A new airborne river surface flow measurement technique is presented, called Airborne Feature Matching Velocimetry (AFMV). It uses matchings of characteristic image features for orthorectification and velocimetry. Riparian matching points with an arbitrarily chosen base image serve to find individual projective transformation matrices to stabilize airborne video recordings. Transformed matching points’ distances of feature shifts between subsequent video frames lead to surface velocity vectors. To test this approach, a riverine moving water surface was recorded by an airborne video camera. Results are compared to (i) image frames rectified by 3D photogrammetry and (ii) related velocimetry results obtained by Particle Image Velocimetry (PIV). Generally, both time averaged and instantaneous surface velocities obtained by AFMV are shown to be of almost equal quality to the PIV approach. AFMV gives slightly less spatially-dense results in poorly textured areas, but clearly outperforms the 3D photogrammetry reference method in relation to computational power. Thus, the new method bears the potential to provide almost real-time instantaneous airborne river surface flow measurements.

提出了一种新的空中河流表面流量测量技术，称为空中特征匹配测速 (AFMV)。它使用特征图像特征的匹配进行正射校正和测速。带有任意选择的基础图像的河岸匹配点用于找到单独的投影变换矩阵以稳定机载视频记录。转换后的匹配点在后续视频帧之间的特征偏移距离导致表面速度向量。为了测试这种方法，机载摄像机记录了河流移动的水面。结果与 (i) 通过 3D 摄影测量校正的图像帧和 (ii) 通过粒子图像测速 (PIV) 获得的相关测速结果进行比较。一般来说，通过 AFMV 获得的时间平均和瞬时表面速度都显示出与 PIV 方法几乎相同的质量。AFMV 在纹理较差的区域给出的空间密度略低，但在计算能力方面明显优于 3D 摄影测量参考方法。因此，新方法有可能提供几乎实时的瞬时空中河流表面流量测量。