Simulation method for remote sensing data under arbitrary spectral response characteristic

Abstract

The invention discloses a simulation method for remote sensing data under arbitrary spectral response characteristic, and belongs to the technical field of earth observation. In the method, the input hyperspectral data is subjected to iteration decorrelation, and hyperspectral data with improved spectral resolution is acquired; and the hyperspectral data with the improved spectral resolution is sampled according to the spectral response characteristic to be simulated, and hyperspectral or multispectral data under the spectral response characteristic to be simulated is acquired. The simulation method can be used for simulating the hyperspectral or multispectral data with arbitrary central wavelength position, arbitrary spectral resolution or arbitrary shape spectral response function by the existing hyperspectral data, and has higher accuracy of simulating data than the conventional spectral interpolation method and wave-band synthesis method so as to contribute to improving radiometric cross-calibration accuracy and data comparison and verification accuracy of a hyperspectral remote sensor.

Description

A Simulation Method of Remote Sensing Data with Arbitrary Spectral Response technical field The invention relates to a simulation method of remote sensing data under arbitrary spectral response characteristics, belongs to the technical field of earth observation, and is a remote sensing data processing technology. Background technique The spectral response characteristics of the remote sensor are described by the set of spectral response functions of all bands. The central wavelength and spectral resolution of the bands commonly used in remote sensing are the peak wavelength and full width at half maximum of the spectral response functions of the bands, respectively. All optical remote sensing data are the result of weighted average sampling of continuous spectral signals in the real world by the remote sensor with its spectral response function. Because different remote sensors have different spectral response characteristics, even if the same area is observed at the same...

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Problems solved by technology

These two types of methods are generally used to simulate hyperspectral data and multispectral data from hyperspectral data respectively; and they do not consider the weighted average effect corresponding to the spectral resolution of the hyperspectral data source itself, causing the accuracy of the simulated data to be affected by the hyperspectral data. The spectral resolution of the source is restricted, and the accuracy is not high when the spectral resolution of the data to be simulated is similar to that of the hyperspectral data source

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