Publications

Li, KY; Guan, KY; Jiang, CY; Wang, S; Peng, B; Cai, YP (2021). Evaluation of Four New Land Surface Temperature (LST) Products in the US Corn Belt: ECOSTRESS, GOES-R, Landsat, and Sentinel-3. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 14, 9931-9945.

Abstract
Asa critical indicator of crop water stress, land surface temperature (LST) has been widely used in agricultural applications for monitoring and quantifying crop stress and crop water use. Given the availability of several newly operational satellite LST products in recent years and an increasing demand for reliable LST for agricultural applications, a systematic and thorough study of evaluation of different satellite LST products for croplands is highly needed. This article, thus, evaluated both the new satellite LST products including ECOsystem Spaceborne Thermal Radiometer on the International Space Station (ECOSTRESS), GOES-R, Landsat Provisional and Sentinel-3, and several mainstream LST products including MODIS Land Surface Temperature/Emissivity product (MOD11A1 and MYD11A1), MODIS/Aqua Land Surface Temperature/3-Band Emissivity product (MYD21A1), and VIIRS/NPP Land Surface Temperature and Emissivity LST (VNP21A1), for agricultural landscapes in the U.S. Corn Belt. The evaluation was benchmarked on in situ measurements from 11 SURFRAD or eddy covariance sites in the growing seasons of 2018 and 2019. Results showed that the nighttime and daytime biases of all LST products on different sites were generally within +/- 2 degrees C and +/- 3 degrees C, respectively. Regarding the daytime LST, the highest agreement with ground observations was achieved by ECOSTRESS with an overall absolute bias <0.9 degrees C and a root-mean-squared error (RMSE) < 2.3 degrees C. MOD11A1 and MYD11A1 products slightly underestimated daytime LST with an overall absolute bias < 0.9 degrees C and RMSE < 2.9 degrees C. MYD21A1, Landsat Provisional LST, GOES-R, VNP21A1 and Sentinel-3 LST achieved an overall absolute bias < 2 degrees C and RMSE < 3.6 degrees C in terms of daytime LST. Regarding nighttime LST, all LST products reached a low overall absolute bias < 0.5 degrees C and RMSE < 1.7 degrees C except ECOSTRESS and MOD11A1 (absolute bias < 1.9 degrees C and RMSE < 3.4 degrees C). We observed that only ECOSTRESS, MOD11A1, and MYD11A1 achieved the daytime absolute bias < 1 degrees C. The significant discrepancies between the accuracies of nighttime and daytime LST products indicate that the algorithms of satellite LST products need further improvement under spatial thermal heterogeneous conditions. We further investigated the temporal resolution of cloud-free LST data for the study region, and we found that the cloud-free LST data availability follows the order GOES-R (9.32/day) > MYD11A1 approximate MOD11A1 (0.37/day) > Sentinel-3 (0.26/day) > Landsat Provisional (0.12/day) > ECOSTRESS (0.07/day). Holistically considering factors of bias, RMSE, spatial resolution and cloud-free data availability of different LST products, MOD11A1, and MYD11A1 are relatively appropriate for agriculture-related applications.

DOI:
10.1109/JSTARS.2021.3114613

ISSN:
1939-1404