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Big Earth Data

For a Special Issue on

Big Data and Artificial Intelligence for Natural Hazards

Manuscript deadline
31 October 2024

Cover image - Big Earth Data

Special Issue Editor(s)

Omid Ghorbanzadeh, BOKU University, Austria
[email protected]

Elia Machado, Lehman College, NY, USA
[email protected]

Pedram Ghamisi, Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Germany
[email protected]

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Big Data and Artificial Intelligence for Natural Hazards

Natural hazards, including landslides, floods, avalanches, wildfire and more, are pervasive and consequential occurrences that pose significant challenges worldwide. These hazards exert adverse impacts on both developed and developing nations, often leading to underestimated economic losses and casualties. Therefore, comprehensive monitoring strategies are imperative to predict and mitigate these hazards effectively. Timely and accurate identification of active natural hazards, as well as those nearing failure, is of paramount importance for facilitating effective monitoring, early warning systems, hazard assessment, susceptibility zonation, and post-event recovery operations.

Recent years have witnessed notable advancements in artificial intelligence (AI) methodologies, offering promising avenues for generating and updating inventories of various natural hazards. Additionally, AI methodologies, with their rapidly improving computational capacity, offer enormous potential for enhanced data analysis, including "big data" and have facilitated the monitoring of surface changes associated with hazards through the synergistic integration of rapidly evolving remote sensing technologies. A rich assortment of data sources, spanning the gamut from optical and multispectral imaging to synthetic aperture radar (SAR) and Light Detection and Ranging (LiDAR) data, collected via ground-based platforms, unmanned aerial vehicles (UAVs), aircraft, and satellites, have been harnessed to address the challenges of monitoring multiple natural hazards.

This esteemed Special Issue serves as an ideal platform to showcase pioneering research that underscores novel AI methodologies in tandem with underutilized remote sensing sensors for the monitoring of various natural hazards. We earnestly invite the submission of original research articles and comprehensive reviews that embrace diverse AI approaches and sensor specifications, all aimed at advancing applications, monitoring techniques, and geospatial analysis of different natural hazards. Furthermore, we strongly encourage studies that leverage data from different sensors to unravel the complexities surrounding the kinematics, controlling factors, and evolutionary patterns of these hazards. This Special Issue invites submissions that may include, but are not limited to, the following topics:

  1. Landslides, including submarine landslides, rockslides, slope failures, and post-fire debris flows.
  2. Floods, including riverine and flash floods.
  3. Wildfire /forest fire/ bushfire.
  4. Avalanches, including snow and debris avalanches.
  5. Risk mitigation measures and control strategies for various natural hazards.
  6. Innovative AI algorithms for the monitoring and detection of land deformations and water-related phenomena using cutting-edge remote sensing datasets.
  7. Application of state-of-the-art remote sensing sensors, such as hyperspectral imagers, multispectral sensors, very high-resolution optical satellites (e.g., WorldView, GeoEye), high-resolution SAR satellites (e.g., TerraSAR-X, COSMO-SkyMed), and advanced LiDAR systems (e.g., full waveform LiDAR, topographic LiDAR).
  8. Advancements in mapping and monitoring various natural hazards through the integration of data from emerging sensors and AI algorithms.
  9. Development and dissemination of “benchmark datasets” for different natural hazards encompassing various sensor modalities.
  10. Leveraging optical, radar, and laser imagery for enhanced analysis of multiple natural hazards.
  11. Exploitation of Unmanned Aerial Vehicles (UAVs), Unmanned Aircraft Systems (UAS), including emerging nano-satellites, hyperspectral UAV platforms, and high-resolution imaging drones, as well as Interferometric SAR (InSAR) and Ground-Based InSAR (GBInSAR) systems for comprehensive monitoring of various natural hazards.
  12. Early warning systems.

We cordially invite contributions to this prestigious Special Issue, wherein leading researchers can showcase their groundbreaking work at the intersection of natural hazard monitoring, remote sensing, and artificial intelligence. By consolidating our collective knowledge and expertise, we endeavor to propel the field forward, enabling effective management and mitigation of multiple natural hazard types.

Submission Instructions

Important Dates

  • October 31, 2024  Paper submission online
  • December 15, 2024  Decision notification to authors
  • February 15, 2025  Revised paper submission
  • March 31, 2025  Publication

Manuscript Submission Information

Please visit the Instructions for Authors page before submitting your manuscript. Once you have finished preparing your manuscript, please submit it through the Taylor & Francis Submission Portal, ensuring that you select the appropriate Special Issue. Publication charges (APCs) will be waived for invited manuscripts submitted to Big Earth Data. Authors who need a waiver code should contact the Editorial Office ([email protected]) before submitting.

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