福衛二號影像山區森林影像地形校正：MVECA法

Topographic Normalization of Formosat2-MS Images of Forest in Rugged Terrain: Using the Modification of Variable Empirical Coefficient Algorithm

在山區衛星影像的應用上，針對地形起伏所造成的地形效應進行校正為重要的前處理步驟，其足以影響後續影像分類的品質以及量化的精度。臺灣山地占土地面積的三分之二以上，山地地區的森林光譜輻射強度值受地形效應影響甚大，如能對植被影像進行地形校正，則有助於後續研究量化精度的提升。為克服改進前人校正模式的缺點，本篇研究提出一種新的參考操作模式，基於VECA（Variable Empirical Coefficient Algorithm）以及Minnaert+SCS 修正設想的Modification ofVariable Empirical Coefficient Algorithm（MVECA）修正模式。本研究以相關係數R 值、離散係數、次數分配直方圖等指標評估MVECA 分區與整區影像校正效能。研究結果顯示MVECA 法在無光照陰暗區以及低光照地區較前人模式具有較好的校正效能，且在全區影像校正效能上，與相對入射光cosi 的R 值除藍光段外，皆呈現極低度相關，且離散係數與校正前比較皆有所降低，顯示受地形效應影響大幅降低，證實本研究所提出的MVECA 法具備地形校正的能力。

Topographic correction is a very important approach of pre-process in the remote sensing application in rugged terrain. Without this step, the quantification and classification of the image will be influenced. A new topographic correction approach, the Modification of Variable Empirical Coefficient Algorithm（MVECA）, was developed on the theoretical and statistic analysis of the spectral values of remotely sensed data acquired from the rugged terrain and topographic variables. To prove the approach is practical, the approach was explained and analyzed in comparison with that before topographic correction and other approaches. The test site selected for the study is located on the relatively rugged terrain over the southeastern hill of the Yu Shan Mountain in Taiwan, the remotely sensed data utilized for examining the result of the proposed approach MVECA is Formosat2 image acquired over the test site. Visual comparison, and statistical analysis of corrected image are adopted for feasible evaluation of the proposed algorithm, and the results suggest that the proposed approach MVECA is capable for removing the topographic effects contained in Formosat2 MS image. The result also shows that MVECA has better ability of topographic correction than Minnaert+SCS and SCS+C in the area of the shadowed area and the steep terrain where incident angles may approach 90°.