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<p>Nighttime light (NTL) data are widely used to represent spatial patterns of human activity, yet their interpretation at subnational scales remains uncertain. This study examines cross-sectional spatial associations between VIIRS nighttime radiance and land-cover compositional evenness across Java Island, Indonesia. Annual VIIRS NTL composites and Landsat-derived land-cover data were aggregated to a uniform 10&#xa0;km × 10&#xa0;km grid. Land-cover compositional evenness was measured using a normalized Shannon entropy index based on four generalized land-cover classes, while nighttime radiance was treated strictly as a proxy for artificial illumination. Global correlation analysis and exploratory local bivariate pattern classification were applied to describe spatial co-patterns. Results reveal a weak overall correlation and pronounced spatial heterogeneity, indicating that areas with similar radiance levels may exhibit contrasting land-cover compositions. For spatial information practice, the findings highlight the importance of scale harmonization, metric selection, and local pattern exploration when integrating NTL with land-cover data.</p>

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Exploratory spatial co-patterns of VIIRS nighttime radiance and land cover compositional evenness at 10-km resolution in Java, Indonesia

  • 期刊论文

  • 发表日期：

    2026年2月16日

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  • Dimas Danar Dewa,
  • Imam Buchori,
  • Anang Wahyu Sejati,
  • Yan Liu

摘要

Nighttime light (NTL) data are widely used to represent spatial patterns of human activity, yet their interpretation at subnational scales remains uncertain. This study examines cross-sectional spatial associations between VIIRS nighttime radiance and land-cover compositional evenness across Java Island, Indonesia. Annual VIIRS NTL composites and Landsat-derived land-cover data were aggregated to a uniform 10 km × 10 km grid. Land-cover compositional evenness was measured using a normalized Shannon entropy index based on four generalized land-cover classes, while nighttime radiance was treated strictly as a proxy for artificial illumination. Global correlation analysis and exploratory local bivariate pattern classification were applied to describe spatial co-patterns. Results reveal a weak overall correlation and pronounced spatial heterogeneity, indicating that areas with similar radiance levels may exhibit contrasting land-cover compositions. For spatial information practice, the findings highlight the importance of scale harmonization, metric selection, and local pattern exploration when integrating NTL with land-cover data.