A repository of Python code and sample files related to the IMPMCT dataset.
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| Natura: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901740652068864 |
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| author | Fang, Runzhuo |
| author_facet | Fang, Runzhuo |
| contents | <h2><strong>Here we will provide the main code for generating the IMPMCT dataset( <a href="https://doi.org/10.5281/zenodo.15113263">https://doi.org/10.5281/zenodo.17142448 </a>).</strong></h2> <p dir="auto">Regarding the yolov8-obb-pose model, please refer to <a href="https://github.com/yzqxy/ultralytics-obb_segment">https://github.com/yzqxy/ultralytics-obb_segment</a>.</p> <p dir="auto">The relevant model weights and validation sets are restored in <a href="https://doi.org/10.5281/zenodo.15119534" rel="nofollow">https://doi.org/10.5281/zenodo.15119534</a>.</p> <p dir="auto">1 identify.ipynb: This file is used to identify the vortex tracks in ERA5 data.</p> <p dir="auto">2 AVHRR_matched.ipynb: This file is used to match AVHRR data with the vortex tracks .</p> <p dir="auto">3 VCI_create.ipynb: This file is used to create the VCI images for every vortex track if AVHRR data is available.</p> <p dir="auto">4 obb_pose_detect.ipynb: This file is used to detect the cyclone features in the VCI images using the yolov8-obb-pose model.</p> <p dir="auto">5 ASCAT_AVHRR_matched.ipynb: This file is used to match ASCAT\QUIKSCAT data with the cyclone features identified in the previous step.</p> <p dir="auto">6 example_data(folder) is the example dataset used in above codes.</p> <p dir="auto">7 match_stoll_ROJO.ipynb: This file is used to match the vortex tracks with the PLs tracks in the ROJO and Stoll dataset.</p> <p dir="auto">8 <a title="cmems_tracks_45_0.8_0.5_0.15.xlsx" href="https://github.com/thebluewind/IMPMCT/blob/main/cmems_tracks_45_0.8_0.5_0.15.xlsx">cmems_tracks_*</a>: Three excels for replying Prof. Stoffelen (<a href="https://doi.org/10.5194/essd-2025-186-AC4">https://doi.org/10.5194/essd-2025-186-AC4</a>)</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17498230 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A repository of Python code and sample files related to the IMPMCT dataset. Fang, Runzhuo <h2><strong>Here we will provide the main code for generating the IMPMCT dataset( <a href="https://doi.org/10.5281/zenodo.15113263">https://doi.org/10.5281/zenodo.17142448 </a>).</strong></h2> <p dir="auto">Regarding the yolov8-obb-pose model, please refer to <a href="https://github.com/yzqxy/ultralytics-obb_segment">https://github.com/yzqxy/ultralytics-obb_segment</a>.</p> <p dir="auto">The relevant model weights and validation sets are restored in <a href="https://doi.org/10.5281/zenodo.15119534" rel="nofollow">https://doi.org/10.5281/zenodo.15119534</a>.</p> <p dir="auto">1 identify.ipynb: This file is used to identify the vortex tracks in ERA5 data.</p> <p dir="auto">2 AVHRR_matched.ipynb: This file is used to match AVHRR data with the vortex tracks .</p> <p dir="auto">3 VCI_create.ipynb: This file is used to create the VCI images for every vortex track if AVHRR data is available.</p> <p dir="auto">4 obb_pose_detect.ipynb: This file is used to detect the cyclone features in the VCI images using the yolov8-obb-pose model.</p> <p dir="auto">5 ASCAT_AVHRR_matched.ipynb: This file is used to match ASCAT\QUIKSCAT data with the cyclone features identified in the previous step.</p> <p dir="auto">6 example_data(folder) is the example dataset used in above codes.</p> <p dir="auto">7 match_stoll_ROJO.ipynb: This file is used to match the vortex tracks with the PLs tracks in the ROJO and Stoll dataset.</p> <p dir="auto">8 <a title="cmems_tracks_45_0.8_0.5_0.15.xlsx" href="https://github.com/thebluewind/IMPMCT/blob/main/cmems_tracks_45_0.8_0.5_0.15.xlsx">cmems_tracks_*</a>: Three excels for replying Prof. Stoffelen (<a href="https://doi.org/10.5194/essd-2025-186-AC4">https://doi.org/10.5194/essd-2025-186-AC4</a>)</p> |
| title | A repository of Python code and sample files related to the IMPMCT dataset. |
| url | https://doi.org/10.5281/zenodo.17498230 |