Towards an Operational, Split Window-Derived Surface Temperature Product for the Thermal Infrared Sensors Onboard Landsat 8 and 9

Abstract

The split window technique has been used for over thirty years to derive surface temperatures of the Earth with image data collected from spaceborne sensors containing two thermal channels. The latest NASA/USGS Landsat satellites contain the Thermal Infrared Sensor (TIRS) instruments that acquire Earth data in two longwave infrared bands, as opposed to a single band with earlier Landsats. The United States Geological Survey (USGS) will soon begin releasing a surface temperature product for Landsats 4 through 8 based on the single spectral channel methodology. However, progress is being made toward developing and validating a more accurate and less computationally intensive surface temperature product based on the split window method for Landsat 8 and 9 datasets. This work presents the progress made towards developing an operational split window algorithm for TIRS. Specifically, details of how the generalized split window algorithm was tailored for the TIRS sensors are presented, along with geometric considerations that should be addressed to avoid spatial artifacts in the final surface temperature product. Validation studies indicate that the proposed algorithm is accurate to within 2 K when compared to land-based measurements and to within 1 K when compared to water-based measurements, highlighting the improved accuracy that may be achieved over the current single-channel methodology being used to derive surface temperature in the Landsat Collection 2 surface temperature product. Surface temperature products using the split window methodologies described here can be made available upon request for testing purposes.

Validation of Sentinel-3 SLSTR Land Surface Temperature Retrieved by the Operational Product and Comparison with Explicitly Emissivity-Dependent Algorithms

“…From this comparison, they observed a standard deviation of up to 2 K at the grassland sites and a general underestimation for the pyrgeometer data. This is in agreement with LST validations performed for various satellite sensors, e.g., MODIS [63], VIIRS [60], and Landsat-8 [64], which used pyrgeometer measurements as reference: especially at daytime, these studies obtained similar standard deviations of around 2 K at grassland sites.…”

“…A maximum increment of up to +20 K was used to produce Sobrino16 and Zhang19, although these increments were only for T 0 < 280 K on the latter. The Zheng19 SWA was produced with even larger increments of up to +30 K: this can be interesting for some applications (e.g., urban heat island, analyses of extreme temperatures), but can also cause an overfitting of retrieval coefficients, which in turn can increase retrieval uncertainty, particularly over the most common natural surfaces [64].…”

Low-Cost Radiometer for Landsat Land Surface Temperature Validation

“…The current ground-based network used to validate ST products (SURFRAD) collects measurements over a broad spectrum and is accurate to within 4 K of Landsat 8-derived ST [29]. The need for a ground network that is more accurate than the 2 K accuracy of the Landsat split-window ST algorithm [24] is apparent and was the focus of this study.…”

“…The ASTER-GED consists of emissivity maps at 100 m spatial resolution from data acquired between 2000 and 2008. The emissivity of the target was estimated by establishing an empirical relationship between the effective emissivity for each band of the prototype radiometer and ASTER Band 13 (10.25-10.95 µm) and Band 14 (10.95-11.65 µm) respectively using the natural material emissivity data provided by the ICESS group from the University of California Santa Barbara [23][24][25]. The emissivity of the geographic location of the deployed radiometer was then calculated from the empirical relationship and used in Equation (1).…”

Editorial for the Special Issue “Remote Sensing Monitoring of Land Surface Temperature”

“…The combination of the state-of-the-art in the thermal infrared (TIR) domain [1][2][3] with the recent advances in the capabilities provided by operating and new satellites [4][5][6][7][8][9][10], UAVbased [11] or aerial remote sensing are boosting the use of land surface temperature (LST) in a variety of research fields [5,8,9,11,12]. LST plays a key role in soil-vegetation-atmosphere processes and becomes crucial in the estimation of surface energy flux exchanges, actual evapotranspiration, or vegetation and soil properties [8,9].…”