Research on the Extraction Method of Urban Built-Up Areas With an Improved Night Light Index
Dingkun Chang, Qinjun Wang, Jingjing Xie, Jingyi Yang, Wentao Xu
Abstract
Nighttime light (NTL) data has been widely used in the research of urban built-up areas extraction. Due to the low resolution and the overflow characteristics of NTL data, it is difficult to extract urban built-up areas in small cities with undeveloped economy and small areas. How to extract them accurately becomes an important problem. Based on Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and Normalized Land Surface Temperature NLST), we proposed an improved night light index, named Vegetation, Building and Temperature Enhanced NTL Urban Index (VBTANUI) to accurately extract built-up areas in small cities by the marker-based watershed segmentation algorithm. Taking Jiayuguan, Ezhou and Wuzhishan, China as three examples, we extracted their urban built-up areas. Comparing with the four traditional NTL indexes, such as VANUI, EANI, BANUI65 and BANUI43, the results showed that: (1) the VBTANUI could effectively enhance the light intensity of the built-up boundaries; (2) F1 scores of VBTANUI in three cities are of 89.60%, 95.70% and 82.75% respectively, which are 6.04%, 7.12%, 8.10% and 8.47% higher in average than that of traditional four indexes; (3) VBTANUI is feasible and effective in the extraction of built-up areas in small cities with undeveloped economy and small areas.