地球信息科学学报 ›› 2012, Vol. 14 ›› Issue (5): 658-665.doi: 10.3724/SP.J.1047.2012.00658

• 遥感技术与应用 • 上一篇    下一篇

城市尺度组分温度的ASTER数据遥感反演

郑文武1,2, 曾永年1*   

  1. 1. 中南大学地球科学与信息物理学院,中南大学空间信息技术与可持续发展研究中心,长沙 410083;
    2. 衡阳师范学院资源环境与旅游管理系,衡阳 421008
  • 收稿日期:2011-12-12 修回日期:2012-08-22 出版日期:2012-10-25 发布日期:2012-10-25
  • 通讯作者: 曾永年(1959-),男,青海西宁人,教授,博士生导师,从事遥感与地理信息系统及其环境变化研究。 E-mail:ynzeng@csu.edu.cn E-mail:ynzeng@csu.edu.cn
  • 作者简介:郑文武(1978-),男,博士研究生。主要从事GIS和遥感应用研究。E-mail: zhwenwu@163.com
  • 基金资助:

    国家自然科学基金项目(41171326,40771198);湖南省自然科学基金项目(08JJ6023,09JJ4021)资助。

Land Surface Component Temperature Retrieval for Urban Scale Based on ASTER Image

ZHENG Wenwu1,2, ZENG Yongnian1*   

  1. 1. School of Geoscience and Info-Physics, Central South University, Spatial Information Technology and Sustainable Development Research Center of Central South University, Changsha 410083, China;
    2. School of Resource Environment and Tourism Management, Hengyang Normal University, Hengyang 421008, China
  • Received:2011-12-12 Revised:2012-08-22 Online:2012-10-25 Published:2012-10-25

摘要:

为了获取城市尺度组分温度,实现城市水热平衡的高精度反演,探索了一种多波段热红外遥感影像的城市尺度组分温度反演算法。算法选取了植被、土壤和不透水表面等3种组分,并且针对ASTER数据,利用线性混合像元分解方法获取像元平均比辐射率,以MODIS近红外数据估算大气水汽含量和大气透过率,采用牛顿迭代法获取大气平均温度,并用最小二乘原理获取地表组分温度。最后,应用长沙市区的实验影像进行了实验研究,通过纯净像元上组分温度反演结果与分裂窗算法反演结果的对比分析,以及组分温度反演结果与实测数据的对比分析,对算法的精度进行了验证,结果表明:(1)纯净像元上,组分温度反演结果与分裂窗算法反演结果具有较好的相关性,植被组分相关性最高,达0.9796,2种结果平均绝对偏差值为0.36℃;(2)组分温度反演结果与实测组分温度绝对偏差范围为0.2~1.4℃,植被组分温度与实测值偏差相对较小,不透水表面组分温度与实测值偏差相对最大。

关键词: 热红外遥感, ASTER, 组分温度, 长沙

Abstract:

Land surface component temperature has more significant physical meaning, and it reflects the actual distribution of temperature more significantly. Meanwhile, its retrieval algorithms have no need for hypothesis that components in pixels have the same temperature. Although the multi-angle retrieval algorithm of component temperature has become mature gradually, its application in the studies on urban thermal environment is restricted due to the difficulty in acquiring urban-scale multi-angle thermal infrared data. Therefore, based on the existing multi-band remote sensing data, access to appropriate urban-scale component temperature is an urgent issue to be solved in current studies on urban thermal infrared remote sensing. In this paper, a new algorithm to retrieve land surface component temperature for urban area had been proposed. It took advantage of ASTER data, and evaluated mean emissivity of pixels based on linear spectral unmixing, retrieved atmospheric water vapor content from MODIS NIR bands, and used Newton's iterative method to obtain atmosphere average temperature. Finally, an experimental study of this algorithm had been conducted and the retrieval result had been validated using some measured data. The results showed that: (1) the results of component temperature retrieval algorithm and split window algorithm of pure pixels have high correlation coefficient and the correlation coefficient of vegetation is the highest; (2) compared with the measured data, biases of the retrieval result ranged between 0.2 and 1.4℃, and the vegetation component temperature among different components had the smallest bias value.

Key words: ASTER, component temperature, Changsha, thermal remote sensing