Cross-Sensor Nighttime Lights Image Calibration for DMSP/OLS and SNPP/VIIRS with Residual U-Net

Dmitry Nechaev,Mikhail Zhizhin,Feng-Chi Hsu,Alexey Poyda,Tilottama Ghosh,Christopher Elvidge

doi:10.3390/rs13245026

Abstract

Remote sensing of nighttime lights (NTL) is widely used in socio-economic studies of economic growth, urbanization, stability of power grid, environmental light pollution, pandemics and military conflicts. Currently, NTL data are collected with two sensors: (1) Operational Line-scan System (OLS) onboard the satellites from the Defense Meteorology Satellite Program (DMSP) and (2) Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP (SNPP) and NOAA-20 satellites from the Joint Polar Satellite System (JPSS). However, the nighttime images acquired by these two sensors are incompatible in spatial resolution and dynamic range. To address this problem, we propose a method for the cross-sensor calibration with residual U-net convolutional neural network (CNN). The CNN produces DMSP-like NTL composites from the VIIRS annual NTL composites. The pixel radiances predicted from VIIRS are highly correlated with NTL observed with OLS (0.96 < R2 < 0.99). The method can be used to extend long-term series of annual NTL after the end of DMSP mission or to cross-calibrate same year NTL from different satellites to study diurnal variations.

Highlights

Defense Meteorology Satellite Program (DMSP) was launched in 1962 and since its satellites with Operational Line-scan System (OLS) serve as a source of valuable nighttime light (NTL) data of the Earth surface
Starting from 1992 the DMSP satellites broadcast digital images, which were post-processed by the NOAA Earth Observation Group (EOG) into global annual average and background removed NTL maps
This work provides a method based on Convolutional Neural Networks to generate analogs of DMSP data from Visible Infrared Imaging Radiometer Suite (VIIRS) data

Summary

Introduction

Defense Meteorology Satellite Program (DMSP) was launched in 1962 and since its satellites with Operational Line-scan System (OLS) serve as a source of valuable nighttime light (NTL) data of the Earth surface. Starting from 1992 the DMSP satellites broadcast digital images, which were post-processed by the NOAA (currently Colorado School of Mines) Earth Observation Group (EOG) into global annual average and background removed NTL maps. With annual data stretch from 1992 to 2013, it makes DMSP Nighttime. Lights the longest data series available for nocturnal remote sensing on human activities [1]. Annual VIIRS maps of nighttime lights are published from 2013 to 2019 [2]. NTL maps made with DMSP (DNL) or VIIRS (VNL) are widely utilized in research of human activity, economy and ecology [3]

Objectives

Methods

Results

Discussion

Conclusion