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Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels
Peng, Zhi Qing1; Xin, Xiaozhou1; Jiao, Jin Jun1; Zhou, Ti1; Liu, Qinhuo1
刊名Hydrology and Earth System Sciences
2016
卷号20期号:11页码:4409-4438
关键词AEROSOL PLAIN SUMMER VISIBILITY EMISSIONS FOG
通讯作者Xin, Xiaozhou (xin-xzh@163.com)
英文摘要Evapotranspiration (ET) plays an important role in surfaceatmosphere interactions and can be monitored using remote sensing data. However, surface heterogeneity, including the inhomogeneity of landscapes and surface variables, significantly affects the accuracy of ET estimated from satellite data. The objective of this study is to assess and reduce the uncertainties resulting from surface heterogeneity in remotely sensed ET using Chinese HJ-1B satellite data, which is of 30m spatial resolution in VIS/NIR bands and 300m spatial resolution in the thermal-infrared (TIR) band. A temperature-sharpening and flux aggregation scheme (TSFA) was developed to obtain accurate heat fluxes from the HJ-1B satellite data. The IPUS (input parameter upscaling) and TRFA (temperature resampling and flux aggregation) methods were used to compare with the TSFA in this study. The three methods represent three typical schemes used to handle mixed pixels from the simplest to the most complex. IPUS handles all surface variables at coarse resolution of 300m in this study, TSFA handles them at 30m resolution, and TRFA handles them at 30 and 300m resolution, which depends on the actual spatial resolution. Analyzing and comparing the three methods can help us to get a better understanding of spatial-scale errors in remote sensing of surface heat fluxes. In situ data collected during HiWATER-MUSOEXE (Multi-Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces of the Heihe Watershed Allied Telemetry Experimental Research) were used to validate and analyze the methods. ET estimated by TSFA exhibited the best agreement with in situ observations, and the footprint validation results showed that the R2, MBE, and RMSE values of the sensible heat flux (H) were 0.61, 0.90, and 50.99Wm-2, respectively, and those for the latent heat flux (LE) were 0.82, -20.54, and 71.24Wm-2, respectively. IPUS yielded the largest errors in ET estimation. The RMSE of LE between the TSFA and IPUS methods was 51.30Wm-2, and the RMSE of LE between the TSFA and TRFA methods was 16.48Wm-2. Furthermore, additional analysis showed that the TSFA method can capture the subpixel variations of land surface temperature and the influences of various landscapes within mixed pixels. © 2016 Author(s).
学科主题Geology; Water Resources
类目[WOS]Geosciences, Multidisciplinary ; Water Resources
收录类别SCI ; EI
语种英语
WOS记录号WOS:20164603012633
内容类型期刊论文
源URL[http://ir.radi.ac.cn/handle/183411/39167]  
专题遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位1. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing
2.100101, China
3. University of Chinese Academy of Sciences, Beijing
4.100049, China
5. Joint Center for Global Change Studies (JCGCS), Beijing
6.100875, China
推荐引用方式
GB/T 7714
Peng, Zhi Qing,Xin, Xiaozhou,Jiao, Jin Jun,et al. Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels[J]. Hydrology and Earth System Sciences,2016,20(11):4409-4438.
APA Peng, Zhi Qing,Xin, Xiaozhou,Jiao, Jin Jun,Zhou, Ti,&Liu, Qinhuo.(2016).Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels.Hydrology and Earth System Sciences,20(11),4409-4438.
MLA Peng, Zhi Qing,et al."Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels".Hydrology and Earth System Sciences 20.11(2016):4409-4438.
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