Abstract
A new procedure to assess the quality of topographic correction (TOC) algorithms applied to remote sensing imagery was previously proposed by the authors. This procedure was based on a model that simulated synthetic scenes, representing the radiance an optical sensor would receive from an area under some specific conditions. TOC algorithms were then applied to synthetic scenes and the resulting corrected scenes were compared with a horizontal synthetic scene free of topographic effect. This comparison enabled an objective and quantitative evaluation of TOC algorithms. This approach showed promising results but had some shortcomings that are addressed herein. First, the model, originally built to simulate only broadband panchromatic scenes, is extended to multispectral scenes in the visible, near infrared (NIR), and short wave infrared (SWIR) bands. Next, the model is validated by comparing synthetic scenes with four Satellite pour l'Observation de la Terre 5 (SPOT5) real scenes acquired on different dates and different test areas along the Pyrenees mountain range (Spain). The results obtained show a successful simulation of all the spectral bands. Therefore, the model is deemed accurate enough for its purpose of evaluating TOC algorithms.
Highlights
The use of remotely sensed data from mountainous regions generally requires additional pre-processing, including topographic correction (TOC)
The objective of topographic correction algorithms is to compensate the differences in radiance between sunny and shaded areas caused by variations in the slope and aspect of terrain
Satellite pour l'Observation de la Terre 5 (SPOT5) images were converted from digital numbers (DN) to top of atmosphere radiance first, and to ground reflectance later, following the procedure explained in [20]
Summary
The use of remotely sensed data from mountainous regions generally requires additional pre-processing, including topographic correction (TOC). A number of TOC algorithms were proposed in the past (e.g., [1,4,7,8]), but their evaluation is not as simple as it might seem In this sense, several strategies to evaluate TOC algorithms have been developed, i.e., visual assessment of the removal of the topographic effect in satellite imagery [5,9,10,11], quantification of the reduction of the dependence between cosγi and the radiance of each spectral band after the correction [12], analysis of the variations in the radiometry of the corrected scenes [5], measurement of the reduction of land cover class variability [2,13,14], and improvement on classification accuracy after topographic correction [4,11].
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