以ADS-40數值多光譜航照影像萃取陰影與非陰影區域崩塌地之研究

Automatic Extraction of Shadow and Non-shadow Landslide Area from ADS-40 Digital Aerial Photographs

廖晟淞(Cheng-Sung Liao)

指導教授 ： 鍾玉龍 ； 邱亞伯

國立屏東科技大學/農學院/熱帶農業暨國際合作系所/碩士(2012年)

https://doi.org/10.6346/NPUST.2012.00149

摘要

航遙測光學影像為崩塌地自動判釋的主要技術之一，但由於影像容易受陰影干擾，導致判釋成果不佳，本研究的主要目的為利用ADS-40數值多光譜航照影像，探討陰影區域與非陰影區域之崩塌地判釋情形，建立快速準確的崩塌地萃取方法，以利於未來崩塌地之監策與管理。本研究以濁水溪上游為研究樣區，將影像區分為陰影區與非陰影區分別進行分析，逐一濾除植生區域與坡度門檻，以分層分類的概念萃取崩塌地，藉此提升崩塌地判釋之準確度。另外嘗試對陰影區域以直方圖匹配(Histogram Matching)與線性相關校正(Linear-Correlation Correction)進行陰影恢復。研究結果顯示，陰影影像具有一定的分類能力，直方圖匹配與線性相關校正雖然對DN 值(Digital Number)具有良好的恢復能力，但是對分類效果不大；而由於非陰影區域去除了陰影的干擾，因此具有良好的分類能力。以坡度25°及15°分別濾除非植生部分之河道，其崩塌地分類結果總體精度分別為83.07%、94.42%，Kappa 統計值0.6204、0.8859；另外，本研究針對非陰影區加入紋理資訊GLCM 平均值進行分類，並以坡度25°保留河道，最後以非植生區域濾除25°以下河道，其崩塌地分類成果Kappa 值提升為0.9162，總體精度為95.92%。

關鍵字

陰影恢復 ； 最大概似法 ； ISODATA 分類法 ； 崩塌地

並列摘要

Remote sensing image is usually used for the detection of landslide locations in disaster monitoring. However, the presence of shadows often disturbs image information, easily affecting classification of the results. Therefore, the objective of this study are to analyze landslide areas on shaded and non-shaded conditions, extracted by ADS-40 airborne multispectral image, and to design an effective and fast method for future monitoring and management. This study used the Jhuoshuei river forest working circles as study area. We used stratified classifications, filter vegetation image, and slope thresholds to discard false positive landslides among the several image classes. Moreover, histogram matching and linear-correlation corrections were used to restore shaded images. Results showed that shaded images are also suitable for classification, but that restoration by histogram matching or linear-correlation correction didn’t affect significantly classification results. Because non-shaded images don’t have shadow interference, non-shaded areas demonstrated good classification ability. In this study, slopes of 25° and 15°demonstrated higher accuracy for landslide detection on shaded and non-shaded areas, respectively. At these slopes, Kappa values of classification were 0.6204 and 0.8859, and overall accuracy were 83.07% and 94.42%, respectively. Finally, after subsuming the mean of textures into analysis of the non-shaded area, the Kappa value and overall classification accuracy increased to 0.9162 and 95.92%, respectively.

並列關鍵字

shadow restoration ； maximum likehood classifier ； ISODATA classifier ； landslide

參考文獻

李訢卉、陳良健 (2008) 整合房屋、道路及地型模型之航空影像真實正射校正。航測及遙測學刊13(2): 101-116。

林才添、鄭祈全、王素芬 (2010) 遙測技術於台北市土地覆蓋變遷之研究。航測及遙測學刊，15(2): 141-153。

陳良健、溫仁佑 (2006) 高解析力衛星影像真實正射改正及遮蔽區域補償。航測及遙測學刊11(3): 249-260。

黃雅莉 (2011) 高屏溪流域國有林崩塌地之變遷與植生恢復。國立屏東科技大學森林系碩士論文，96頁。

董炤巖 (2010) 以物件導向分類法進行SPOT衛星影像之崩塌地萃取。國立屏東科技大學森林系碩士論文，72頁。