Short Name:

ASTER L2 Surface Emissivity V003

The ASTER L2 Surface Emissivity is an on-demand product (( generated using the five thermal infrared (TIR) bands (acquired either during the day or night time) between 8 and 12 µm spectral range. It contains surface emissivity over the land at 90 meters spatial resolution. Estimates of surface emissivity were thus far only derived using surrogates such as land-cover type or vegetation index. The Temperature/Emissivity Separation (TES) algorithm is used to derive both E (emissivity) and T (surface temperature). The main goals of the TES algorithm include: recovering accurate and precise emissivities for mineral substrates, and estimating accurate and precise surface temperatures especially over vegetation, water and snow.The TES algorithm is executed in the ASTER processing chain following generation of ASTER Level-2 Surface Radiance (TIR). The land-leaving radiance and down-welling irradiance vectors for each pixel are taken in account. Emissivity is estimated using the Normalized Emissivity Method (NEM), and is iteratively compensated for reflected sunlight. The emissivity spectrum is normalized using the average emissivity of each pixel. The minimum-maximum difference (MMD) of the normalized spectrum is calculated and estimates of the minimum emissivity derived through regression analysis. These estimates are used to scale the normalized emissivity and compensate for reflected skylight with the derived refinement of emissivity. ASTER Level 2 data requests for observations that occurred after May 27, 2020 will resort back to using the climatology ozone input. Additional information can be found in the ASTER L2 Processing Options Update ( V003 data set release date: 2002-05-03 Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at

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