Radiometric-topographic normalization in mountainous terrain for Landsat-TM-based forest parameter assessment by the kNN method

摘要

The kNN method of combining a terrestrial forest inventory with remote sensing image analysis is applied in mountainous terrain. This poses problems of radiometric-topographic normalization, which are addressed in this paper. The SCS (sun-canopy-sensor) method, extended for including diffuse sky radiation, is found to be particularly suited for this. Estimating parameters of radiometric-topographic correction algorithms (such as the ratio of direct sun radiation and diffuse sky radiation in case of the extended SCS method) from the image itself by regression of forest pixels arbitrarily selected at different topographic conditions relies on the assumption that the forest pixels selected at different irradiation conditions represent (in the statistical average) identical forest conditions. This assumption can hardly be proved to be valid. The estimation of this ratio by tuning within the kNN cross-validation procedure, on the other hand, represents a sound method, making use of the large amount of forest information available from terrestrial forest inventories. The practicability of this method depends on the number and thematic distribution of field plots on one single scene, for which homogenous atmospheric conditions can be assumed.