Articles | Volume 22, issue 10
Nat. Hazards Earth Syst. Sci., 22, 3435–3459, 2022
https://doi.org/10.5194/nhess-22-3435-2022
Nat. Hazards Earth Syst. Sci., 22, 3435–3459, 2022
https://doi.org/10.5194/nhess-22-3435-2022
Research article
20 Oct 2022
Research article | 20 Oct 2022

Development of black ice prediction model using GIS-based multi-sensor model validation

Seok Bum Hong et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-147', Anonymous Referee #1, 10 Aug 2022
    • AC1: 'Reply on RC1', Seok Bum Hong, 06 Sep 2022
    • AC3: 'Reply on RC1', Seok Bum Hong, 10 Sep 2022
  • RC2: 'Comment on nhess-2022-147', Anonymous Referee #2, 23 Aug 2022
    • AC2: 'Reply on RC2', Seok Bum Hong, 06 Sep 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by editor) (16 Sep 2022) by Yves Bühler
AR by Seok Bum Hong on behalf of the Authors (23 Sep 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (23 Sep 2022) by Yves Bühler
AR by Seok Bum Hong on behalf of the Authors (30 Sep 2022)  Author's response    Manuscript
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Short summary
This study advances previous models through machine learning and multi-sensor-verified results. Using spatial and meteorological data from the study area (Suncheon–Wanju Highway in Gurye-gun), the amount and location of black ice were modelled based on system dynamics to predict black ice and then simulated with the geographic information system (m2). Based on the model results, multiple sensors were buried at four selected points in the study area, and the model was compared with sensor data.
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