Normalization of VIIRS DNB images for improved estimation of socioeconomic indicators

作     者：Man Duc Chuc Tsubasa Hirakawa Hiromichi Fukuic 

作者机构：Graduate School of EngineeringChubu UniversityKasugaiJapan Chubu Institute for Advanced StudiesChubu UniversityKasugaiJapan Chubu Institute for Advanced Studies and International Digital Earth Applied Science Research Center(IDEAS)Chubu UniversityKasugaiJapan 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2021年第14卷第5期

页      面：540-554页

核心收录：

学科分类：08[工学] 0708[理学-地球物理学] 0835[工学-软件工程] 0704[理学-天文学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：VIIRS DNB seasonal factors stable lit normalization socioeconomic indicators 

摘      要：Monthly Visible Infrared Imaging Radiometer Suite(VIIRS)Day-Night Band(DNB)composite data are widely used in research,such as estimations of socioeconomic parameters.However,some surface conditions affect the VIIRS DNB radiance,which may create some estimation bias in certain regions.In this paper,we propose a novel normalization algorithm for VIIRS DNB monthly composite data.The aim is to normalize VIIRS radiance,collected under different surface conditions,to a reference point,so that the bias is reduced.The algorithm is based on the utilization of stable lit pixels as a reference and a nonlinear regression algorithm,to match un-normalized data to the reference data.Experimental results show that the algorithm could improve correlation(R2)between the total sum of nightlights(TOL),electric power consumption(EPC),and gross domestic product(GDP)at both a global and local scale.The algorithm could significantly diminish the seasonal component of un-normalized nightlights radiance caused by snow.The intensified nightlights radiance in sandy regions could also be reduced to a more reasonable range in comparison with other regions.Visual inspection shows that the brightness of snow-affected and sandy regions was strongly reduced after undergoing normalization.