A comparison of four methods for extracting Land Surface Emissivity and Temperature in the Thermal Infrared Hyperspectral Data

Document Type: Original Article


School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran


Land Surface Temperature (LST) and Land Surface Emissivity (LSE) are two important physical properties
of Earth's surface. LST retrieval plays a valuable role in environmental studies. Therefore, in order to
estimate LST accurately, it is necessary to obtain LSEs. The HyTES (Hyperspectral Thermal Emission
Spectrometer) instrument has 256 spectral bands covering the thermal infrared (TIR) spectral range. Due to
a large number of narrow bandwidths of HyTES, this sensor can produce the accurate LST and LSEs. The
main goal of this paper is to evaluate the accuracy of LSE and LST retrieval methods from HyTES data and
to improve the accuracy of the Normalization (NOR) method. For this purpose, four different methods have
been considered to retrieve LSE: (i) the Reference Channel method (REF), (ii) the Emissivity Normalization
method, (iii) the Alpha emissivity method (AlPHA) and (iv) a method to improve the NOR algorithm. The
first three methods have been widely used with thermal multispectral data in other researches. These
methods were used with HyTES hyperspectral data in this paper; the fourth is a new method that improved
the accuracy of the NOR method. The results of quality assessment show that the emissivity RMSEs of the
REF, NOR, ALPHA methods and the new proposed method are 0.021, 0.815, 0.034 and 0.0201,
respectively. Also, LST RMSEs of the REF and NOR methods are less than 1.5 K.


Main Subjects

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