Fan, Xiwei; Tang, Bo-Hui; Wu, Hua; Yan, Guangjian; Li, Zhao-Liang; Zhou, Guoqing; Shao, Kun; Bi, Yuyun (2015). Extension of the Generalized Split-Window Algorithm for Land Surface Temperature Retrieval to Atmospheres With Heavy Dust Aerosol Loading. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 8(2), 825-834.

Abstract
It is worth noting that the influences of dust aerosol type and different aerosol loadings were not considered in the development of the generalized split-window (GSW) algorithm. However, numerical simulations showed that the influence of dust aerosol could lead to a maximum land surface temperature (LST) retrieval error of 5.12 K when the aerosol optical depth (AOD) in the atmosphere is 1.0 and viewing zenith angle (VZA) is 60 degrees. This paper focuses on reducing the influence of dust aerosol on the LST retrieval error of the GSW algorithm. A linear function was developed to reduce such influence with respect to the AOD. The slope could be expressed as a function of the difference between the MODIS channel brightness temperatures T-31 and T-32 measured at the top of the atmosphere (TOA) and difference and mean of the two-channel emissivities, and the offset could be used as a constant value for each VZA. The results showed that the retrieval accuracy could be improved by approximately 4 K for AOD = 1.0 and VZA = 60 degrees. Sensitivity analysis in terms of the uncertainties of the input parameters showed that the maximum LST retrieval error is 1.15 K for VZA = 0 degrees. Some of the in situ measurements observed at the Yingke site in northwest China and Arvaikheer site in south Mongolia were used to test the proposed method, respectively. The results showed that the proposedmethod could improve the LST retrieval accuracy by at least 1 K for the GSW algorithm in atmospheres with heavy dust aerosol loading.

DOI:
10.1109/JSTARS.2014.2358584

ISSN:
1939-1404