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Open AccessArticle

A POI and LST Adjusted NTL Urban Index for Urban Built-Up Area Extraction

1
School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
2
Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(10), 2918; https://doi.org/10.3390/s20102918
Received: 15 April 2020 / Revised: 14 May 2020 / Accepted: 19 May 2020 / Published: 21 May 2020
(This article belongs to the Section Remote Sensors)
Nighttime light (NTL) images have been broadly applied to extract urban built-up areas in recent years. However, the typical NTL images provided by Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) and National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) have the drawbacks of low resolution and blooming effect, which bring difficulty for the application of them in urban built-up area extraction. Therefore, this paper proposes the POI (point of interest) and LST (land surface temperature) adjusted NTL urban index (PLANUI) to extract the urban built-up areas with high accuracy. PLANUI is the first urban index to integrate POI and NTL for urban built-up area extraction. In this paper, NPP/VIIRS and Luojia 1-01 images were introduced as the original NTL data and the vegetation adjusted NTL urban index (VANUI) was selected as the comparison item. The threshold method was utilized to extract urban built-up areas from these data. The results show that: (1) Based on the comparison with the reference data, the PLANUI can make up the shortcoming of low resolution and the blooming effect of NTL effectively. (2) Compared with the VANUI, the PLANUI can significantly improve the accuracy of the urban built-up areas extracted and characterize urban features. (3) According to the results based on NPP/VIIRS and Luojia 1-01 images, the PLANUI has extensive applicability, both for regions with different degrees of economic development and NTL data with different resolutions. PLANUI can enhance the features of urban built-up areas with social sensing data and natural remote sensing data, which helps to weaken the NTL blooming effect and improve the extraction accuracy. PLANUI can provide an effective approach for urban built-up area extraction, which plays a certain guiding role for the study of urban structure, urban expansion, and urban planning and governance. View Full-Text
Keywords: urban built-up area; nighttime light remote sensing; NPP/VIIRS; Luojia 1-01; POI; LST urban built-up area; nighttime light remote sensing; NPP/VIIRS; Luojia 1-01; POI; LST
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MDPI and ACS Style

Li, F.; Yan, Q.; Bian, Z.; Liu, B.; Wu, Z. A POI and LST Adjusted NTL Urban Index for Urban Built-Up Area Extraction. Sensors 2020, 20, 2918.

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