Vessel Detection with SDGSAT-1 Nighttime Light Images

Abstract

The Sustainable Development Goals Science Satellite-1 (SDGSAT-1) Glimmer Imager for Urbanization (GIU) data is very sensitive to low radiation and capable of detecting weak light sources from vessels at night while significantly improving the spatial resolution compared to similar products. Most existing methods fail to use the relevant characteristics of vessels effectively, and it is difficult to deal with the complex shape of vessels in high-resolution Nighttime Light (NTL) data, resulting in unsatisfactory detection results. Considering the overall sparse distribution of vessels and the light source diffusion phenomenon, a novel vessel detection method is proposed in this paper, utilizing the high spatial resolution of the SDGSAT-1. More specifically, noise separation is completed based on a local contrast-weighted RPCA. Then, artificial light sources are detected based on a density clustering algorithm, and an inter-cluster merging method is utilized to realize vessel detection further. We selected three research areas, namely, the Bohai Sea, the East China Sea, and the Gulf of Mexico, to establish a vessel dataset and applied the algorithm to the dataset. The results show that the total detection accuracy and the recall rate of the detection algorithm in our dataset are 96.84% and 96.67%, which is significantly better performance than other methods used for comparison in the experiment. The algorithm overcomes the dataset’s complex target shapes and noise conditions and achieves good results, which proves the applicability of the algorithm.

Night-Time Vessel Detection Based on Enhanced Dense Nested Attention Network

“…Due to the limitations of the current method and data, it is hard to determine the number of vessels within a single pixel in DNB images and the specific size of detected vessels. Look up 1 and the recently launched SDGSAT satellite both carry a detector for the glimmer imager bands, with its spatial resolution raised to 38 m at the nadir and 10 m in the panchromatic band, providing the possibility for more accurate identification of lighted vessels [50,51]. By improving the corresponding vessel-detection algorithms, theoretically, multiple vessels that were previously contained within a single pixel on the original DNB image can now possibly be identified in the existing SDGSAT data.…”

Assessment of Earthquake Damage and Economic Recovery in Hatay Province, Turkey Using Nighttime Light Data

“…Among them, the glimmer imager adopts a 10-meter panchromatic band design, which is divided into low-gain, high-gain, and high-low-gain fusions [42]. Furthermore, it is designed with red, green, and blue bands (RGB) with a 40-m resolution [43,44]. Although the glimmer imager for urbanization (GIU) image has a high spatial resolution, it still contains a considerable amount of linear and isolated noise, as depicted in Figure 3.…”