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首页> 外文期刊>ISPRS International Journal of Geo-Information >Topographic Correction to Landsat Imagery through Slope Classification by Applying the SCS + C Method in Mountainous Forest Areas
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Topographic Correction to Landsat Imagery through Slope Classification by Applying the SCS + C Method in Mountainous Forest Areas

机译：应用SCS + C方法对山地林地进行坡度分类的Landsat影像地形校正

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摘要

The aim of the topographic normalization of remotely sensed imagery is to reduce reflectance variability caused by steep terrain and thus improve further processing of images. A process of topographic correction was applied to Landsat imagery in a mountainous forest area in the south of Mexico. The method used was the Sun Canopy Sensor + C correction (SCS + C) where the C parameter was differently determined according to a classification of the topographic slopes of the studied area in nine classes for each band, instead of using a single C parameter for each band. A comparative, visual, and numerical analysis of the normalized reflectance was performed based on the corrected images. The results showed that the correction by slope classification improves the elimination of the effect of shadows and relief, especially in steep slope areas, modifying the normalized reflectance values according to the combination of slope, aspect, and solar geometry, obtaining reflectance values more suitable than the correction by non-slope classification. The application of the proposed method can be generalized, improving its performance in forest mountainous areas.
机译：遥感影像的地形归一化的目的是减少陡峭地形造成的反射率变化，从而改善影像的进一步处理。对墨西哥南部山区森林地区的Landsat影像进行了地形校正处理。使用的方法是Sun Canopy Sensor + C校正（SCS + C），其中C参数是根据研究区域的地形坡度分类（每个频带分为9类）以不同的方式确定的，而不是使用单个C参数每个乐队。根据校正后的图像对归一化反射率进行比较，视觉和数值分析。结果表明，通过坡度分类进行的校正可以改善阴影和浮雕的消除效果，尤其是在陡坡地区，可以根据坡度，坡向和太阳几何形状的组合修改归一化的反射率值，从而获得比通过非坡度分类进行校正。可以推广该方法的应用，提高其在森林山区的性能。

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