Junwei Wang , Shuguo Chen , Shixian Hu , Linke Deng , Chaofei Ma , Hailong Peng , Qingjun Song
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引用次数: 0
Abstract
Ultraviolet (UV) remote sensing plays a critical role in understanding photochemical and biological processes in the global ocean. While UV radiation significantly influences the marine environment, the limited availability of global UV measurements has hindered comprehensive analyses, particularly in photochemically sensitive regions. The Ultraviolet Imager (UVI) on China’s HaiYang-1C (HY-1C) satellite, launched in 2018, offers unique data with two UV bands (355 and 385 nm), enabling the study of UV-driven oceanic processes that were previously unachievable with standard visible-only ocean color sensors. This study develops a system vicarious calibration (SVC) approach tailored for HY-1C’s UVI, integrating co-located observations from the Coastal Zone Color Scanner (COCTS) on the same satellite platform to derive accurate remote sensing reflectance (Rrs) in the UV spectrum. Using MOBY in situ measurements as reference data for SVC and ship-based measurements for validation, we demonstrate that UVI-derived Rrs achieve high accuracy, with Mean Absolute Percentage Differences (MAPD) reduced to 15.7 % and 8.4 % for the 355 and 385 nm bands, respectively, following system vicarious calibration. This enhanced accuracy provides a pathway for producing consistent UV ocean color products and contributes to a deeper understanding of marine biogeochemical cycles. The findings highlight the potential of HY-1C UVI in expanding ocean color research into the UV domain, offering valuable insights for future satellite missions.
期刊介绍:
The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.