1994
DOI: 10.1016/0273-1177(94)90197-x
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Spectral emissivity measurements of land-surface materials and related radiative transfer simulations

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Cited by 42 publications
(19 citation statements)
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“…The vegetation and ground emissivity spectra were selected from the MODIS University of California, Santa Barbara (UCSB) Emissivity Library [33] on the composition of the level-1 and level-2 products in the FROM-GLC, and the spectra were entered in the BRDF kernel models to obtain the scene emissivity. Although the emissivity was reported to vary with the view zenith angle, we found that the angular variation of emissivity was insignificant in the FOV (i.e., 15 degrees) of the TIRS instrument and can be disregarded without leading to obvious errors to the LST.…”
Section: Determination Of Lsesmentioning
confidence: 99%
“…The vegetation and ground emissivity spectra were selected from the MODIS University of California, Santa Barbara (UCSB) Emissivity Library [33] on the composition of the level-1 and level-2 products in the FROM-GLC, and the spectra were entered in the BRDF kernel models to obtain the scene emissivity. Although the emissivity was reported to vary with the view zenith angle, we found that the angular variation of emissivity was insignificant in the FOV (i.e., 15 degrees) of the TIRS instrument and can be disregarded without leading to obvious errors to the LST.…”
Section: Determination Of Lsesmentioning
confidence: 99%
“…We note that this value is representative of lavas and pyroclastic rocks in general (Wan et al, 1994;Higgins and Harris, 1997). A 2.5% error in emissivity would yield a 1°C error in surface temperature (ATCOR, 2002), while an error of less than 5% inside of the Stephanos Crater would yield a 2°C error, which is close to the error estimation of the land surface temperature, as will be shown below.…”
Section: Landsat Image Processingmentioning
confidence: 83%
“…However, most of the existed temperature and emissivity separation algorithms [3], [4], [5], [6], [7], [8], [9], [10], [11], [12] designed for processing thermal infrared data will be out of use when it was used to process the mid-infrared data. In order to avoid the uncertainty of surface temperature determination from the difference of soil radiance under sun-shining and sun-shaded condition in the four step method [13] due to the unknown soil emissivity before measurements, we obtains soil thermal infrared emissivity and temperature with high accuracy by utilizing the ISSTES algorithm [11] from thermal infrared data, then introducing the soil temperature into soil mid-infrared emissivity extraction, reducing the number of parameters need to be inversed in mid-infrared, forming redundant observation, and using the least square method to solve the equation at last. Assuming the environmental radiance doesn't change during the measurements, we can get the equation 1 , , 1 , , With the least square method, we acquire 3 , 1 4 , , 2 , , , …”
Section: Theroy and Methodologymentioning
confidence: 99%