Publication Date:
2018-11-06
Description:
Remote sensing soil moisture is one of the important indexes for monitoring agricultural drought in large scale farmland area. The time series length and update speed of remote sensing data have been the important factors restricting their application. Because of the difference between the sensor and the inversion method, remote sensing data from different sources cannot be directly compared and analysed. Therefore, data fusion becomes a hotspot of research interest and key issue in the application of remote sensing data nowadays. Based on cumulative distribution matching principle, Lagrange interpolation can establish this correlation between any quantile on different cumulative probability distribution curves. Based on the above, a continuous fusion algorithm of multi-source remote sensing soil moisture is built in this study. Using this new fusion method, SMOS and CCI data are fused to real-time remote sensing soil moisture data product with long time series. The verification...
Print ISSN:
1755-1307
Electronic ISSN:
1755-1315
Topics:
Geography
,
Geosciences
,
Physics
