Title
Noise-sensitivity Analysis and Improvement of Automatic Retrieval of Temperature and Emissivity Using Spectral Smoothness.
Abstract
There are numerous algorithms that can be used to retrieve land surface temperature (LST) and land surface emissivity (LSE) from hyperspectral thermal infrared (HTIR) data. The algorithms are sensitive to a number of factors, where noise is difficult to handle due to its unpredictability. Although there is a lot of research regarding the influence of noise on retrieval errors, few studies have focused on the mechanism. In this study, we selected the automatic retrieval of temperature and emissivity using spectral smoothness (ARTEMISS) algorithm-the representative of the iterative spectral smoothness temperature-emissivity separation algorithm family-as the research object and proposed an improved algorithm. First, we analyzed the influence mechanism of noise on the retrieval errors of ARTEMISS in theory. Second, we carried out a simulation and inversion experiment and analyzed the relationship between instrument spectral resolution, noise level, the ARTEMISS parameter setting and the retrieval errors separately. Last, we proposed an improved method (resolution-degrade-based spectral smoothness algorithm, RDSS) based on the mechanism and law of the influence of noise on retrieval errors and provided corresponding suggestions on instrument design. The results show that RDSS improves the accuracy of temperature inversion and is more effective for thermal infrared data with a high noise level and high spectral resolution, which can reduce the LST inversion error by up to 0.75 K and the LSE median absolute deviation (MAD) by 31%. In the presence of noise in HTIR data, the RDSS algorithm performs better than the ARTEMISS algorithm in terms of temperature-emissivity separation.
Year
DOI
Venue
2020
10.3390/rs12142295
REMOTE SENSING
Keywords
DocType
Volume
hyperspectral thermal infrared,spectral smoothness,temperature-emissivity separation,sensitivity analysis,noise
Journal
12
Issue
Citations 
PageRank 
14
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Honglan Shao100.34
Chengyu Liu200.34
Feng Xie300.34
Chunlai Li416.23
Wang, Y.J.521621.29