Landsat 9数据的地表温度反演算法优化

doi:10.13474/j.cnki.11-2246.2023.0204

测绘通报 ›› 2023, Vol. 0 ›› Issue (7): 74-79.doi: 10.13474/j.cnki.11-2246.2023.0204

Landsat 9数据的地表温度反演算法优化

温亚飞^1,2, 刘宇², 王光辉², 张秋昭¹

1. 中国矿业大学环境与测绘学院, 江苏徐州 221116;
2. 自然资源部国土卫星遥感应用中心, 北京 100048

收稿日期:2023-03-16 出版日期:2023-07-25 发布日期:2023-08-08
通讯作者: 刘宇。E-mail:867532660@qq.com
作者简介:温亚飞(1993-),男,硕士,主要研究方向为热红外地表温度反演理论和应用。E-mail:674601798@qq.com

Optimization of land surface temperature inversion algorithm for Landsat 9 data

WEN Yafei^1,2, LIU Yu², WANG Guanghui², ZHANG Qiuzhao¹

1. School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China;
2. Land Satellite Remoting Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China

Received:2023-03-16 Online:2023-07-25 Published:2023-08-08

摘要/Abstract

摘要： 地表温度作为地表与大气之间能量交换的关键参数被广泛地用于众多领域。本文针对Landsat 9数据,优化了单窗算法模型和劈窗算法模型,实现了地表温度反演,并结合SURFRAD站点实测数据和地表温度产品进行了精度验证分析。结果表明:两种算法模型的确定系数均大于0.96,其中劈窗算法模型精度较高,误差(RMSE)值为1.45 K左右,单窗算法模型精度较低,误差(RMSE)值为1.61 K左右;劈窗算法模型相较于单窗算法模型对参数的敏感性较低,在高水汽含量范围内,劈窗算法模型的结果要优于单窗算法模型的结果;本文提出的地表温度反演方法结果与官方地表温度产品的误差(RMSE)值均在2.5 K以内,可满足热红外遥感数据生产地表温度产品的应用需求。

关键词: 地表温度, Landsat 9, 单窗算法, 劈窗算法, 热红外遥感

Abstract: As a key parameter of energy exchange between surface and atmosphere, land surface temperature (LST) is widely used in many fields. Based on the Landsat 9 TIRS data, this paper optimized and updated the parameters of single window algorithm model and split window algorithm model to realize surface temperature inversion, and combined the measured data of SURFRAD site and the land surface temperature products for accuracy verification analysis. The results show that the determination coefficients of the two algorithms are both greater than 0.96. The split window algorithm model has higher accuracy and the error (RMSE) is about 1.45 K, while the single channel algorithm model has lower accuracy and the error (RMSE) is about 1.61 K. Compared with the single channel model, the split window model is less sensitive to the parameters. In the range of high water vapor content, the results of the split window model are better than those of the single channel model. The error (RMSE) values of the land surface temperature inversion method proposed in this paper and the official land surface temperature products are both within 2.5 K, which can meet the application requirements of producing land surface temperature products with thermal infrared remote sensing data.

Key words: surface temperature, Landsat 9, single channel algorithm, split window algorithm, thermal infrared remote sensing

中图分类号:

P237

温亚飞, 刘宇, 王光辉, 张秋昭. Landsat 9数据的地表温度反演算法优化[J]. 测绘通报, 2023, 0(7): 74-79.

WEN Yafei, LIU Yu, WANG Guanghui, ZHANG Qiuzhao. Optimization of land surface temperature inversion algorithm for Landsat 9 data[J]. Bulletin of Surveying and Mapping, 2023, 0(7): 74-79.

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Landsat 9数据的地表温度反演算法优化

Optimization of land surface temperature inversion algorithm for Landsat 9 data

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