为18．3％，相比海拔订正前的模拟误差减少约5％，表明利用多源遥感数据融合后的人居指数在省级尺度上模拟人口空间分布的精度较高。

Abstr：In order to bridge the gap between aggregated census data and geocoded data,different dasymetric mapping techniques were developed to disaggregate census data. The satellite-measured DMSP/OLS night- time light data was widely used for regional level mapping of socioeconomic activities due to its high tempo- ral resolution,free availability and wide swath. However,due to the coarse resolution, data saturation and overglow effects of DMSP/OLS data,any application need to take into account the limitations of using this data source. Firstly,although the DMSP/OLS sensor has a nominal resolution of 1 km, this has been resam- pled from the 2.7 km native resolution of the sensor. The coarse resolution of the nighttime lights data lower the accuracy of dasymetric mapping. Secondly,the overglow effect due to surface reflection and scat- tering and refraction in the atmosphere results in the overestimation of lighted areas. Thirdly,the low ra- diometric resolution of 6 bits （i. e. the digital number value ranges from 0 and 63） results in data saturation over brightly light built-up areas. Vegetation indexes like Normalized Difference Vegetation Index （NDVI） are negatively correlated with the impervious surfaces and can be used for estimation of built-up areas. The incorporation of vegetation index （NDVI） can reduce the errors occurring in estimating human settlements from the DMSP/OLS nighttime light imagery due to data saturation and other factors. In addition, elevation is an important variable in population distribution modeling because most human settlements occur on low- er elevation in China. This paper provides an approach for rapid and accurate estimation of population on a per pixel-basis using a integration of tw

文章关键词：

Keyword：:spatialization of statistical population DMSP/OLS NDVI human settlement index ZhejiangProvince

课题项目：中国气象局气候变化专项（ccsF一201336）;浙江省科技厅公益技术研究社会发展项目（2011C23051）;国家自然科学基金项目（41001023）

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  本文关键词：基于多源遥感数据及DEM的人口统计数据空间化——以浙江省为例，由笔耕文化传播整理发布。