A high‐performance approach for brightness temperature inversion

Abstract

Brightness temperature inversion is one of the most essential tasks in satellite remote sensing data processing. Accurate calculation of brightness temperature is crucial for many remote sensing applications, such as land surface temperature retrieval, sea surface temperature retrieval, and active fire detection. Due to the huge amount of remote sensing data, performance is also very important for operational use. Major current approaches for brightness temperature inversion are iteration methods, Look-Up- Table (LUT) methods, and empirical formula methods. Some of these algorithms can invert brightness temperature efficiently with limited accuracy, while others can invert brightness temperature at high accuracy but have lower performance. It is desirable to develop an algorithm that can make the balance of accuracy and performance more flexible and can invert brightness temperature efficiently even at high accuracy. In this paper, we analyse the advantages and limitations of the current algorithms for brightness temperature inversion, and propose a new approach based on the high-order approximation of the relationship between band-averaged radiance and brightness temperature. Our approach has the advantages of high accuracy and flexibility. It can be vectorized easily to exploit the advanced features of current computing platforms and improve performance in operational data processing. For validation and analysis, we have applied this method to brightness temperature inversion of MODIS thermal infrared (TIR) measurements and compared with other algorithms for accuracy and performance. The results demonstrate that our approach can be used for operational data processing more flexibly and efficiently.

Satellite-based Applications on Climate Change

“…Band mapping algorithms, as well as software toolkits and testing database, have been developed for MODIS, AIRS comparison, and VIIRS proxy data generation study (Hao et al , b, 2007Qu et al 2005aQu et al , b, 2006aHao and Qu 2009a). The hyper-spectral measurements of the Atmospheric Infrared Sounder (AIRS) onboard NASA satellite Aqua were used to simulate thermal emissive bands of MODIS and VIIRS.…”

Revision of the Single-Channel Algorithm for Land Surface Temperature Retrieval From Landsat Thermal-Infrared Data

“…Therefore, the computation of at-sensor brightness temperatures from the at-sensor registered radiance using ( 9) should employ effective wavelengths. The use of a single wavelength value to retrieve temperature from radiance in the case of a sensor with a certain channel width (sometimes referred in the literature as bandpass effects) has been revised by different authors [14]. A commonly used approximation of Planck's function specific to Landsat is given by [15]…”

Land surface temperature estimation at the global scale using satellite observations

“…However, temperature estimation problem is considered as underdetermined and usually there is a need to incorporate additional measurements or information beside radiance measured by the main observation instrument in order to better constrain the set of possible solutions and improve the overall accuracy of the land surface temperature recovery. Approaches for satellite based LST retrieval can be categorized as procedures that estimate LST in a deterministic way, [1]; or on the other hand approaches that try to improve their estimate through regression based on some other quantities that are easier to measure accurately, e.g. vegetation or spectral indices in the visible or near infrared (VNIR) part of the spectrum, [2].…”