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Application of Satellite Data for Lightning Mapping

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 971

Special Issue Editors


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Guest Editor
Langmuir Laboratory and Physics Department, New Mexico Institute of Mining and Technology, 801 Leroy Place, Socorro, NM 87801, USA
Interests: lightning detection; lightning protection; instrumentation; lightning over the Amazon
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
National Space Institute, Technical University of Denmark (DTU Space), 2800 Kongens Lyngby, Denmark
Interests: atmospheric electricity; atmospheric physics; lightning physics and protection; atmospheric plasma; atmospheric remote sensing science and technology; computational electromagnetics; meteorology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The application of satellite data for lightning mapping has revolutionized the way we monitor and understand lightning activity on a global scale. By utilizing advanced sensors, such as the Geostationary Lightning Mapper (GLM) covering the Americas, the Lightning Mapping Imager (LMI) covering China and Australia, and the Lightning Imager (LI) covering Europe and Africa, it is now possible to detect and track lightning strikes in near real-time over vast regions, including remote and oceanic areas previously inaccessible to ground-based detection systems. Satellite lightning mapping provides critical insights into storm dynamics, severe weather forecasting, and climate studies by capturing both intra-cloud and cloud-to-ground lightning events. These data aid in improving early warning systems for extreme weather, enhancing aviation safety, and supporting disaster management efforts. Additionally, lightning observations from space contribute to research on atmospheric electrical activity and its impact on ecosystems and global climate patterns.

Dr. Adonis Ferreira Raiol Leal
Dr. Dongshuai Li
Guest Editors

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Keywords

  • lightning
  • lightning climatology
  • spaceborne sensors
  • forecasting
  • nowcasting
  • GLM
  • LMI
  • LI
  • lightning mapping

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Published Papers (1 paper)

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Research

18 pages, 5654 KB  
Article
Thermal Deformation Correction for the FY-4A LMI
by Yuansheng Zhang, Xiushu Qie, Dongjie Cao, Shanfeng Yuan, Dongfang Wang, Hongbo Zhang, Dongxia Liu, Zhuling Sun, Mingyuan Liu, Kexin Zhu, Rubin Jiang and Jing Yang
Remote Sens. 2026, 18(1), 163; https://doi.org/10.3390/rs18010163 - 4 Jan 2026
Viewed by 511
Abstract
Affected by solar radiation in space, the FY-4A Lightning Mapping Imager (LMI) detection array exhibits daily periodic thermal expansion and contraction, leading to deviations in lightning positioning accuracy. While LMI’s detection efficiency is higher at night, the dual edge matching algorithm, which relies [...] Read more.
Affected by solar radiation in space, the FY-4A Lightning Mapping Imager (LMI) detection array exhibits daily periodic thermal expansion and contraction, leading to deviations in lightning positioning accuracy. While LMI’s detection efficiency is higher at night, the dual edge matching algorithm, which relies on surface features for correction, does not perform well during nighttime (around 3 pixels). Analysis shows that most of the lightning data corrected by this method exhibit significant deviations from the actual lightning locations in practical applications. Therefore, this paper proposes a new correction method based on high precision ground-based lightning location data from the 2019 summer World Wide Lightning Location Network (WWLLN) and the Beijing Broadband Lightning Network (BLNET). Using these datasets as reference standards, the periodic deviation of LMI is determined, and a correction curve is derived using a weighted Gaussian fitting approach. This method further improves the nighttime lightning location accuracy of LMI on the basis of the current operational algorithm. The results demonstrate that the corrected LMI data significantly reduces the positioning errors, with an accuracy within ±1 pixel in the Beijing area, as an example. Full article
(This article belongs to the Special Issue Application of Satellite Data for Lightning Mapping)
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