测绘通报 ›› 2020, Vol. 0 ›› Issue (9): 89-93,118.doi: 10.13474/j.cnki.11-2246.2020.0290

• 学术研究 • 上一篇    下一篇

DMSP-OLS与NPP-VIIRS夜间灯光数据测算统计指标能力评估——以京津冀地区县域GDP、人口及能源消耗为例

李峰, 张晓博, 廖顺宝, 钱安   

  1. 防灾科技学院生态环境学院, 河北 三河 065201
  • 收稿日期:2020-03-20 出版日期:2020-09-25 发布日期:2020-09-28
  • 作者简介:李峰(1979-),男,博士,副教授,研究方向为遥感技术与应用。E-mail:lif1223@aliyun.com
  • 基金资助:
    河北省高校科技研究重点项目(ZD2020407);中央高校基本科研业务费(ZD2020407);河北省自然科学基金(D2018512002)

Capability assessment of DMSP-OLS and NPP-VIIRS nighttime light data estimating statistical indicators: a case of county-level GDP, population and energy consumption in Beijing-Tianjin-Hebei region

LI Feng, ZHANG Xiaobo, LIAO Shunbao, QIAN An   

  1. School of Ecology and Environment, Institute of Disaster Prevention, Sanhe 065201, China
  • Received:2020-03-20 Online:2020-09-25 Published:2020-09-28

摘要: 夜间灯光数据记录了地球表面的人造灯光强度,是估计社会统计指标的有效手段之一。为了评估DMSP-OLS和NPP-VIIRS 2种夜间灯光数据对社会统计指标的模拟潜力,采用4种常用的灯光校正方法分别对2种夜间灯光数据进行灯光饱和性校正,根据校正后的夜间灯光数据分别建立与京津冀地区县域GDP、人口和能源消耗3种社会统计指标间的线性回归模型,从模型拟合的相关系数、F统计量值与概率p值中分析并评价了2种夜间灯光数据对GDP、人口和能源消耗3种社会统计指标的测算能力。本文研究结果表明:EANTLI法是2种夜间灯光数据的最佳校正方式,而HSI法不适用于夜间灯光数据校正后与县域社会统计指标的线性关系拟合2种夜间灯光数据对GDP的拟合效果都较好,NPP-VIIRS夜间灯光数据估算社会统计指标的拟合能力要优于DMSP-OLS数据。

关键词: DMSP-OLS, NPP-VIIRS, 夜间灯光, 统计指标测算, GDP, 人口, 能源消耗

Abstract: Nighttime light data, which records the intensity of artificial light on the earth's surface, is one of the effective means to estimate social statistical indicators. To assess the simulation potential of DMSP-OLS, NPP-VIIRS nighttime light data for social statistical indicators, four common light correction methods are respectively used for saturation correction of two nighttime light data. Three linear regression models are respectively applied to construct between GDP, population, energy consumption data and the corrected nighttime light data from Beijing-Tianjin-Hebei. Then, the correlation coefficient of model fitting, statistical value of F and probability value of p are employed to analyze and evaluate the ability of two kinds of night light data in terms of measuring GDP, population and energy consumption. The results show that EANTLI method is the best correction method for two kinds of night light data, while HSI method is not suitable for fitting the linear relationship between nighttime light data and county-level social statistical index. The two kinds of night light data both have a good fitting effect on GDP. The fitting ability of social statistical indicators of NPP-VIIRS data is better than that of DMSP-OLS data.

Key words: DMSP-OLS, NPP-VIIRS, nighttime light, statistical index measurement, GDP, population, energy consumption

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