河道粒徑大小與分布的調查對於河道流況、輸沙、形態及生態棲地研究至關重要。傳統上粒徑調查方法常以人工調查為主，然而人工方法費時費力，故隨著空拍影像與影像分析技術的快速發展，近年人們開始應用這些新技術來協助進行河道表面泥沙粒徑的調查工作，並且獲得了一定程度的成果。然而這些成果仍然存在許多的差異性，這些差異會影響後續使用者的應用信心。為瞭解無人機空拍與影像分析技術判釋河道泥沙粒徑的應用效果，本研究以南投縣和社溪河道做為研究區域，在研究區域內進行無人機(unmanned aerial vehicle, UAV)空拍調查，同時以傳統方式進行河道泥沙粒徑人工調查。將河道現場空拍所得影像，以運動恢復結構(Structure from Motion, SfM)成像技術，建構河道三維點雲資料。後續用此點雲資料計算出粗糙高度 RH、高程標準偏差σ及去勢化高程標準偏差σd等三種代表河床表面粗糙度的指標。最後將此三種河床表面粗糙度指標的大小及分布，分別與人工採樣所得的河床表面泥沙粒徑大小與分布進行關聯性比對。
結果顯示三種粗糙度指標大小與粒徑大小之間皆有密切的正相關(R2>0.8)，且該關係非單一線性關係式，而是指數關係或是冪次方關係，這種關係反映出河床較小礫石對表面粗糙度的影響高於較大礫石或是巨石對表面粗糙度的影響。本研究也據此成果，透過空拍影像分析及八次現地人工調查分別建構了三種河床表面粗糙度指標(RH、σ及σd)與河床表面粒徑之關係式，並在五個採樣區域使用關係式推估粒徑進行驗證。其結果以RH-粒徑關係式推估之粒徑與現調粒徑呈現高度相關(R2>0.8)，展示了應用空拍影像建構的粗糙度-粒徑關係式推估粗礫石河床表面粒徑分佈具可行性。

To understand the effectiveness of UAV aerial photography and image analysis techniques in indicate riverbed sediment grain sizes, this study selected the Heshe River in Nantou County, Taiwan, as the research area. UAV aerial surveys were conducted within the study area, alongside traditional manual surveys of riverbed sediment grain sizes. The images obtained from the field surveys were used to construct three-dimensional point cloud data of the riverbed using Structure from Motion (SfM) imaging techniques. This point cloud data was used to calculate three metrics representing riverbed surface roughness: roughness height (RH), elevation standard deviation (σ), and detrended elevation standard deviation (σd). The size and distribution of these indicators were compared with those of riverbed sediment grains obtained from manual sampling. The results showed a strong correlation (R2 > 0.8) between the three roughness metrics and grain size, indicating exponential or power law relationships rather than simple linear ones. Smaller gravel had a greater impact on surface roughness than larger gravel or boulders. Based on these findings, relationships between the roughness metrics (RH, σ, and σd) and grain size were constructed using aerial image analysis and eight field surveys, and validated in five sampling areas. The RH-grain size relationship showed the highest correlation (R2 > 0.8) with the measured grain size, demonstrating the feasibility of using aerial images to construct roughness-grain size relationships for estimating the surface grain size distribution of coarse gravel riverbeds.

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