This paper describes scientific research conducted to highlight the potential of an integrated GPR-UAV system in engineering-geological applications.The analysis focused on the stability of a natural scree slope in th...This paper describes scientific research conducted to highlight the potential of an integrated GPR-UAV system in engineering-geological applications.The analysis focused on the stability of a natural scree slope in the Germanasca Valley,in the western Italian Alps.As a consequence of its steep shape and the related geological hazard,the study used different remote sensed methodologies such as UAV photogrammetry and geophysics survey by a GPR-drone integrated system.Furthermore,conventional in-situ surveys led to the collection of geological and geomorphological data.The use of the UAV-mounted GPR allowed us to investigate the bedrock depth under the detrital slope deposit,using a non-invasive technique able to conduct surveys on inaccessible areas prone to hazardous conditions for operators.The collected evidence and the results of the analysis highlighted the stability of the slope with Factors of Safety,verified in static conditions(i.e.,natural static condition and static condition with snow cover),slightly above the stability limit value of 1.On the contrary,the dynamic loading conditions(i.e.,seismic action applied)showed a Factor of Safety below the stability limit value.The UAV-mounted GPR represented an essential contribution to the surveys allowing the definition of the interface debris deposit-bedrock,which are useful to design the slope model and to evaluate the scree slope stability in different conditions.展开更多
针对传统局部不变特征的景象匹配算法冗余点多、实时性差、抗几何变换不突出的情况,提出基于CenSurE-star的无人机(UAV)景象匹配算法。首先采用Cen Sur E特征星型滤波器(CenSurE-star)提取基准图和实时图中的特征点,并生成FREAK二进制...针对传统局部不变特征的景象匹配算法冗余点多、实时性差、抗几何变换不突出的情况,提出基于CenSurE-star的无人机(UAV)景象匹配算法。首先采用Cen Sur E特征星型滤波器(CenSurE-star)提取基准图和实时图中的特征点,并生成FREAK二进制描述符;然后将汉明距离作为特征点的相似性判定度量,采用K近邻距离比值的方法提取匹配点对;最后利用基于RANSAC的定位模型得到空间几何变换关系,实现图像匹配并获取定位点经纬坐标。算法性能评价实验表明,本文算法不仅相对于SIFT、SURF、ORB算法,对各种变换具有更好的鲁棒性,而且相对于改进的SIFT、SURF算法处理时间有更大程度的缩短,算法定位误差在0.8个像素内,尺度误差在0.02倍内,旋转角度误差在0.04°内。基于算法进行外场飞行实验,实验证明算法定位精度较高,可以适应地貌信息较少的环境,并能满足无人机视觉辅助导航的需求。展开更多
文摘This paper describes scientific research conducted to highlight the potential of an integrated GPR-UAV system in engineering-geological applications.The analysis focused on the stability of a natural scree slope in the Germanasca Valley,in the western Italian Alps.As a consequence of its steep shape and the related geological hazard,the study used different remote sensed methodologies such as UAV photogrammetry and geophysics survey by a GPR-drone integrated system.Furthermore,conventional in-situ surveys led to the collection of geological and geomorphological data.The use of the UAV-mounted GPR allowed us to investigate the bedrock depth under the detrital slope deposit,using a non-invasive technique able to conduct surveys on inaccessible areas prone to hazardous conditions for operators.The collected evidence and the results of the analysis highlighted the stability of the slope with Factors of Safety,verified in static conditions(i.e.,natural static condition and static condition with snow cover),slightly above the stability limit value of 1.On the contrary,the dynamic loading conditions(i.e.,seismic action applied)showed a Factor of Safety below the stability limit value.The UAV-mounted GPR represented an essential contribution to the surveys allowing the definition of the interface debris deposit-bedrock,which are useful to design the slope model and to evaluate the scree slope stability in different conditions.
文摘针对传统局部不变特征的景象匹配算法冗余点多、实时性差、抗几何变换不突出的情况,提出基于CenSurE-star的无人机(UAV)景象匹配算法。首先采用Cen Sur E特征星型滤波器(CenSurE-star)提取基准图和实时图中的特征点,并生成FREAK二进制描述符;然后将汉明距离作为特征点的相似性判定度量,采用K近邻距离比值的方法提取匹配点对;最后利用基于RANSAC的定位模型得到空间几何变换关系,实现图像匹配并获取定位点经纬坐标。算法性能评价实验表明,本文算法不仅相对于SIFT、SURF、ORB算法,对各种变换具有更好的鲁棒性,而且相对于改进的SIFT、SURF算法处理时间有更大程度的缩短,算法定位误差在0.8个像素内,尺度误差在0.02倍内,旋转角度误差在0.04°内。基于算法进行外场飞行实验,实验证明算法定位精度较高,可以适应地貌信息较少的环境,并能满足无人机视觉辅助导航的需求。
