摘要
随着遥感技术的不断发展,来自国防气象卫星可见红外成像线性扫描业务系统(DMSP-OLS)和Suomi国家极轨卫星可见近红外成像辐射仪(NPP-VIIRS)的夜光灯光数据在人文经济研究中展示着越来越大的潜力。研究采用像元数值模拟法,基于DMSP/OLS 2013年灯光数据模拟重构DMSP/OLS 1992-2012各年数据,采用相互校正法,通过建立DMSP/OLS 2013年0~63级灯光数据与2013年NPP/VIIRS灯光数据相应空间位置平均值间的数值转换关系,实现2014-2018各年NPP/VIIRS平均灯光数据向DMSP/OLS数据的转换,最终获得1992-2018年两个传感器间连续的灯光校正影像。研究结果表明,针对DMSP/OLS各年灯光数据间的校正,像元数据模拟法比传统不变目标区域法校正效果好。结果经验证,DMSP/OLS各年灯光原始值和校正值间的线性拟合优度平均值达0.989。对所得1992-2018年连续的灯光校正结果结合国家、省、市、县级尺度社会经济数据验证结果表明,灯光灰度总量与各级GDP数据存在极显著的正相关关系,证明校正后的灯光数据有较高的准确性和连续性。研究构建的DMSP/OLS与NPP/VIIRS灯光数据相互校正方法为长时间序列社会经济要素发展趋势的研究奠定了坚实基础。
With the continuous development of remote sensing technology,luminous lighting data from Defense Meteorological Satellite Program Visible Infrared Imaging Operational Linear Scanning Operational System(DMSP-OLS),and Suomi National Polar-orbiting Partnership Satellite Visible Infrared Imaging Radiometer Suite(NPP-VIIRS),are showing increasing potential in human economic research.The study adopts the pixel numerical simulation method to reconstruct the DMSP/OLS data for the years 1992 to 2012 based on the DMSP/OLS 2013 lighting data.The conversion of the NPP/VIIRS average lighting data from 2014 to 2018 to the DMSP/OLS data is achieved by establishing a numerical conversion relationship between the DMSP/OLS 2013 lighting data from Level 0 to Level 63,and the corresponding spatial location averages of the 2013 NPP/VIIRS lighting data using the mutual correction method.The results have shows that for the correction between the DMSP/OLS lighting data for each year,pixel numerical simulation method is more effective than the traditional constant target area method.The results have validated that the average value of the linear fit between the original and corrected light values for each year of DMSP/OLS is 0.9890.The verification results of the obtained continuous lighting correction results from 1992 to 2018,combined with national,provincial,municipal and county scale socioeconomic data,have shown that there is a highly significant positive correlation between the total amount of lighting grayscale and GDP data at all levels,where have proven that the corrected lighting data have high accuracy and continuity.The mutual correction methods of DMSP/OLS and NPP/VIIRS lighting data constructed in the study have laid a solid foundation for the research on the development trend of long time series socio-economic factors.
出处
《科技创新与应用》
2021年第27期1-9,16,共10页
Technology Innovation and Application
基金
欧盟Erasmus+项目(编号:598838-EPP-1-2018-EL-EPPKA2-CBHE-JP)资助。
关键词
遥感
灯光
数值模拟
相互校正
remote sensing
lighting
numerical simulation
mutual correction