Journal of Geo-information Science ›› 2020, Vol. 22 ›› Issue (8): 1743-1751.doi: 10.12082/dqxxkx.2020.190379

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Remote Sensing Estimation of Surface Broadband Emissivity over the Deserts in Xinjiang

Aynigar· yalkun1,2(), ALI Mamtimin2, LIU Suhong1, YANG Fan3, HE Qing3, LIU Yongqiang1,2,*()   

  1. 1. College of Resources & Environmental Sciences, Xinjiang University, Urumqi 830046, China
    2. Taklimakan Desert Meteorology Field Experiment Station of CMA, Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
    3. Uygur Autonomous Regional Meteorological Service, Urumqi 830002, China
  • Received:2019-07-16 Revised:2020-02-02 Online:2020-08-25 Published:2020-10-25
  • Contact: LIU Yongqiang E-mail:15899104482@163.com;lyqxju@163.com
  • Supported by:
    National Natural Science Foundation of China(41675011)

Abstract:

Surface Broadband Emissivity (BBE) is a key variable for estimating surface longwave net radiation, which is a component of the surface radiation budget and an important parameter in climate, weather, and hydrological models. A constant land surface longwave emissivity, or simple parameterization, has been adopted by many land-surface models because of the lack of reliable observations. Moreover, of all the various Earth surface types, bare soil has the largest variation in BBE. Thus, accurate estimation of land surface emissivity for bare soil is important for retrieval of surface temperature and calculation of longwave surface energy budget. In order to retrieval accurate emissivity from remote sensing in the bare-soil area, two types of data were obtained indeserts of Xinjiang: (1) Land surface emissivity at 25 sites along two highways across the Taklimakan Desert. The spectral of broadband emissivity were measured in the fall of 2013 and 2014 by portable FTIR ( Fourier Transform thermal InfraRed spectroscopy), (2) MODIS (Moderate Resolution Imaging Spectroradiometer) temperature and emissivity data ( MOD11A1 and MOD11B1 ), reflectance data ( MOD09GA ), and albedo data (MCD43A3) of the same period.The two types of data were combined to estimate the surface emissivity of the Xinjiang deserts. Firstly, we re-estimated the coefficients of the MODIS BBE equation and the GLASS (Global Land Surface Satellite) BBE equation. The MODIS and GLASS BBE equations were both optimized with the new coefficients. Secondly, we compared with the optimized GLASS BBE equation with the FTIR and MODIS BBE equations. By comparison, the accuracy of optimized GLASS BBE equation was significantly improved, which was proved by: (1) According to the error analysis against FTIR data, the value of R2 (coefficient of determination) increased from 0.42 to 0.95, the RMSE ( Root Mean Square Error ) and the Bias reduced by 1 and 3 orders of magnitude, respectively; (2) Compared to MODIS BBE data, the value of R2 increased from 0.69 to 0.91, the RMSE and Bias reduced by 1 and 2 orders of magnitude, respectively. In our study, the BBE in Xinjiang desertswasfinally calculated using the optimized GLASS BBE equation. Our results show that the BBE in Taklimakan Desert ranged from 0.88 to 0.91, which was due to the single type of terrain, soil, and particularly aridity.While the Gurbantunggut Desert and the Kumtag Desert were more affected by topography and vegetation, their BBE values (0.89~0.95 and 0.89~0.94, respectively) were slightly higher than that of the Taklimakan Desert. The sparse vegetated area around the deserts and the edge area had the highest BBE(0.95~1.00).The BBE equationsdeveloped for Xinjiang desertsbased on GLASS and MODIS provides useful reference forfuture land-surface process models.

Key words: surface broadband emissivity, GLASS, MODIS, FTIR, remote sensing, Taklimakan desert, Gurbantunggut desert, Kumtag desert