Is Nighttime Light Primarily From Human Settlements? Exploring the Spatial Relationship Between NTL and Impervious Surface in Zhejiang Province, China

Over the past three decades, China's rapid urbanization has led to significant population concentration and economic growth, effectively captured by nighttime light (NTL) remote sensing. While NTL data is widely used to monitor urbanization, the relationship between NTL and impervious surfaces—key indicators of human settlements—remains underexplored. This study investigates the spatial relationship between NTL and impervious surface data, using Zhejiang Province as a case study due to its representative characteristics of rapid development and pronounced regional disparities. First, we conducted a quantitative analysis using the proportion of impervious surface index (Pb), revealing a high correlation (0.74) between NTL and impervious surfaces. Second, we examined the scale effect by analyzing their relationship at resolutions ranging from 500 meters to 10 kilometers, finding that the correlation peaked at an 8,000-meter scale (correlation coefficient of 0.875). Building on these results, we employed bivariate clustering to classify regions into four categories based on NTL and impervious surface characteristics: high NTL-high impervious, high NTL-low impervious, low NTL-high impervious, and low NTL-low impervious. This classification revealed spatial mismatches indicative of regional development imbalances, light pollution in ecological zones, and rural population loss. Our findings reveal a nuanced relationship between NTL and impervious surfaces, demonstrating that nighttime light is not solely determined by the presence of impervious surfaces but is influenced by a combination of human activities, land use patterns, and regional development characteristics. These findings provide new insights into the potential of NTL data for understanding urbanization processes and identifying uncoordinated development patterns, offering a foundation for sustainable urban planning and policy-making in Zhejiang Province and similar regions across China.