PMID- 27879744
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20180104
LR  - 20180104
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 8
IP  - 2
DP  - 2008 Feb 14
TI  - Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from 
      Chinese Geostationary FengYun Meteorological Satellite (FY-2C) Data.
PG  - 933-951
AB  - On the basis of the radiative transfer theory, this paper addressed the estimate 
      ofLand Surface Temperature (LST) from the Chinese first operational 
      geostationarymeteorological satellite-FengYun-2C (FY-2C) data in two thermal 
      infrared channels (IR1,10.3-11.3 mu m and IR2, 11.5-12.5 mu m ), using the 
      Generalized Split-Window (GSW)algorithm proposed by Wan and Dozier (1996). The 
      coefficients in the GSW algorithmcorresponding to a series of overlapping ranging 
      of the mean emissivity, the atmosphericWater Vapor Content (WVC), and the LST 
      were derived using a statistical regressionmethod from the numerical values 
      simulated with an accurate atmospheric radiativetransfer model MODTRAN 4 over a 
      wide range of atmospheric and surface conditions.The simulation analysis showed 
      that the LST could be estimated by the GSW algorithmwith the Root Mean Square 
      Error (RMSE) less than 1 K for the sub-ranges with theViewing Zenith Angle (VZA) 
      less than 30 degrees  or for the sub-rangs with VZA less than 60 degrees and the atmospheric WVC 
      less than 3.5 g/cm(2) provided that the Land Surface Emissivities(LSEs) are known. 
      In order to determine the range for the optimum coefficients of theGSW algorithm, 
      the LSEs could be derived from the data in MODIS channels 31 and 32 provided by 
      MODIS/Terra LST product MOD11B1, or be estimated either according tothe land 
      surface classification or using the method proposed by Jiang et al. (2006); and 
      theWVC could be obtained from MODIS total precipitable water product MOD05, or 
      beretrieved using Li et al.' method (2003). The sensitivity and error analyses in 
      term of theuncertainty of the LSE and WVC as well as the instrumental noise were 
      performed. Inaddition, in order to compare the different formulations of the 
      split-window algorithms,several recently proposed split-window algorithms were 
      used to estimate the LST with thesame simulated FY-2C data. The result of the 
      intercomparsion showed that most of thealgorithms give comparable results.
FAU - Tang, Bohui
AU  - Tang B
AD  - Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of 
      Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 
      Beijing, 100101, China. tangbh@igsnrr.ac.cn.
FAU - Bi, Yuyun
AU  - Bi Y
AD  - TRIO/LSIIT(UMR7005 CNRS)/ENSPS, Bld Sebastien Brant, BP10413, 67412 Illkirch, 
      France.
FAU - Li, Zhao-Liang
AU  - Li ZL
AD  - Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of 
      Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 
      Beijing, 100101, China. lizl@igsnrr.ac.cn.
FAU - Xia, Jun
AU  - Xia J
AD  - Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of 
      Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 
      Beijing, 100101, China.
LA  - eng
PT  - Journal Article
DEP - 20080214
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
PMC - PMC3927530
OTO - NOTNLM
OT  - FY-2C data
OT  - Land surface temperature
OT  - Split-window algorithm.
EDAT- 2008/02/14 00:00
MHDA- 2008/02/14 00:01
PMCR- 2008/02/01
CRDT- 2016/11/24 06:00
PHST- 2008/01/03 00:00 [received]
PHST- 2008/01/31 00:00 [accepted]
PHST- 2016/11/24 06:00 [entrez]
PHST- 2008/02/14 00:00 [pubmed]
PHST- 2008/02/14 00:01 [medline]
PHST- 2008/02/01 00:00 [pmc-release]
AID - s8020933 [pii]
AID - sensors-08-00933 [pii]
AID - 10.3390/s8020933 [doi]
PST - epublish
SO  - Sensors (Basel). 2008 Feb 14;8(2):933-951. doi: 10.3390/s8020933.