Soil moisture site data upscaling method based on Bayesian theory

A Bayesian theory, soil moisture technology, applied in the field of upscaling of soil moisture site data based on Bayesian theory, to achieve the effect of reducing uncertainty
CN104573393AInactive Publication Date: 2015-04-29BEIJING NORMAL UNIVERSITY
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING NORMAL UNIVERSITY
Publication Date
2015-04-29
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The invention discloses a soil moisture site data upscaling method based on the Bayesian theory. The soil moisture site data upscaling method includes steps of estimating prior probability density distribution function pre_pdf of a target variable on the basis of sparse site observation data in an upscaling area; inversing MODIS ATI into SM by establishing nonlinear regression relation between the SM and the MODIS ATI, estimating an estimated confidence interval of the soil moisture nonlinear regression and probability distribution as soft data in a probability form; integrating the prior distribution of the target variable and auxiliary information of the probability form from the MODIS ATI through the Bayesian theory, and acquiring posterior probability density distribution function post_pdf of the target variable; calculating the value of the target variable in the maximum probability through maximization of the posterior probability distribution function. By the soil moisture site data upscaling method, uncertainties caused by scale difference between soil moisture remote sensing products and ground site authentication data are effectively reduced. The soil moisture site data upscaling method can be applied to upscaling application of other ground surface parameters.
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Description

technical field

[0001] The invention relates to the field of navigation remote sensing, in particular to a method for upscaling soil moisture site data based on Bayesian theory. Background technique

[0002] The problem of scale is a huge obstacle to the full use of multi-source soil moisture data. The problem of scale mismatch not only exists in the multi-channel observation process of soil moisture, but also exists in various related fields such as soil moisture simulation and data assimilation. Low-resolution soil moisture products (SMAP is about 100km 2 , SMOS is about 1600km 2 , etc.) are also limited by scale factors, which originate from the scale difference between satellite sensor resolution and point observations from ground-based instruments. In addition, strictly speaking, the scale of point observations (support area less than 1m 2 ) also does not match the scale of the model grid (support area greater than 10m 2 ), the scale transformation between soil mois...

Claims

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