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Identifying Key Meteorological Factors and Thresholds for Vegetation Damage in Hainan Island under Typhoon Yagi
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Weiguang LI1, 2, Run LYU1, 2, Hailiang LI3, 4, *, Xiaomin CHEN1, 2, Wei HOU1, 2, Haiping ZOU1, 2
Chinese Journal of Tropical Crops | 2025, 46(9) : 2250 - 2258
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Chinese Journal of Tropical Crops | 2025, 46(9): 2250-2258
• Post-harvest Treatment & Quality Safety •
Identifying Key Meteorological Factors and Thresholds for Vegetation Damage in Hainan Island under Typhoon Yagi
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Weiguang LI1, 2, Run LYU1, 2, Hailiang LI3, 4, *, Xiaomin CHEN1, 2, Wei HOU1, 2, Haiping ZOU1, 2
Affiliations
  • 1.Hainan Climate Center, Haikou, Hainan 570203, China
  • 2.Hainan Key Laboratory of Meteorological Disaster Prevention and Mitigation in South China Sea, Haikou, Hainan 570203, China
  • 3.Institute of Scientific and Technical Information, Chinese Academy of Tropical Agricultural Sciences / Key Laboratory of Applied Research on Tropical Crop Information Technology of Hainan Province, Haikou, Hainan 571101, China
  • 4.Hainan Tang Huajun Academician Workstation, Haikou, Hainan 571101, China
Published: 2025-09-25 doi: 10.3969/j.issn.1000-2561.2025.09.022
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This study aimed to identify the key factors influencing vegetation changes on Hainan Island under Typhoon Yagi, determine the disaster thresholds, and provide scientific support for typhoon disaster prediction, assessment, and mitigation. Using the GEE platform, Sentinel-2 NDVI data from August 19 to September 18, 2024, covering the period before and after Typhoon Yagi landfall, were analyzed in conjunction with topographic and meteorological variables (such as typhoon path, maximum wind speed, minimum pressure, and precipitation). An XGBoost model was applied to predict post-typhoon NDVI changes, and SHAP analysis was used to explore the nonlinear effects of meteorological factors. The XGBoost model yielded a coefficient of determination (R2) of 0.75 and a root mean square error (RMSE) of 0.12, indicating a high prediction accuracy for post-typhoon NDVI changes. Feature importance analysis within the XGBoost model revealed that pre-typhoon NDVI, typhoon distance, and maximum wind speed were the primary influencing factors, while slope and aspect had a weaker effect. Further SHAP analysis confirmed that typhoon distance and maximum wind speed were the key meteorological factors driving NDVI changes. When the typhoon distance was less than 76.4 km, NDVI showed a significant decline, while NDVI changes intensified when the maximum wind speed exceeded 29.3 m/s, highlighting the crucial role of strong winds in vegetation damage. Regions within 76.4 km (approximately within the 11th wind radius) of the typhoon's path and with maximum wind speeds greater than 29.3 m/s experienced severe vegetation damage. It is recommended that the high-risk areas be prioritized in typhoon warnings and pre-disaster defense measures.

Typhoon Yagi  /  disaster-causing factor  /  vegetation change  /  disaster thresholds  /  XGBoost model  /  SHAP analysis
Weiguang LI, Run LYU, Hailiang LI, Xiaomin CHEN, Wei HOU, Haiping ZOU. Identifying Key Meteorological Factors and Thresholds for Vegetation Damage in Hainan Island under Typhoon Yagi[J]. Chinese Journal of Tropical Crops, 2025 , 46 (9) : 2250 -2258 . DOI: 10.3969/j.issn.1000-2561.2025.09.022
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Year 2025 volume 46 Issue 9
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Article Info
doi: 10.3969/j.issn.1000-2561.2025.09.022
  • Receive Date：2025-02-28
  • Online Date：2026-03-07
  • Published：2025-09-25
Article Data
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History
  • Received：2025-02-28
  • Accepted：2025-04-16
Funding
Affiliations
    1.Hainan Climate Center, Haikou, Hainan 570203, China
    2.Hainan Key Laboratory of Meteorological Disaster Prevention and Mitigation in South China Sea, Haikou, Hainan 570203, China
    3.Institute of Scientific and Technical Information, Chinese Academy of Tropical Agricultural Sciences / Key Laboratory of Applied Research on Tropical Crop Information Technology of Hainan Province, Haikou, Hainan 571101, China
    4.Hainan Tang Huajun Academician Workstation, Haikou, Hainan 571101, China
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https://castjournals.cast.org.cn/joweb/rdzwxb/EN/10.3969/j.issn.1000-2561.2025.09.022
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
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Genus		 种数
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species		 占总种数比例
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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