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April 19, 2026Humanities and Social Sciences Communications0 citationsOpen Access

Integrating development equity and landscape patterns to enhance the alignment between nighttime lighting and sustainable development goals

CWChengyuan WangYLYuan LiuXSXiaofan Sun

Key Points

  • The aim is to integrate nighttime lighting data and landscape patterns to improve monitoring of sustainable development goals.
  • Analyzed nighttime lighting remote sensing data from 2000 to 2015 in China.
  • Developed the nighttime lighting landscape index to assess lighting equity and intensity.
  • Investigated the correlation between nighttime lighting trends and SDG progress.
  • 84.2% of nighttime lighting observations in China showed an increasing trend.
  • Urban fringe areas saw more light increase, while urban centers experienced a decline.
  • The nighttime lighting landscape index was effective in monitoring SDGs 1, 8, 9, and 11.

Abstract

Nighttime lighting (NTL) remote sensing provides globally consistent and long-term observations of surface nighttime light. It has been widely applied to assess regional economic and social development. However, it remains essential to consider NTL landscape patterns, light equality, and light intensity, to enhance the accuracy and consistency of NTL tools track the key SDGs process, and understand the interaction mechanism between NTL and SDG Score. This research tracks the progress of achieving the SDGs in China, uncovering potential applications of NTL in sustainability science. We found that 84.2% of NTLs in China exhibited an increasing trend, primarily in urban fringe areas, while urban centers showed a declining trend in 2000-2015. The Nighttime Lighting Landscape Index (NTLI), integrating landscape hierarchy, lighting equity, and light intensity, proved optimal for monitoring SDGs, effectively tracking the SDG 1, SDG 8, SDG 9, and SDG 11. By explicitly incorporating landscape patterns and development equity into NTL assessment, this study provides a methodological advance over prior NTL-based approaches and demonstrates how multidimensional lighting information can enhance the robustness and interpretability of sustainability monitoring. These findings build an equity-aware, landscape-informed assessment framework for tracking typical SDGs progress using the NTL data.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69e4713b010ef96374d8dc9chttps://doi.org/10.1057/s41599-026-07143-w
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