Construction of Drought Indices Based on Passive Microwave Remote Sensing AMSR-E Data over Huaihe River Basin

2013 ◽  
Vol 433-435 ◽  
pp. 1813-1816
Author(s):  
Jing Wen Xu ◽  
Peng Wang ◽  
Jun Fang Zhao ◽  
Shuang Liu
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
River Basin ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Impact Factors ◽  
Drought Indices ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Passive Microwave Remote Sensing

On the basis of previous work, this paper aims to build several proper drought indices based on the basic computation for the band information of passive microwave remote sensing AMSR-E data in Huaihe river basin. Compared with measured soil moisture, optimal drought indices have been selected to explore the spatio-temporal variation laws of drought conditions and its impact factors. The results indicate that there are satisfactory negative correlations between MPDIs (Microwave Polarization Difference Index) and observed soil moisture on the whole, which means the more negative the index is, the more serious the drought will be. Besides, MPDIs at frequency 69GHz and 187GHz calculated by AMSR-E brightness temperature data are much closer to the variation trend of soil moisture than those obtained from other bands.

Construction of Drought Indices from Passive Microwave Remote Sensing AMSR-E Data in Huaihe River Basin

2013 ◽  
Vol 397-400 ◽  
pp. 2503-2506
Author(s):  
Rui Wang ◽  
Jing Wen Xu ◽  
Dan Wang ◽  
Xing Mei Xie ◽  
Peng Wang
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
River Basin ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Drought Indices ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Passive Microwave Remote Sensing ◽  
Spatio Temporal

On the basis of previous work, this paper aims to build several proper drought indices based on passive microwave remote sensing AMSR-E data in Huaihe River Basin. Compared with measured soil moisture, optimal drought indices have been selected to explore the spatio-temporal variation of drought conditions. The results indicate that there are satisfactory negative correlations between MPDIs (Microwave Polarization Index) and observed soil moisture. Moreover, MPDIs calculated by bands of 69GHz and 187GHz are much closer to variation trend of soil moisture than those obtained by other bands.

Soil Moisture Inversion Based on AMSR-E and MODIS Data Fusion: A Case Study of Huaihe River Basin

2014 ◽  
Vol 716-717 ◽  
pp. 1064-1067
Author(s):  
Jing Wen Xu ◽  
Yu Peng Wang ◽  
Jun Fang Zhao ◽  
Fei Yu Pu ◽  
Peng Wang
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Data Fusion ◽  
River Basin ◽  
Surface Condition ◽  
Remote Sensing Data ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Sensing Data ◽  
Modis Data

In this paper, the correlation between fused data and original data, the measured soil and the precipitation data over Huaihe river basin by exploring the inversion of soil moisture from the time and space based on the method of multi-source remote sensing data fusion has been studied. In order to fuse the AMSR-E data which is all-day and all-weather and can penetrate the earth surface to some extent, with the MODIS data that can reflect the surface condition and temperature characteristics, the method of wavelet fusion was carried out in MATLAB. The conclusions of this study are listed as follows: (1) the inversion result of the fused data based on AMSE-E and MODIS is much better than a single remote sensing data inversion; (2) the fused data based on AMSE-E and MODIS is sensitive to soil moisture change trend when the seasons alternated every year, especially in the spring, summer and autumn.

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