空拍機（UAV）近年來的興起，促使許多遙測相關研究進步，理由為UAV操作簡單，便於研究區域內進行空中拍攝，且拍攝自由度高、容易取得圖資影像。本研究將利用UAV對河川物理棲地結合現地調查，對河道棲地進行探討。

本研究透過現地物理棲地調查，調查時間自2018年1月至3月，地點為屏東縣萬巒鄉之五溝水，調查物理棲地類型包含淺瀨區（Riffle）、淺流區（Glide）與深潭區（Pool），淺瀨區水面流態含有劇烈波紋；深潭區則水面則平滑；淺流區水面則介於淺瀨區與深潭區兩者之間，屬過渡區。研究主要目標有二，（一）透過現地辨識河川物理棲地與調查物理棲地因子特徵，並利用統計方法單因子變異數分析，了解不同棲地之特徵差異性；（二）透過UAV拍攝之空拍圖結合影像處理與紋理分析，並運用最大概似模式進行物理棲地分類。

研究結果顯示利用流速、水深、福祿數與流速水深比等因子中，單因子變異數分析均有顯著差異，而透過事後多重比較法則顯示福祿數最能有效呈現不同棲地之數據差異性。模式分類方面透過分三類物理棲地，總體分類精度達71.95%，Kappa係數為0.526；分兩類棲地（去除淺流區）總體分類精度為83.09%，Kappa係數為0.662。若模式分類應用於五溝水中，分三類棲地顯示淺瀨區占23.15%、淺流區占49.23%、深潭區占27.62%；分兩類棲地顯示淺瀨區占38.97%、深潭區占61.03%。透過空拍圖與模式分類於河道物理棲地之應用，可迅速了解河道棲地內之分佈情形，並提供水生生物間之應用範疇。

Field survey in this paper focuses on Wu Gou Shui, Wanluan Township, Pingtung County. This paper contains two sections. In section 1, survey team identified the physical habitat by surface flow type. The criteria for the assessment were: swiftly flow with a high proportion of its water surface broken as Riffle; smooth water surface as Pool; and a wavy water surface as Glide. Velocity, water depth were measured at each physical habitat, and we analyzed velocity, water depth, Froude number and velocity/depth ratio using ANOVA statistic. In section 2, for mapping physical habitat, we photographed the river image by unmanned aerial vehicle (UAV) and combined image processing with texture analysis. Furthermore, we mapped physical habitat using Maximum-likelihood classification. In statistical analysis, velocity, water depth, Froude number and velocity/depth all showed significant differences on ANOVA. And Froude Number showed the most significant differences on Post hoc test. In classification of model, overall classification accuracy and Kappa coefficient are 71.95% and 0.526 for three types of physical habitat, 83.09% and 0.662 for two types of classification (remove Glide). Physical habitat mapping of the study reach recorded a distribution of 23.15% riffles, 49.23% glides and 27.62% pools in three types of classification, compared with 38.97% riffle and 61.03% in two types of classification. This research can quickly show the distribution of habitat through aerial imagery and model classification, and hope it can also provide application in aquatic environment.

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