王斐, 覃志豪, 宋彩英. 利用Landsat TM影像进行地表温度像元分解[J]. 武汉大学学报 ( 信息科学版), 2017, 42(1): 116-122. DOI: 10.13203/j.whugis20140604
引用本文: 王斐, 覃志豪, 宋彩英. 利用Landsat TM影像进行地表温度像元分解[J]. 武汉大学学报 ( 信息科学版), 2017, 42(1): 116-122. DOI: 10.13203/j.whugis20140604
WANG Fei, QIN Zhihao, SONG Caiying. An Efficient Approach for Pixel Decomposition of Land Surface Temperature from Landsat TM Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(1): 116-122. DOI: 10.13203/j.whugis20140604
Citation: WANG Fei, QIN Zhihao, SONG Caiying. An Efficient Approach for Pixel Decomposition of Land Surface Temperature from Landsat TM Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(1): 116-122. DOI: 10.13203/j.whugis20140604

利用Landsat TM影像进行地表温度像元分解

An Efficient Approach for Pixel Decomposition of Land Surface Temperature from Landsat TM Data

  • 摘要: 提出了一种基于Landsat TM的地表温度二次像元分解方法,将地表温度的空间分辨率从120 m提高到30 m。首先,利用地表类型的线性统计模型(E-DisTrad)获取初次分解子像元的地表温度,计算得到初次分解子像元的辐亮度;然后,利用面向对象的图像分割方法获取二次分解子像元的权重,实现对地表温度的二次分解;最后,采用升尺度再分解的验证方法进行精度分析,并选取了北京市TM影像进行实例分析。实验结果表明,二次像元分解模型不仅能有效地提高地表温度的空间分辨率,反映出不同地表类型地表温度的空间差异性,而且保证了像元分解前后能量值的一致性,非常适合于复杂地表覆盖地区的热红外波段遥感影像数据的降尺度处理。

     

    Abstract: The spatial resolution of land surface temperature (LST, 120 m) retrieved from thermal infrared (TIR) band is lower than its visible/near-infrared (VNIR) bands (30 m). LST image with high spatial resolution compatible with VNIR bands of Landsat TM is very important for application of the LST image to many studies such as environmental monitoring. The objective of this study is to decompose the coarse pixels of the LST image data into the same pixel scale of the auxiliary VNIR data. Firstly, the E-DisTrad method is used to divide LST of the parent pixels into the sub-pixels to obtain the first decomposition temperature and the theoretical radiance at-sensor of each sub-pixel. Then, a chess-segmentation is done to the temperature of the sub-pixels on the basis of the object-oriented image segmentation method to compute the weight for each sub-pixel, which is consequently used to allocate the thermal radiance for each sub-pixel to generate the decomposed LST image. At last, a method of increase the spatial resolution firstly and then used for double-step pixel decomposition is executed in the study to validate the accuracy and efficiency of the decomposition method for the Landsat TM image of Beijing. The result showed that the double-step pixel decomposition method is applicable for decomposition of LST images for high spatial resolution, reflecting the spatial differences of different land use and land cover and ensure the conservation of energy before and after pixel decomposition. Therefore we can conclude that it is ideally suited for complex covered surface area of downscaling thermal infrared band remote sensing data.

     

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