
Proceedings Paper
Study on the late frost monitoring technology for winter wheat by EOS/MODIS dataFormat | Member Price | Non-Member Price |
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Paper Abstract
Retrieving land-surface temperature with split-window algorithm was firstly applied to NOAA-AVHRR data.
With the application of MODIS sensor, its data has been used more and more widely. Since MODIS sensor is able
to observe vapor in the air, it can provide the parameters including vapor content and atmospheric transmissivity
for split-window algorithm which can thus be applied more conveniently. The article, adopting the split-window
algorithms of Becker-Li (1990), Sobrino (1991) and Qin Zhihao (2005), retrieves the surface temperature at
daytime and nighttime with MODIS1B data and compares with the surface temperature products of NASA. Finally,
the algorithm of Qin Zhihao is demonstrated to be the one with higher accuracy at daytime and nighttime and the
algorithm for surface temperature at nighttime is simple with acceptable accuracy.
Paper Details
Date Published: 2 October 2008
PDF: 14 pages
Proc. SPIE 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X, 710415 (2 October 2008); doi: 10.1117/12.797806
Published in SPIE Proceedings Vol. 7104:
Remote Sensing for Agriculture, Ecosystems, and Hydrology X
Christopher M. U. Neale; Manfred Owe; Guido D'Urso, Editor(s)
PDF: 14 pages
Proc. SPIE 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X, 710415 (2 October 2008); doi: 10.1117/12.797806
Show Author Affiliations
Xuefen Zhang, Meteorological Observation Center of CMA (China)
Liang Sun, Beijing Normal Univ. (China)
LRSS (China)
Beijing Key Lab. of Environmental Remote Sensing (China)
Rui Sun, Beijing Normal Univ. (China)
LRSS (China)
Beijing Key Lab. of Environmental Remote Sensing (China)
Liang Sun, Beijing Normal Univ. (China)
LRSS (China)
Beijing Key Lab. of Environmental Remote Sensing (China)
Rui Sun, Beijing Normal Univ. (China)
LRSS (China)
Beijing Key Lab. of Environmental Remote Sensing (China)
Published in SPIE Proceedings Vol. 7104:
Remote Sensing for Agriculture, Ecosystems, and Hydrology X
Christopher M. U. Neale; Manfred Owe; Guido D'Urso, Editor(s)
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