A Method for Retrieving Soil Moisture

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<P ><STRONG style="mso-bidi-font-weight: normal"><FONT face="Times New Roman">A Method for Retrieving Soil Moisture in <ST1:PLACE w:st="on"><ST1:COUNTRY-REGION w:st="on">Tibet</ST1:COUNTRY-REGION></ST1:PLACE> Region By Utilizing Microwave Index from TRMM/TMI Data<P></P></FONT></STRONG></P>
<P ><FONT size=3><FONT face="Times New Roman"><STRONG style="mso-bidi-font-weight: normal">Kebiao Mao</STRONG>, Tang Hua Jun, Zhang Li Xin, Li Man Chun, Guo Ying, Zhao Dengzhong.,<P></P></FONT></FONT></P>
<P ><FONT size=3><FONT face="Times New Roman">According to simulation analysis of the advanced integral equation model (AIEM), there is a good linear relationship between emissivity and soil moisture under conditions of given roughness. The normalized difference of emissivities at 19.35GHz and 10.65GHz with vertical polarization can partly eliminate the influence of roughness and the squared correlation coefficient is about 0.985. This paper uses the normalized brightness temperature for retrieving soil moisture in <ST1:COUNTRY-REGION w:st="on"><ST1:PLACE w:st="on">Tibet</ST1:PLACE></ST1:COUNTRY-REGION> from TRMM/TMI data. This method avoids parametrizing the land surface temperature which is a key parameter for the computation of emissivity. We make some sensitivity analysis for the atmosphere which is the main influence factor for our method. The analysis results indicate that our method is very good for clear days but is not very good when there is rainfall. We evaluate our algorithm by using the ground truth data obtained from GAME <ST1:COUNTRY-REGION w:st="on"><ST1:PLACE w:st="on">Tibet</ST1:PLACE></ST1:COUNTRY-REGION> and the retrieval error of soil moisture is about <ST1:CHMETCNV w:st="on" tcsc="0" numbertype="1" negative="False" hasspace="False" sourcevalue=".04" unitname="m3">0.04m3</ST1:CHMETCNV>m-3 relative to experimental data. The analysis indicates that the relationship obtained from the theoretical model should be revised through the local ground measurement data because the method is still influenced by roughness and vegetation. After making a regression revision, the retrieval error of soil moisture is under <ST1:CHMETCNV w:st="on" tcsc="0" numbertype="1" negative="False" hasspace="False" sourcevalue=".02" unitname="m3">0.02m3</ST1:CHMETCNV>m23. Finally, we retrieve the soil moisture in <ST1:COUNTRY-REGION w:st="on"><ST1:PLACE w:st="on">Tibet</ST1:PLACE></ST1:COUNTRY-REGION> from TRMM/TMI data, and the distribution trend of retrieval results is consistent with the real world.<P></P></FONT></FONT></P>
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<P ><FONT face="Times New Roman"><STRONG style="mso-bidi-font-weight: normal">Kebiao Mao</STRONG>, Tang H. J., Zhang L. X., Li M. C., Guo Y., Zhao D. Z.,  A Method for Retrieving Soil Moisture in Tibet Region By Utilizing Microwave Index from TRMM/TMI Data, International Journal of Remote Sensing, DOI:10.1080/01431160701442104. 2008</FONT>，<FONT face="Times New Roman">29</FONT>（<FONT face="Times New Roman">10</FONT>）：<FONT face="Times New Roman">2905-2925. <P></P></FONT></P>
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<TD class=h vAlign=top align=left>本文引用地址：<a href="http://www.sciencenet.cn/blog/user_content.aspx?id=231325" target="_blank" >http://www.sciencenet.cn/blog/user_content.aspx?id=231325</A> </TD></TR>
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<TD >本文关键词： </TD>
<TD >遥感 土壤水分 被动微波 TMI </TD></TR>
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