An atmospheric correction algorithm for thermal infrared multispectral data over land-a water-vapor scaling method

Abstract

Thermal infrared (TIR) multispectral data over land can be atmospherically corrected by radiative transfer calculations combined with global assimilated data from a weather forecast system. This approach is advantageous to operational processing but is not accurate. A new atmospheric correction algorithm with global assimilated data, a water vapor scaling (WVS) method, has improved results. In this algorithm, the accuracy of global assimilated data is markedly improved on a pixel-by-pixel basis as follows: (1) selecting gray pixels from an image; (2) estimating the scaling factors for the water-vapor profiles of gray pixels by an improved multichannel algorithm; (3) estimating the scaling factors for the water-vapor profiles of nongray pixels by horizontal interpolation; and (4) improving the water-vapor profiles of all pixels with the scaling factors. The proposed method can be applied if the image has one or more gray pixels. The simulation results for the advanced spaceborne thermal emission and reflection radiometer (ASTER) TIR subsystem show that the proposed method reduces errors on air temperature profiles as well as on water-vapor profiles and is as accurate as atmospheric correction with radiosonde measurements.