[1]黄耀裔,陈文成.基于DMSP/OLS修正的福建省人口数据网格化[J].泉州师范学院学报,2020,(06):86-93.
　HUANG Yaoyi,CHEN Wencheng.Data Griding of Population in Fujian Province Based on Modified DMSP/OLS[J].,2020,(06):86-93.
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基于DMSP/OLS修正的福建省人口数据网格化()
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《泉州师范学院学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年06期
页码:
86-93
栏目:
环境与资源
出版日期:
2020-12-15

文章信息/Info

Title:
Data Griding of Population in Fujian Province Based on Modified DMSP/OLS
文章编号:
1009-8224(2020)06-0086-08
作者:
黄耀裔; 陈文成
泉州师范学院 资源与环境科学学院,福建 泉州 362000
Author(s):
HUANG Yaoyi; CHEN Wencheng
School of Resource and Environmental Science, Quanzhou Normal University, Quanzhou Fujian362000,China
关键词:
DMSP/OLS;  NDVI;  改进HSI;  人口网格化;  福建省
Keywords:
DMSP/OLS;  NDVI;  model modification;  population gridding;  Fujian Province
分类号:
K910
文献标志码:
A
摘要:
基于福建省人口普查的县域常住人口、DMSP/OLS、NDVI等数据,据研究的植被指数能有效降低夜间灯光数据过饱和问题,结合植被指数改进优化HSI指数模型.在改进的HSI指数下,基于地理探测器分区后分别直接以常住人口的网格个数为权进行加权个案与加权最小二乘法进行人口网格化建模,再进行人口零误差调整得到1 km×1 km尺度的福建省人口统计数据网格化.结果表明:结合地理探测器的改进HSI指数模型能优化夜间灯光过饱和,有效回避可变面元效应等问题,提高模型拟合精度,对人口网格化效果更好,更符合实际的人口空间分布.
Abstract:
According to the data of resident population, DMSP/OLS, NDVI inFujian Province, the vegetation index studied can effectively reduce the oversaturation ofthe night light data, and improve the HSI index model with the vegetation index, under theimproved HSI index, based on the number of grids of the resident population, the weightedcases and the weighted least squares were modeled by the grid number of the residentpopulation, and then the population zero-error adjustment was carried out to get the grid ofthe population statistics data of Fujian Province at the scale of 1 km×1 km. The resultsshowed that the improved HSI index model combined with the geographical detector can optimizethe night light oversaturation, effectively avoid the variable panel effect, improve thefitting accuracy of the model, to obtain better effect of population gridding, and to be more in linewith the actual spatial distribution of population.

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备注/Memo

备注/Memo:
收稿日期:2020-06-03
作者简介:黄耀裔(1983-),男,福建泉州人,高级实验师,硕士,主要从事环境信息系统应用、开发评价研究.
基金项目:福建省自然科学项目(2016J01195); 泉州市科技项目(2018Z027)
更新日期/Last Update: 2020-12-15