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• W4285309503 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." @default.
• W4285309503 created "2022-07-14" @default.
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• W4285309503 date "2022-01-01" @default.
• W4285309503 modified "2023-10-17" @default.
• W4285309503 title "Research on the Extraction Method of Urban Built-Up Areas With an Improved Night Light Index" @default.
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• W4285309503 doi "https://doi.org/10.1109/lgrs.2022.3179846" @default.
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