基于Landsat-8数据的地表温度遥感反演研究

摘要地表温度是地表能量和水平衡的重要指标，对气象、水文、地质和生态等领域研究有着重要意义。与传统地面点实测温度相比，热红外遥感信息量更大、覆盖面更广、动态性更好，可以准确地获取局部温度的空间差异，是资源环境动态监测的重要内容。在城市热岛、林火监测、旱灾监测等领域都有广泛的研究。所以对地表温度遥感反演研究有重要意义。

随着遥感技术的发展，利用遥感反演地表温度的方法不断出现，如劈窗算法、双角度法和单通道算法等。Landsat 系列卫星数据是地表温度反演的重要数据源之一。本文选取徐州市区周边作为研究区，基于 Landsat 8 数据，分别采用 Offer Rozenstein 劈窗算法和 Juan C.Jiménez-Muñoz 劈窗算法，实现地表温度反演。结果表明：两种劈窗算法均能够较好的反应徐州市区周边的地表温度趋势。其中， Offer Rozenstein 算法相比于 Juan C.Jiménez-Muñoz 算法反演精度略高。70789

毕业论文关键词：地表温度反演 Landsat-8 TIRS 劈窗算法徐州

The Study of Land Surface Temperature Retrieval based on Landsat 8 Data

Abstract Land surface temperature is one of the vital parametes of dynamic change monitoring earth's resources environment, meteorology, hydrology, geology, ecology, and biogeochemistry research have important significance. Compared with conventional ground point measuring temperature, thermal infrared remote sensing has a wide coverage, amounts of information, as good dynamic performance and can accurately obtain area surface temperature difference, and then analyzes its influence on resources and environment changes, which is the important content of resource environment dynamic monitoring. In the urban heat island effect, the forest fire , drought monitoring and other fields have much research. Therefore, the study of land surface temperature inversion have important significance.

Remote sensing technology is on a rapid development, using it to retrieve land surface temperature appear constantly, such as split window algorithm, double Angle method and the single channel algorithm, etc. Landsat series satellite data is an important remote sensing data of land surface temperature inversion. Selecting Xuzhou city surrounding area as the study area, this paper uses Landsat 8 satellite remote sensing data, adopt the Offer Rozenstein split window algorithm and Juan C.Jiménez-Muñoz split window algorithm to realize land surface temperature inversion. The results show that the two split window algorithms are better reacting surface temperature trends around the city. But overall, Offer Rozenstein algorithm is more accurate than Juan C.Jiménez-Muñoz split window algorithm.

Key Words: land surface temperature retrieval Landsat-8 TIRS split-window algorithm Xuzhou

摘要 .. I

Abstract II

目录 III

图清单 .. IV

表清单 .. IV

变量注释表 .. V

1 绪论 1

1.1 研究背景及意义..1

1.2 国内外研究进展 1

1.3 研究内容与方法 3

2 地表温度反演算法 5

2.1 反演的理论基础 5

2.2 本研究中两种劈窗算法简介 6

2.3 反演算法参数敏感性说明基于Landsat-8数据的地表温度遥感反演研究:http://www.751com.cn/guanli/lunwen_80178.html