Share Email Print
cover

Proceedings Paper

Component temperatures inversion using airborne multi-band thermal infrared image
Author(s): Honglan Shao; Chengyu Liu; Feng Xie; Jianyu Wang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Most of the pixels in thermal infrared remote sensing images are three-dimensional non-isothermal pixel, especially for the pixels with the size of meters, tens of meters or hundreds of meters which have received widespread attention in geoscience and remote sensing. Even though the sizes of some pixels reach centimeters, the three-dimensional non-isothermal phenomenon may still arise. So, it is very important to accurately determine the component temperatures in one pixel for the related researches in geoscience. The remote sensing data used to carry out the related inversion experiments in this paper was the airborne remote sensing data obtained by WSIS (Wide Spectrum Imaging Spectrometer) the imaging wave bands of which include VNIR (visible light and near infrared), SWIR (short wave infrared) and TIR (thermal infrared). Firstly, the components of all the pixels in the image were determined through the VNIR images using linear mixing spectral model. Secondly, the emissivity of each component in every pixel in the image was determined according to a prior knowledge base of emissivity of many surface features. Thirdly, the so called average temperature of every pixel was retrieved using the TES (temperature and emissivity separation) algorithm. The retrieved temperature was regarded as initial value. The multi-band equations were established after the linearization of Planck function, and the component temperatures of every pixel in the image were inversed. The results show that the accuracy of the component temperatures inversion in one pixel can be improved obviously, with the combination of the VNIR, SWIR and TIR images.

Paper Details

Date Published: 26 November 2014
PDF: 12 pages
Proc. SPIE 9263, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V, 926320 (26 November 2014); doi: 10.1117/12.2069141
Show Author Affiliations
Honglan Shao, Shanghai Institute of Technical Physics (China)
Chengyu Liu, Shanghai Institute of Technical Physics (China)
Feng Xie, Shanghai Institute of Technical Physics (China)
Jianyu Wang, Shanghai Institute of Technical Physics (China)


Published in SPIE Proceedings Vol. 9263:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V
Allen M. Larar; Makoto Suzuki; Jianyu Wang, Editor(s)

© SPIE. Terms of Use
Back to Top