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Sensors (Basel). 2018 Oct 29;18(11). pii: E3665. doi: 10.3390/s18113665.

Mapping Urban Extent Using Luojia 1-01 Nighttime Light Imagery.

Li X1,2, Zhao L3, Li D4,5, Xu H6,7.

Author information

1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. lixi@whu.edu.cn.
2
Collaborative Innovation Centre of Geospatial Technology, Wuhan 430079, China. lixi@whu.edu.cn.
3
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. lixian_zhao@whu.edu.cn.
4
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. drli@whu.edu.cn.
5
Collaborative Innovation Centre of Geospatial Technology, Wuhan 430079, China. drli@whu.edu.cn.
6
School of Economics, Wuhan Donghu University, Wuhan 430212, China. xuhuimin1985_2008@163.com.
7
Key Laboratory of the Ministry of Land and Resources for Law Evaluation Engineering, Wuhan 430074, China. xuhuimin1985_2008@163.com.

Abstract

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.

KEYWORDS:

LJ1-01 data; VIIRS DNB; human settlement index; nighttime light imagery; urban areas

PMID:
30380616
DOI:
10.3390/s18113665
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