Ma et al. (2026) Tropical Cyclone Detection and Tracking Using Spatial–Temporal Characteristics of Regional Wind Speed From CYGNSS: Proof of Concept and Assessment

Identification

• Journal: IEEE Transactions on Geoscience and Remote Sensing
• Year: 2026
• Date: 2026-01-01
• Authors: Xiangchao Ma, Dongkai Yang, Feng Wang, Weichen Sun, Chuanrui Tan, Jie Li, Mengjie Wang
• DOI: 10.1109/tgrs.2026.3664983

Research Groups

[Information not available in the provided text.]

Short Summary

[Information not available in the provided text.]

Objective

• To develop and assess a method for tropical cyclone detection and tracking using spatial-temporal characteristics of regional wind speed data from CYGNSS.

Study Configuration

• Spatial Scale: [Information not available in the provided text.]
• Temporal Scale: [Information not available in the provided text.]

Methodology and Data

• Models used: [Information not available in the provided text.]
• Data sources: CYGNSS (Cyclone Global Navigation Satellite System) wind speed data.

Main Results

• [Information not available in the provided text.]

Contributions

• [Information not available in the provided text.]

Funding

• [Information not available in the provided text.]

Citation

@article{Ma2026Tropical,
  author = {Ma, Xiangchao and Yang, Dongkai and Wang, Feng and Sun, Weichen and Tan, Chuanrui and Li, Jie and Wang, Mengjie},
  title = {Tropical Cyclone Detection and Tracking Using Spatial–Temporal Characteristics of Regional Wind Speed From CYGNSS: Proof of Concept and Assessment},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  year = {2026},
  doi = {10.1109/tgrs.2026.3664983},
  url = {https://doi.org/10.1109/tgrs.2026.3664983}
}