Assessing the Ability of Luojia 1-01 Imagery to Detect Feeble Nighttime Lights.
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ID: 27654
2019
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Abstract
The Luojia1-01 (LJ1-01) satellite launched on June 2, 2018 provides a new option for nighttime light (NTL) application research. In this paper, four types of human settlements, such as cities, counties, towns and villages, are sampled to evaluate the potential of LJ1-01 to detect feeble NTL by comparing with the NTL images from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-Orbiting Partnership Satellite. First, the landscape indices and cutoff threshold method are applied to enhance signal-noise ratio (SNR). Then, the detection accuracy of samples is evaluated to determine the optimal cutoff threshold for each NTL data source. After that, the spatial correspondence of different NTL images and the area consistency between the samples and NTL footprints are compared. Finally, after the discussion of feeble NTL detection and the influence of clouds, moonlight and image composites, it can be concluded that LJ1-01 is more suitable for detection feeble NTL objects, while great importance should be attached to the measures to eliminate the noise in LJ1-01 image and make LJ1-01 more widely used: (1) In the study area, a suitable cutoff threshold of LJ1-01 image can be set to 0.1 nano-Wcmsr, which is lower than that of VIIRS image (0.3 nano-Wcmsr), and this enables LJ1-01 to reserve more information of NTL, especially the feeble NTL. Moreover, the minimum area that can be identified by NTL footprints from LJ1-01 is 0.02 km, while that of VIIRS and DMSP are 0.3 km and 4.5 km, respectively. (2) The cutoff threshold method can identify the range of NTL with more noise, but cannot eliminate the noise separately. The filtering method and the image composition method may play more important role in the applications of LJ1-01 data.
| Reference Key |
li2019assessingsensors
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| Authors | Li, Xue;Liu, Zhumei;Chen, Xiaolin;Sun, Jie; |
| Journal | sensors |
| Year | 2019 |
| DOI |
E3708
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| URL | |
| Keywords | Keywords not found |
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