Fusion calculation method of modis broadband emissivity and glass broadband emissivity

Abstract

The invention provides a fusion calculation method of MODIS wide-band emissivity and GLASS wide-band emissivity. First, the MODIS narrow-band emissivity is converted into MODIS wide-band emissivity, and then the MODIS wide-band emissivity and the GLASS wide-band emissivity are calculated. Based on the mixed exponential model, the corresponding covariance model coefficients are respectively fitted, including the basis variance of the first exponential model of the block variance and the basis variance of the second exponential model, and the block variance, the basis variance of the first exponential model and the second exponential model are obtained by using The basis variances are MODIS broadband emissivity and GLASS broadband emissivity, respectively, to obtain the corresponding adjustment operator, use the adjustment operator to calculate the corresponding error covariance model, and then use the ideal interpolation algorithm based on the two error covariance models. Fusion of MODIS and GLASS broadband emissivity. Compared with the fusion method of the prior art, the broadband emissivity obtained by the fusion method has a better fusion effect, so that the ideal interpolation has a better application space in the fusion of surface 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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