Research on Spatial Delineation Method of Urban-Rural Fringe Combining POI and Nighttime Light Data—Taking Wuhan City as an Example

**Background:** The urban-rural fringe (URF) is a transitional zone between urban core areas and rural hinterlands, characterized by sharp conflicts in land use, governance, and social equity. Accurate delineation of the URF is critical for fine-scale urban and rural planning, but traditional methods relying on administrative boundaries, population density, or land use data suffer from low accuracy, poor temporal resolution, or limited socioeconomic interpretability. Nighttime Light (NTL) imagery can reflect human activity intensity but suffers from 'saturation' and 'overflow' effects at high resolutions. Point of Interest (POI) data capture micro-level human activity but cannot reflect development scale or intensity. This study proposes a fused NPP and POI composite index to overcome these limitations, using Wuhan City as a case study.

**Methods:** The study area is Wuhan, Hubei Province, China (area 8,569.55 km², population 11.21 million, urbanization rate 80.49% as of 2019). NTL data were obtained from the NPP-VIIRS DNB band (November 2020, 500 m resolution). POI data (345,861 valid points) were crawled from Baidu Maps (April 2021) and classified into five categories: cultural and sports, commercial, industrial, public service, and residential. The NPP and POI composite index was calculated using the geometric mean of normalized NTL brightness and POI kernel density values. A kernel density bandwidth of 500 m was selected after comparative testing at 50 m, 500 m, and 3,500 m. Breaking point analysis was applied along 180 radial transects (2° intervals) from the population center of gravity to identify the inner boundary (first mutation in composite index values). The outer boundary was identified via inflection points in the cumulative area of composite index isolines. Validation used land use structure information entropy (from the Third National Land Survey, reclassified into 8 categories) and NDVI (from MODIS MOD13Q1, 250 m resolution, 2010–2020) across a 3 km × 3 km verification grid and four transects, plus field surveys.

**Key Results:** The inner boundary threshold was determined at a composite index value of approximately 0.1. The urban core area (composite index 0.2–0.6) includes seven central districts plus seven identified new city clusters (Songjiagang, Yangluo, Caidian, Zhifang, Shamao, Qianchuan, Zhucheng). The URF covers 1,482.35 km² (17.30% of Wuhan's total area). Land use within the URF comprises 40.75% construction land, 30.03% water, and 14.60% cultivated land. Population density decreases from urban core (9,335.83 persons/km²) to URF (2,556.28 persons/km²) to rural (827.84 persons/km²). Land use structure information entropy is highest in the URF (1.630), compared to urban core (0.937) and rural (1.418). NDVI increases from urban core (0.431, SD 0.101) to URF (0.523, SD 0.184) to rural (0.718, SD 0.158). NDVI in the URF showed a decreasing trend from 2010 to 2020, while urban core and rural NDVI increased. Transect validation confirmed that areas with information entropy >1.2 and NDVI between 0.5–0.7 corresponded to the delineated URF. Field surveys in 9 locations confirmed the transitional landscape characteristics. The URF exhibits a 'six axes, two rings' banded and leaping distribution pattern around the main urban core.

**Clinical Implications:** This study does not address clinical or medical topics. It is a methodological paper in urban geography and spatial planning. The findings have implications for urban infrastructure allocation, industrial division, ecological function zoning, and fine governance of transitional urban-rural areas. The composite index approach offers improved accuracy over traditional methods and can support land spatial planning and sustainable urban development.