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| Land surface temperature retrieval of FY-3D MWRI based on XGBoost model |
| Xin Pingping1, Shen Ju2, Tian Yuan1, Shang Weibang1 |
1. Dachaidan Administrative Committee Meteorological Bureau of Qinghai Province,Haixi Prefecture 817000; 2. Haixi Prefecture Meteorological Bureau of Qinghai Province,Haixi Prefecture 817100 |
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Abstract Surface temperature is an important parameter in surface physical processes,and microwave remote sensing is one of the main methods for obtaining surface temperature information under cloud conditions.This study is based on the XGBoost model and uses FY-3D/MWRI brightness temperature data to construct an LST estimation model for the Qinghai Plateau.The performance of this model in typical flood and drought processes is compared and analyzed,and compared with existing business products.The results indicate that the model can well reflect the two low-temperature and two high-temperature regions of the Qinghai Plateau,and it performs stably during floods and droughts.The XGBoost model results have high accuracy.Compared with the CLDAS surface temperature product,the correlation coefficient r is higher by 0.12,the root mean square error RMSE is lower by 3.8 K,and the average absolute error MAE is lower by 3.2 K,indicating that the XGBoost model results have certain advantages in surface temperature inversion on the Qinghai Plateau.
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Received: 27 June 2025
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| [1] |
姜鹏,纪瑞鹏,冯锐,等.基于多源遥感数据的辽宁地表温度反演及空间分布研究 [J].气象与环境学报,2012,28(3):44-48.
|
| [2] |
朱怀松,刘晓锰,裴欢.热红外遥感反演地表温度研究现状 [J].干旱气象,2007(2):17-21.
|
| [3] |
练义华.基于深度学习和机器学习的全天候地表温度估算方法研究[D].北京:中国农业科学院,2023.
|
| [4] |
胡翠琴,马英,黄晓东,等.基于随机森林算法的青藏高原AMSR2地表温度降尺度反演 [J].草业科学,2025,42(1):11-22.
|
| [5] |
王雅萍,王遂缠,孔令旺.CLDAS降水产品的适用性分析及机器学习订正应用 [J].气象水文海洋仪器,2024,41(3):111-115.
|
| [6] |
曾杨,赖晨,张娟娟.基于多源探测数据的液态降水现象及量级综合判识研究 [J].气象水文海洋仪器,2024,41(4):29-32,36.
|
| [7] |
赵美亮,曹广超,曹生奎,等.1980——2017年青海省地表温度时空变化特征 [J].干旱区研究,2021,38(1):178-187.
|
|
|
|