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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月17日

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  • Chengyuan Wang,
  • Yuan Liu,
  • Xiaofan Sun,
  • Yuheng Wu,
  • Enheng Wang,
  • Xuegang Mao,
  • Hongpeng Liu,
  • Qian Niu,
  • Tiantian Feng,
  • Liwei Yang,
  • Wangyang Lu,
  • Yao Yao

摘要

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.