Fusion calculation method of MODIS broadband emissivity and GLASS broadband emissivity

Abstract

The invention provides a fusion calculation method of MODIS broadband emissivity and GLASS broadband emissivity. The method comprises the following steps: firstly, converting MODIS narrow-band emissivity into the MODIS broadband emissivity, respectively fitting the MODIS broadband emissivity and the GLASS broadband emissivity on the basis of a mixed index model, so as to obtain corresponding covariance model coefficients, which include a block variance, a base variance of a first index model and a base variance of a second index model; respectively determining corresponding adjusting operators of the MODIS broadband emissivity and the GLASS broadband emissivity by the obtained block variance, base variance of the first index model and base variance of the second index model; calculating corresponding error covariance models by the adjusting operators; and carrying out a fusion of the MODIS broadband emissivity and the GLASS broadband emissivity by an ideal interpolation algorithm on the basis of the two error covariance models. Compared with a fusion method in the prior art, by the fusion method of the broadband emissivity, a better fusion effect is obtained; and the ideal interpolation has a better application space in fusion of surficial remote sensing products.

Description

technical field [0001] The invention belongs to the technical field of wide-band emissivity fusion, and more specifically relates to a fusion calculation method of MODIS wide-band emissivity and GLASS wide-band emissivity. Background technique [0002] Broadband emissivity refers to the hemispherical integral of emissivity within a certain broadband range. Broadband emissivity is not only one of the important parameters for estimating the surface radiation balance, but also an important input for many surface climate meteorological and hydrological models. However, there are few broadband emissivity products obtained by remote sensing at present, and the accuracy and quality are limited. Remote sensing product fusion can combine multi-source data information to improve product quality. Therefore, it is of great significance to use the method of product fusion to improve the quality of broadband emissivity products. [0003] At present, the fusion of remote sensing product...

AI Technical Summary

Problems solved by technology

For the fusion method, each method has its advantages and disadvantages. Time and ecological filtering are more suitable for products with strong periodicity, but there will also be situations where there is no valid data for several years

The spatial filtering operation is simple, but when the spatial variability is large, the spatial filtering cannot present complex surfaces, because most of the filtering shows a smoothing effect in space

However, spatio-temporal filtering can better combine spatio-temporal characteristics and reconstruct spatio-temporal continuous products, but it is still not the optimal value.

[0004] At present, the ideal interpolation algorithm is used to fuse the emissivity of the broadband method is mainly limited by two factors, one of which is that the error covariance model is difficult to estimate, and the other is that it is difficult to deal with large data

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