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Open AccessArticle

Mapping Urban Extent Using Luojia 1-01 Nighttime Light Imagery

by Xi Li 1,2, Lixian Zhao 1,*, Deren Li 1,2 and Huimin Xu 3,4,*
1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2
Collaborative Innovation Centre of Geospatial Technology, Wuhan 430079, China
3
School of Economics, Wuhan Donghu University, Wuhan 430212, China
4
Key Laboratory of the Ministry of Land and Resources for Law Evaluation Engineering, Wuhan 430074, China
*
Authors to whom correspondence should be addressed.
Sensors 2018, 18(11), 3665; https://doi.org/10.3390/s18113665
Received: 29 September 2018 / Revised: 22 October 2018 / Accepted: 24 October 2018 / Published: 29 October 2018
(This article belongs to the Special Issue The Design, Data Processing and Applications of Luojia 1-01 Satellite)
Luojia 1-01 satellite, launched on 2 June 2018, provides a new data source of nighttime light at 130 m resolution and shows potential for mapping urban extent. In this paper, using Luojia 1-01 and VIIRS nighttime light imagery, we compared several methods for extracting urban areas, including Human Settlement Index (HSI), Simple Thresholding Segmentation (STS) and SVM supervised classification. According to the accuracy assessment, the HSI method using LJ1-01 data had the best performance in urban extent extraction, which presented the largest Kappa Coefficient value, 0.834, among all the results. For the urban areas extracted by VIIRS based HSI method, the largest Kappa Coefficient value was 0.772. In contrast, the largest Kappa Coefficient values obtained by STS method were 0.79 and 0.7512 respectively when using LJ1-01 and VIIRS data, while for SVM method the values were 0.7829 and 0.7486 when using Landsat-LJ and Landsat-VIIRS composite data respectively. The experimented results demonstrated that the utilization of nighttime light imagery can largely improve the accuracy of urban extent extraction and LJ1-01 data, with a higher resolution and more abundant spatial information, can lead to better identification results than its predecessors. View Full-Text
Keywords: nighttime light imagery; LJ1-01 data; urban areas; human settlement index; VIIRS DNB nighttime light imagery; LJ1-01 data; urban areas; human settlement index; VIIRS DNB
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Li, X.; Zhao, L.; Li, D.; Xu, H. Mapping Urban Extent Using Luojia 1-01 Nighttime Light Imagery. Sensors 2018, 18, 3665.

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