HJ-1B satellite intermediate infrared and thermal infrared channel-combined surface temperature inversion method

Abstract

The invention belongs to the quantitative remote sensing technical field and relates to an HJ-1B satellite intermediate infrared and thermal infrared channel-combined surface temperature inversion method. The method includes the following steps that: (1) satellite image data are preprocessed, so that satellite entrance pupil radiation brightness data, atmospheric water vapor content and aerosol optical thickness are obtained; (2) multi-dimensional parameter search table-based intermediate infrared surface reflection solar radiation inversion is constructed, so that an intermediate infrared surface reflection solar radiation inversion product can be obtained; (3) surface emissivity inversion is performed through using the empirical statistic relation of vegetation coverage and surface emissivity, so that the surface emissivity can be obtained; and (4) surface temperature inversion is performed on intermediate infrared data and thermal infrared data through suing the atmospheric water vapor content in the step (1) and the surface emissivity in the step (3), so that a surface temperature inversion product can be obtained. With the method adopted, the utilization of data is effectively improved, the problem of the instability of surface temperature inversion is solved, and the accuracy of temperature inversion is improved.

Description

technical field [0001] The invention relates to the technical field of quantitative remote sensing, in particular to a ground surface temperature inversion method combining mid-infrared and thermal infrared channels of an HJ-1B satellite. Background technique [0002] Surface temperature remote sensing retrieval has always been a hotspot and difficulty in quantitative infrared remote sensing research. At present, the combined surface temperature retrieval algorithm of thermal infrared (8 μm-14 μm) and mid-infrared (3 μm-5 μm) is mainly based on temperature-independent spectral index algorithm, day and night algorithm, Mid-infrared and thermal infrared multi-channel land surface temperature retrieval algorithm based on mid-infrared sun angle correction factor. Both the temperature-independent spectral index algorithm and the day-night algorithm require the matching data of the mid-infrared and thermal infrared channels for day and night, which is very inconvenient; the mid-in...

AI Technical Summary

Problems solved by technology

Both the temperature-independent spectral index algorithm and the day-night algorithm require the matching data of the mid-infrared and thermal infrared channels for day and night, which is very inconvenient; the mid-infrared and thermal infrared multi-channel surface temperature inversion algorithm for the mid-infrared sun angle correction factor takes into account However, this method is difficult to accurately remove the influence of mid-infrared surface reflected solar radiation, and the accuracy of the inversion model is low. Therefore, when the mid-infrared and thermal infrared channels are combined with surface temperature inversion, it is necessary to solve atmospheric correction, solar radiation, and surface specific radiation. Rate inversion and surface temperature inversion problems

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