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. 2018 Oct 29;18(11):3665.
doi: 10.3390/s18113665.

Mapping Urban Extent Using Luojia 1-01 Nighttime Light Imagery

Xi Li  1   2 , Lixian Zhao  3 , Deren Li  4   5 , Huimin Xu  6   7
Affiliations

Mapping Urban Extent Using Luojia 1-01 Nighttime Light Imagery

Xi Li et al. Sensors (Basel). .

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.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Study area under different data sources: (a) LJ1-01 NTL image in June 2018; (b) VIIRS DNB image in May 2018; (c) Landsat 8 OLI false color composite (R/G/B = 5/4/3) in April 2018; (d) Google Map remote sensing satellite image in 2018.
Figure 2
Figure 2
Extracted urban areas of Wuhan by HSI method using LJ1-01 NTL data: (a) threshold = 0.4; (b) threshold = 0.8; (c) threshold = 1.2.
Figure 3
Figure 3
Extracted urban areas of Wuhan by HSI method using VIIRS DNB data: (a) threshold = 0.6; (b) threshold = 0.9; (c) threshold = 1.2.
Figure 4
Figure 4
Extracted urban areas of Wuhan by STS method using LJ1-01 NTL data: (a) threshold = 2; (b) threshold = 10; (c) threshold = 18.
Figure 5
Figure 5
Extracted urban areas of Wuhan by STS method using VIIRS DNB data: (a) threshold = 2; (b) threshold = 10; (c) threshold = 18.
Figure 6
Figure 6
Extracted urban areas of Wuhan by SVM method using: (a) Landsat data only; (b) Landsat and LJ1-01 composite data; (c) Landsat and VIIRS composite data.
Figure 7
Figure 7
Accuracy assessment of urban extent extraction for: (a) HSI method using LJ1-01 data; (b) HSI method using VIIRS data; (c) STS method using LJ1-01 data; (d) STS method using VIIRS data; (e) SVM method.
Figure 7
Figure 7
Accuracy assessment of urban extent extraction for: (a) HSI method using LJ1-01 data; (b) HSI method using VIIRS data; (c) STS method using LJ1-01 data; (d) STS method using VIIRS data; (e) SVM method.
Figure 7
Figure 7
Accuracy assessment of urban extent extraction for: (a) HSI method using LJ1-01 data; (b) HSI method using VIIRS data; (c) STS method using LJ1-01 data; (d) STS method using VIIRS data; (e) SVM method.
Figure 8
Figure 8
Urban extent extraction results with the largest Kappa Coefficient for: (a) HSI method (LJ1-01 data used and threshold = 0.65); (b) STS method (LJ1-01 data used and threshold = 5); (c) SVM method using Landsat data only; (d) Google Map satellite image for comparison.
Figure 9
Figure 9
Urban extent extraction results with the largest Kappa Coefficient for: (a) HSI method using LJ1-01 data (threshold = 0.65); (b) HSI method using VIIRS data (threshold = 0.95); (c) STS method using LJ1-01 data (threshold = 5); (d) STS method using VIIRS data (threshold = 9).
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