# Enhanced Color Nighttime Light Remote Sensing Imagery Using Dual-Sampling Adjustment

## TL;DR

This paper introduces a method to enhance nighttime light satellite images by combining them with daytime images, resulting in high-resolution color images that better capture urban features and economic activity.

## Contribution

A dual-sampling adjustment method is proposed to generate high-quality color nighttime light remote sensing imagery by fusing day and night data.

## Key findings

- Fusion images improved spatial resolution from 500 m to 15 m while retaining daytime features and nighttime light distribution.
- Enhanced imagery effectively balances optical fidelity and spatial texture features according to quality evaluations.
- Color nighttime light brightness in Beijing's central business district strongly correlates with business activity (r = 0.7221).

## Abstract

Nighttime light remote sensing imagery is limited by its single band and low spatial resolution, hindering its ability to accurately capture ground information. To address this, a dual-sampling adjustment method is proposed to enhance nighttime light remote sensing imagery by fusing daytime optical images with nighttime light remote sensing imagery, generating high-quality color nighttime light remote sensing imagery. The results are as follows: (1) Compared to traditional nighttime light remote sensing imagery, the spatial resolution of the fusion images is improved from 500 m to 15 m while better retaining the ground features of daytime optical images and the distribution of nighttime light. (2) Quality evaluations confirm that color nighttime light remote sensing imagery enhanced by dual-sampling adjustment can effectively balance optical fidelity and spatial texture features. (3) In Beijing’s central business district, color nighttime light brightness exhibits the strongest correlation with business, especially in Dongcheng District, with r = 0.7221, providing a visual tool for assessing urban economic vitality at night. This study overcomes the limitations of fusing day–night remote sensing imagery, expanding the application field of color nighttime light remote sensing imagery and providing critical decision support for refined urban management.