Cross-Comparison of channel parameters between FY-3E/MERSI-LL and Himawari-8/AHI in China

Xie, Lianni; Wu, Shuang; Chen, Jie; Zheng, Wei; Yan, Hua; Xu, Zuomin

doi:10.1080/01431161.2022.2116297

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…FY-3E senses the globe in the early mornings and afternoons (Equator Crossing Time (ECT) 05:30 am L.T. ), with the potential of largely reducing the gaps currently left by sun-synchronous platforms [95]. In fact, the particular acquisition time of this satellite makes it particularly interesting as it can cover a time window otherwise discovered by the other sensors.…”

Section: Discussionmentioning

confidence: 99%

The Capabilities of FY-3D/MERSI-II Sensor to Detect and Quantify Thermal Volcanic Activity: The 2020–2023 Mount Etna Case Study

et al. 2023

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Satellite data provide crucial information to better understand volcanic processes and mitigate associated risks. In recent years, exploiting the growing number of spaceborne polar platforms, several automated volcanic monitoring systems have been developed. These, however, rely on good geometrical and meteorological conditions, as well as on the occurrence of thermally detectable activity at the time of acquisition. A multiplatform approach can thus increase the number of volcanological-suitable scenes, minimise the temporal gap between acquisitions, and provide crucial information on the onset, evolution, and conclusion of both transient and long-lasting volcanic episodes. In this work, we assessed the capabilities of the MEdium Resolution Spectral Imager-II (MERSI-II) sensor aboard the Fengyun-3D (FY-3D) platform to detect and quantify heat flux sourced from volcanic activity. Using the Middle Infrared Observation of Volcanic Activity (MIROVA) algorithm, we processed 3117 MERSI-II scenes of Mount Etna acquired between January 2020 and February 2023. We then compared the Volcanic Radiative Power (VRP, in Watt) timeseries against those obtained by MODIS and VIIRS sensors. The remarkable agreement between the timeseries, both in trends and magnitudes, was corroborated by correlation coefficients (ρ) between 0.93 and 0.95 and coefficients of determination (R2) ranging from 0.79 to 0.84. Integrating the datasets of the three sensors, we examined the effusive eruption of Mount Etna started on 27 November 2022, and estimated a total volume of erupted lava of 8.15 ± 2.44 × 106 m3 with a Mean Output Rate (MOR) of 1.35 ± 0.40 m3 s−1. The reduced temporal gaps between acquisitions revealed that rapid variations in cloud coverage as well as geometrically unfavourable conditions play a major role in thermal volcano monitoring. Evaluating the capabilities of MERSI-II, we also highlight how a multiplatform approach is essential to enhance the efficiency of satellite-based systems for volcanic surveillance.

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Section: Discussionmentioning

confidence: 99%

The Capabilities of FY-3D/MERSI-II Sensor to Detect and Quantify Thermal Volcanic Activity: The 2020–2023 Mount Etna Case Study

et al. 2023

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“…MERSI‐LL has seven observation channels, including 1 low‐light channel and 6 Thermal Infrared (TIR) channels, covering the range of 0.7–12 μm. The spatial resolution of two infrared split window channels is 250 m, and the remaining channels are 1,000 m (Xie et al., 2022). In our study, a total of 8,891 L1 level images from six TIR channels were used from May 1 to 31 May 2023.…”

Section: Methodsmentioning

confidence: 99%

First PWV Retrieval Using MERSI‐LL Onboard FY‐3E and Cross Validation With Co‐Platform Occultation and Ground GNSS

Jiang,

Wu,

et al. 2024

Geophysical Research Letters

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FY‐3E plays a vital role in the meteorological global earth observing system. Precipitable water vapor (PWV) is an essential parameter for the water cycle and global climate change. Here, we carry out the PWV retrieval using the MERSI‐LL sensor onboard the FY‐3E satellite for the first time. The retrieval accuracy under different cloudage conditions is validated by the extra PWV from ground‐based GNSS and spaceborne occultation. For the results against ground‐based GNSS, the total accuracy shows an RMSE of 2.69–3.36 mm as the clouds increase, and correlation coefficients higher than 0.95. The spatial accuracy distribution indicates that inland stations have higher accuracy than the coast and island stations. As for the results against spaceborne occultation, the verification accuracy varies with the spatial pairing distance, showing poor accuracy in the low latitude area. This study can provide an essential reference for the community to understand the current water vapor inversion performance of MERSI‐LL.

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“…And the superiority of FY-3E over H8 and GK-2A PMSs is also compared by engineering application. (Dong et al, 2022;Xie et al, 2022;Zhang et al, 2022). Two of the infrared split-window bands have a spatial resolution of 250 m, and the remaining bands are of 1000 m resolution.…”

Section: Introductionmentioning

confidence: 99%

Wildfire monitoring technologies of transmission line corridors based on Fengyun-3E satellite imaging

Li,

Chen,

et al. 2023

Front. Energy Res.

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Facing towards the Carbon Neutrality goal by 2060, renewable energy sources are boosted in China in the past decade. Either these renewables or power systems are sensitive and vulnerable to natural disasters, such as wildfire and typhoon. In this paper, a fire spot identification algorithm is proposed for wildfire disaster occurred in transmission line corridors based on Fengyun-3E (FY-3E). It mitigates the effect of large observation of solar zenith angle, as well as changes of satellite views, on the infrared channel detection. And cloud information under complex atmospheric conditions is analyzed to extract the cloud pixel fire spot, which decreases false ratio of fire-spot alerts. According to the analysis of hybrid pixel linear spectrums, the fire-spot detection sensitivity of FY-3E is four times as that of geostationary meteorological satellites. The effectiveness of the proposed algorithm was confirmed by an application in the Shanxi province power grid of State Grid in China. It shows that and the FY-3E has a superiority in wildfire monitoring for power system in terms of fire detection sensitivity, spatial range accuracy, and positioning accuracy. Compared to geostationary meteorological satellites, the fire locating accuracy of FY-3E is increased by more than one-fold. This research can assist the operation and maintenance departments of transmission lines to rapidly detect wildfire, thereby reducing the damage of wildfires on the power grid.

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Cross-Comparison of channel parameters between FY-3E/MERSI-LL and Himawari-8/AHI in China

Cited by 5 publications

References 15 publications

The Capabilities of FY-3D/MERSI-II Sensor to Detect and Quantify Thermal Volcanic Activity: The 2020–2023 Mount Etna Case Study

The Capabilities of FY-3D/MERSI-II Sensor to Detect and Quantify Thermal Volcanic Activity: The 2020–2023 Mount Etna Case Study

First PWV Retrieval Using MERSI‐LL Onboard FY‐3E and Cross Validation With Co‐Platform Occultation and Ground GNSS

Wildfire monitoring technologies of transmission line corridors based on Fengyun-3E satellite imaging

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