Precipitation nowcasting using transformer-based generative models and transfer learning for improved disaster preparedness-Reference-Cited by-同舟云学术

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Precipitation nowcasting using transformer-based generative models and transfer learning for improved disaster preparedness

Published:2024-08 Issue: Volume:132 Page:103962
ISSN:1569-8432
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Piran Md. Jalil^ORCID,Wang Xiaoding^ORCID,Kim Ho Jun,Kwon Hyun Han^ORCID

Funder

Ministry of Education - Singapore

Ministry of Environment

Korea Environmental Industry and Technology Institute

Publisher

Elsevier BV

Reference35 articles.

1. Machine learning for precipitation nowcasting from radar images;Agrawal,2019

2. A MODIS-based automated flood monitoring system for southeast Asia;Ahamed;Int. J. App. Earth Obs. Geol.,2017

3. Dynamic rainfall-induced landslide susceptibility: a step towards a unified forecasting system;Ahmed;Int. J. App. Earth Obs. Geol.,2023

4. Preformer: A memory-efficient transformer for point cloud semantic segmentation;Akwensi;Int. J. Appl. Earth Obs. Geol.,2024

5. Optical flow models as an open benchmark for radar-based precipitation nowcasting (rainymotion v0. 1);Ayzel;Geol. Mod. Dev.,2019

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