Validation of ASTER Emissivity Retrieval Using the Mako Airborne TIR Imaging Spectrometer at the Algodones Dune Field in Southern California, USA

Abstract

Validation of emissivity (ε) retrievals from spaceborne thermal infrared (TIR) sensors typically requires spatial extrapolations over several orders of magnitude for a comparison between centimeter-scale laboratory ε measurements and the common decameter and lower resolution of spaceborne TIR data. In the case of NASA’s Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) temperature and ε separation algorithm (TES), this extrapolation becomes especially challenging because TES was originally designed for the geologic surface of Earth, which is typically heterogeneous even at centimeter and decameter scales. Here, we used the airborne TIR hyperspectral Mako sensor with its 2.2 m/pixel resolution, to bridge this scaling issue and robustly link between ASTER TES 90 m/pixel emissivity retrievals and laboratory ε measurements from the Algodones dune field in southern California, USA. The experimental setup included: (i) Laboratory XRD, grain size, and TIR spectral measurements; (ii) radiosonde launches at the time of the two Mako overpasses for atmospheric corrections; (iii) ground-based thermal measurements for calibration, and (iv) analyses of ASTER day and night ε retrievals from 21 different acquisitions. We show that while cavity radiation leads to a 2% to 4% decrease in the effective emissivity contrast of fully resolved scene elements (e.g., slipface slopes and interdune flats), spectral variability of the site when imaged at 90 m/pixel is below 1%, because at this scale the dune field becomes an effectively homogeneous mixture of the different dune elements. We also found that adsorption of atmospheric moisture to grain surfaces during the predawn hours increased the effective ε of the dune surface by up to 0.04. The accuracy of ASTER’s daytime emissivity retrievals using each of the three available atmospheric correction protocols was better than 0.01 and within the target performance of ASTER’s standard emissivity product. Nighttime emissivity retrievals had lower precision (<0.03) likely due to residual atmospheric effects. The water vapor scaling (WVS) atmospheric correction protocol was required to obtain accurate (<0.01) nighttime ASTER emissivity retrievals.

Thermal remote sensing for plant ecology from leaf to globe

“…Soil water content dramatically impacts emissivity with over an 800% increase in emissivity at higher water contents observed, especially in sandy soils (Mira et al, 2007). Even small amounts of atmospheric humidity absorbed by soils in early morning hours can impact emissivity estimates obtained from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, illustrating the importance of soil moisture measurements for TIR validation experiments (Mushkin et al, 2020). Soil emissivity has a greater impact on canopy emissivity in systems where LAI and NDVI values are low (Olioso, 1995).…”

Thermal Remote Sensing from UAVs: A Review on Methods in Coastal Cliffs Prone to Landslides

“…The Jet Propulsion Laboratory (under a NASA contract), in collaboration with the Japanese Space Agency and the Ministry of Trade and Industry of Japan, developed and launched the advanced spaceborne thermal emission and reflection radiometer (ASTER) onboard of the Terra satellite in 1990 [86]. From this period on, the use of TIR remotely sensed data have found important applications in the geological domain for the recognition of minerals, especially in mining surveys [49,87,88]. ASTER can acquire 5 bands in the TIR domain (see Table 2), permitting to enhance the spectral components of minerals and apply complex algorithms for the processing of geological models.…”