LHRSI: A Lightweight Spaceborne Imaging Spectrometer with Wide Swath and High Resolution for Ocean Color Remote Sensing

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Authors: B. Cheng, Yongqian Zhu, Miao Hu, Xianqiang He, Qianmin Liu, Chunlai Li, Chen Cao, B. C. Zhao, Jindong Wu, Jianyu Wang, Jie Luo, Jiawei Lu
+6 more Zhihua F. Song, Yu Song, W H Jiang, Zi Wang, Guoliang Tang, Shijie Liu
Cited by: 2
References: 24

Abstract

Global water environment monitoring urgently requires remote sensing data with high temporal resolution and wide spatial coverage. However, current space-borne ocean color spectrometers still face a significant trade-off among spatial resolution, swath width, and system compactness, which limits the large-scale deployment of satellite constellations. To address this challenge, this study developed a lightweight high-resolution spectral imager (LHRSI) with a total mass of less than 25 kg and power consumption below 80 W. The visible (VIS) camera adopts an interleaved dual-field-of-view and detectors splicing fusion design, while the shortwave infrared (SWIR) camera employs a transmission-type focal plane with staggered detector arrays. Through the field-of-view (FOV) optical design, the instrument achieves swath widths of 207.33 km for the VIS bands and 187.8 km for the SWIR bands at an orbital altitude of 500 km, while maintaining spatial resolutions of 12 m and 24 m, respectively. On-orbit imaging results demonstrate that the spectrometer achieves excellent performance in both spatial resolution and swath width. In addition, preliminary analysis using index-based indicators illustrates LHRSI’s potential for observing chlorophyll-related features in water bodies. This research not only provides a high-performance, miniaturized spectrometer solution but also lays an engineering foundation for developing low-cost, high-revisit global ocean and water environment monitoring constellations.

Fields of Study & Subjects

Optical Polarization and Ellipsometry Marine and coastal ecosystems Advanced optical system design

Publication details

Journal / source
Remote Sensing
Publisher
MDPI AG
Volume
18
Issue
2
Pages
218–218
Publication date
9 January 2026
Language
EN