Separating the radiance contribution of land surface and atmosphere

The problem of quantitative remote sensing inversion is ill-posed in essence. In order to turn the inversion problem from uncertainty into certainty, we must try to make full use of all the Information we have. Furthermore, reducing the number of parameters to be inversed is another good way. For thermal inversion, separation of land surface and atmospheric contribution (SAS) to the remote sensing signal is a necessity to both atmosphere research and land surface research. Taking advantage of the spatial information generated from the visible and near infrared spectral bands, we presented an algorithm to get the relative contribution to remote sensing signal (radiance) from land surface and atmosphere. The algorithm is based on the difference of the spatial thermal pattern between land surface and atmosphere. As a result, regressive image and difference image is generated. Regressive image contains the contribution from land surface and homogenous part of atmosphere. It has similar spatial pattern with land surface. And difference image contains the contribution of inhomogenous part of atmosphere. It reflects the spatial pattern of atmosphere. The test with MAS (MODIS Airborne Simulator) data shows that SAS algorithm has the ability to remove the thermal abnormal from the original thermal image. The real test proves that most of chippy cirrus cloud has been removed from the observed radiance and little effect remains in the regressive image. From the study, we can draw a conclusion that visible and near infrared image is helpful to thermal inversion. It also reveals that spatial information is one kind of good information source that should be used in remote sensing inversion.