Abstracts for the 5th International GAME Conf.
3-5 October 2001
Aichi Trade Center
Nagoya Japan
Remote Sensing Land Surface Wetness by Using of TRMM/TMI Microwave Data
Gu Songyan (1), Zhu Yuanjing (1), Zhao Bolin (1), Zhang Wenjian (1)
(1) Geographics Department of Peking University
Water cycle analysis is the most important part of the project of GEWEX. In water cycle analysis, the land surface wetness information plays an important role. TRMM/TMI is a new kind of microwave image unit, and has a great potential application in land characters analysis, especialy on remote sensing land surface wetness information and monitoring flood area. In our work, the wetness index analysis method was used to analysis the flood area during the summer of 1998 over Boyang and Tongting lake area in China, and we tried to retrieve the land surface emmisivity over the same area to estimate the land surface wetness. To accomplish this, we have analysed the characters of TRMM/TMI channels first by using of VIDSORT model; and then developed a set of wetness indexes by combining three window channels of TRMM/TMI together. We have tried three kind of wetness index, they are
Hf(H)-Lf(H);
(Tbv-Tbh)/( Tbv+Tbh);
a1[Tb(f2)-Tb(f1)]+a2[Tb(f3)-Tb(f2)]
(a1 and a2 is consent)
According to our analysis results, the wetness PR19 and BWI10 are better
than the other indexes. So we use the best wetness indexes (PR19 and BWI10) which is sensitive to the land surface wetness changes to do our flood classification and monitoring. In our Cal./Val. test, the data of China L-SAR aboard on the plane and Canadian Radar-SAR aboard on the Radarsat was used, and we got a 70% to 80% Cal/Val results. At the same time we also have a try to retrieve the surface microwave emisivity from TMI data, just following the concept of BWI. We use the emmisivity product to estimate the land surface wetness, and we also got a good result. Our future work will forcus to investigate the possible improvements to the algorithm and extend testing of the algorithm to other regions.
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