NDLI: Estimating Evapotranspiration using Remote Sensing in the Haihe Basin

Content Provider	IEEE Xplore Digital Library
Author	Jun Xiong Bingfang Wu Yuemin Zhou Jing Li
Copyright Year	2006
Description	Author affiliation: Inst. of Remote Sensing Applic., Chinese Acad. of Sci., Beijing (Jun Xiong; Bingfang Wu; Yuemin Zhou; Jing Li)
Abstract	In this paper, the potential of using three existing models coupled to estimate the regional evapotranspiration (ET) in the Haihe basin (China) is studied. The Surface Energy Balance System (SEBS) is used to determining the spatio-temporal variability in regional evapotranspiration condition though 2002-2004 using more than 200 NOAA AVHRR images per year. The surface energy balance algorithm for land (SEBAL) is used to describe transpiration ability in the main days of crop growing season on various crop types at the field scale using LANDSAT TM and ETM data. And the Penman-Monteith equation is used for integrating the previous high and low resolution ET results to finally estimate the field scale water usage in the whole growing season, which has great benefit to policy-maker for agriculture management. The adaptation of this approach is evaluated over various land cover types at 250 m spatial resolution by analyzing the error between daily ET estimation and in-situ measurements. These comparisons reveal that: considering the underlying complexity in Haihe basin, the ET estimates can be accepted in the vegetation-covered fields after validated by limited scintillometer measurements (24.4% average deviation for daily estimates, and less than 7% for the yearly period), for whole-regional validation, more measurements are needed.
Starting Page	1044
Ending Page	1047
File Size	304358
Page Count	4
File Format	PDF
ISBN	0780395107
DOI	10.1109/IGARSS.2006.269
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Water resources Land surface Sea measurements Equations Energy resolution Remote monitoring Water heating Crops Spatial resolution
Content Type	Text
Resource Type	Article

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