A Typhoon Center Positioning Method Using FY Satellite Data

Junqi Wan; Xiang Xiong; Fei Sun

doi:10.47297/taposatWSP2633-456904.20230401

PDF
Export
Share
Collection
Album

A Typhoon Center Positioning Method Using FY Satellite Data

Volume 4, Issue 1

Views: 0 Downloads: 2

A Typhoon Center Positioning Method Using FY Satellite Data
Academy of Computer, Huanggang Normal University, No.146 Xinggang 2nd Road,Huanggang,China,438000
Vol. 4, Issue 1, Pages: 27-32(2023)
DOI：10.47297/taposatWSP2633-456904.20230401

Full txt

Junqi Wan, Xiang Xiong & Fei Sun. (2023). A Typhoon Center Positioning Method Using FY Satellite Data. Theory and Practice of Science and Technology, 4(1), 27-32.
DOI：

Junqi Wan, Xiang Xiong & Fei Sun. (2023). A Typhoon Center Positioning Method Using FY Satellite Data. Theory and Practice of Science and Technology, 4(1), 27-32. DOI： 10.47297/taposatWSP2633-456904.20230401.

摘要

Abstract

Aiming to detect the eye of eyed typhoons

this paper proposes an automatic typhoon center positioning method using FY-2 satellite data. The method uses the three-channel image data (IR 1

IR 2

and IR 3) of the FY-2 satellite and searches the outline of each cloud cluster. Then

the method locates the position of the main cloud cluster of the typhoon by setting relevant parameters for outline screening. On the main cloud cluster

the algorithm segments the cloud cluster containing the eye. That is to exclude the interference of the spiral arms of the storm. Subsequently

the method performs a thresholding process and the contour detection. Finally

this method determines the position of the eye through the traversal and conditional calculation of the pixels in the main cloud cluster. This method can automatically detect the typhoon center quickly and accurately.

关键词

Keywords

TyphoonFY-2 satellite dataCenter positioningContour detectionContour filteringThreshold segmentation

references

Simon A, Simon A . Forecast Challenges for the Hurricane Improvement Program (HFIP) Corrected Consensus Approach (HCCA) for tropical cyclone track and intensity guidance[J]. Weather and Forecasting,2018,33(1):35-37. [2] Creasey R L, Elsberry R L. Tropical cyclone center positions from sequence of HDSS sondes deployed along high-altitude overpasses[J]. Weather and Forecasting, 2017, 32(1):317-25.[3] Lu Zhuanxia, Li Xue, Li Jining, Hua Caicheng, Lu Zhe. Reconstruction of the typhoon center and wind speed distribution using HF sky-wave backscatter spectrum[J]. China J. Space Set., 2018,38(4):508-16. [4] Huang Xuanxuan, Zhu Kefeng, Zhao Kun. An algorithm for adaptive identifying and tracking eyes of typhoons near landfall[J]. Journal of Nanjing university(nature sciences),2014,50(6):855-64.[5] Shaohui, Jin, Shuang, et al. A Salient Region Detection and Pattern Matching-Based Algorithm for Center Detection of a Partially Covered Tropical Cyclone in a SAR Image[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(1):280-91.[6] Zhou Guanbo,Qian Qifeng,Lv Xinyan, et al. Application and expectation of artificial intelligence in typhoon monitoring and forecasting[J]. Journal of Meteorological Research and Application,2022,43(2):01-08.[7] Liu Jia, Wang Xudong. Typhoon center location method based on FY-2 remote sensing data[J]. Bulletin of Surveying and Mapping,2020(6):49-52.

Alert me when the article has been cited

Submit

No data

Related Author

No data

Related Institution

No data

⁰