Study On Component Temperature Inversion Algorithm And The Scale Structure For Remote Sensing Pixel

Land surface temperature (LST) is an important parameter in the study of energy balance/exchange over land surface. Because natural land surface is usually heterogeneous and not isothermal, the pixel-mean temperature cannot adequately represent the actual thermal state of the surface. Many applications will appreciate component temperature input for better results. With the support of ground-based experiments and other auxiliary information, it is possible to retrieve component temperature from multi-angular or multi-spectral thermal infrared (TIR) remote sensing data. Presented in this paper is the theory, as well as practice, of component temperature inversion.Because a remote sensing pixel in TIR band is usually a mixture of several land cover types, the "pixel-subpixel-component" structure was chosen to be the framework of forward model and inversion strategy in this paper. Here, a "subpixel" was defined as the fraction inside one pixel that is of pure land cover type instead of its usual meaning that is ambiguous between "component" and "endmember". It was pointed out that the "subpixel-component" structure is usually complex and should be modeled with 3-D model, while "pixel-subpixel" structure can be approximated with 2-D model. So, most complex models that describe the directionality of land surface are subpixel models, and they can be integerated into pixel models with linear combination. In the component temperature inversion algorithm, the "pixel-subpixel" decomposition was done by exploiting resolution difference between TIR and VNIR (visible and near infrared) data; and the decomposition of "subpixel-component" was done by inverting BRDF model with VNIR data.It is important that the forward models used in inversion should be effective as well as simple. So, a well-known BRDF model, the SAIL model, was adapted and extended to thermal bands by directly modifying its RT differential equations. The extended SAIL model can be used to predict directional thermal radiance or to derive component equivalent emissivity for horizontally homogeneous canopy.Inversion algorithm was built on the concept of component equivalent emissivity and its matrix representation. Bayes inference was also incorporated into the frame so that a priori knowledge could be introduced to be constraint of result. It was also shown in the error analysis that a priori information was very critical for inversion of those unknown variables that are not sensitive to observation. A priori information wasexpressed as mean and std. deviation and the result of inversion was expressed as posterior mean and posterior std. deviation. The gained information for a variable could be measured with the decrement of its std. deviation before and after inversion. Based on this measurement, it was shown that (1) component temperature got more information with multi-angular data set than with single-angle and multi-spectral data set; (2) single-angle and multi-spectral data set could be used to retrieve component temperature only if a priori information is enhanced. Because component temperature varies much throughout a scene of remote sensing image, globally defined a priori information can never be very precise. So it is necessary to give separate a priori mean and std. deviation for each pixel. Exploiting spatial correlation of the unknown variables, an iterative upgrade method is proposed to extract new a priori mean and std. deviation from a neighborhood of previous inverted posterior mean and std. deviation.As part of work in component inversion practice, chapter 4 gave some details for basic data processing and correction. Mainly introduced here was an automatic image registration algorithm, which was specially designed for airborne multi-angular remote sensing images. It cooperated with wavelet decomposition, multi-variant correlation coefficient and B-spline warping function in the frame of pyramidal resolution matching; and it performed well with images that contain localized distortion and spectral change. After registration, su...