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Remote Sensing
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Application of Satellite Data for Lightning Mapping
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Application of Satellite Data for Lightning Mapping

A Special Issue of Remote Sensing (ISSN 2072-4292) belonging to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: 15 March 2027 | Viewed by 2130

Editors

Dr. Adonis Ferreira Raiol Leal

E-Mail Website
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
Dr. Dongshuai Li

E-Mail Website
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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

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

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Published Papers (2 papers)

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Research

20 pages, 1007 KB  
Article
Calibration of Event-Based Camera for High-Speed Observations of Lightning and Transient Luminous Events
by Nicolas Pedersen, Tao Liu, Olivier Chanrion, Justo Sánchez, Francisco J. Gordillo-Vázquez, Torsten Neubert, Farhad Rachidi, Alejandro Luque and Dongshuai Li
Remote Sens. 2026, 18(18), 3201; https://doi.org/10.3390/rs18183201 - 17 Sep 2026
Viewed by 358
Abstract
Event-based vision sensors (EVSs) offer an innovative approach to optical sensing by responding solely to changes in photon flux with asynchronous pixels. This enables high-speed imaging with minimal data throughput and a large dynamical range > 120 dB. Despite their growing use in [...] Read more.
Event-based vision sensors (EVSs) offer an innovative approach to optical sensing by responding solely to changes in photon flux with asynchronous pixels. This enables high-speed imaging with minimal data throughput and a large dynamical range > 120 dB. Despite their growing use in edge detection and the observation of Earth science phenomena such as lightning and transient luminous events (TLEs), optimizing EVS performance specifically for high-speed observations on microsecond timescales, where the photon flux is key, remains challenging. This is due to the unitless, non-intuitive nature of their bias settings, which drives the working principles of the sensor. In this study, we perform a comprehensive calibration of an event-based camera, focusing on three critical parameters: contrast thresholds, refractory period, and corner frequency of the inherent low-pass filter. Using a pre-calibrated LED source and newly developed event generation code, we establish physical relationships between these raw digital bias settings and the camera’s response characteristics. Our results show tunable ranges of 5–190% for on contrast thresholds, 5–65% for off contrast thresholds, 12–480 μs for refractory periods, and 1–11 kHz for corner frequencies. These calibrations provide the fundamental camera characteristics for accurate optical signal reconstruction and improved detection of fast transient phenomena. The approach is demonstrated on a Prophesee EVK4; however, the proposed calibration method can be applied to any EVS camera that employs similar hardware components and bias settings and thus provides a necessary framework for the quantitative use of EVS cameras in atmospheric remote sensing. Full article
(This article belongs to the Special Issue Application of Satellite Data for Lightning Mapping)
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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
Cited by 1 | Viewed by 1027
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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