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Proceedings Paper

The transpiration and the spectral response of non-irrigated Haloxylon ammodendron at canopy scale
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Paper Abstract

Transpiration, an essential component of surface evapotranspiration, is particularly important in the research of surface evapotranspiration in arid areas. The paper explores the spectral information of the arid vegetal evapotranspiration from a semi-empirical perspective by the measured data and the up-scaling method. The paper inverted the transpiration of Haloxylon ammodendronat at the canopy, pixel and regional scales in the southern edge of the Gurbantunggut desert in Xinjiang, China. The results are as follows: At the canopy scale, the optimal exponential model of the sap flow based on the hyperspectrum is Y = 3.65× SR(1580,1600) + 0.76, R2 = 0.72. At the pixel scale, there was a good linear relationship between the sap flow and the SR index, with a linear relationship of Y = 0.0787 X - 0.0724, R2 = 0.604. At the regional scale, based on the optimal exponential model and the EO-1 Hyperion remote sensing data, the transpiration of the study area was inverted. Comparing the results of the SEBAL and SEBS models, the errors of the simulation results were 12.66% and 11.68%. The paper made full use of the knowledge flow at different scales, bridging the scale difference in canopy and remote sensing images to avoid the information bottleneck in the up-scaling. However, there is much limit in the data acquirement, the endmembers determine, the temporal-spatial up-scaling, and the accuracy assessment to be improved in the future studies.

Paper Details

Date Published: 24 October 2012
PDF: 7 pages
Proc. SPIE 8513, Remote Sensing and Modeling of Ecosystems for Sustainability IX, 85130M (24 October 2012); doi: 10.1117/12.928275
Show Author Affiliations
Xiao-ming Cao, Institute of Geographical Sciences and Natural Resources Research (China)
Juan-le Wang, Institute of Geographical Sciences and Natural Resources Research (China)
Zhiqiang Gao, Institute of Geographical Sciences and Natural Resources Research (China)
Colorado State Univ. (United States)
Yantai Institute of Coastal Zone Research (China)
Mao-si Chen, Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 8513:
Remote Sensing and Modeling of Ecosystems for Sustainability IX
Wei Gao; Thomas J. Jackson, Editor(s)

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