Browsing by Author "PAI-HUI HSU"

Because of the precipitous terrain and short rapid rivers in Taiwan, the landslides usually happen after heavy rains and the resulting floods. Landslides are natural hazards that often cause series property damages and even life losses. This makes the landslide monitoring and mitigation techniques an important study issue for the related professional disciplines in Taiwan. Wtih the development of remote sensing technology, both the spatial and spectral resolution of satellite images become more mature for objection identification and detection. In this paper, the landslide areas are detected using the pre- and post-images by the decision trees classifier. Firstly, the thresholding method according to the variety of Normalized Difference Vegetation Index (NDVI) is used to remove the vegetation areas. Then, a supervised classifier is used to distinguish the river zones from the bare lands and identify different types of landslides. Finally, based on the spatial analysis of digital terrain model (DTM) using GIS technology, more information about the landslide areas can be integrated according to the geometric characteristics of the terrain such, as the slope, aspect and watershed analysis. The detected landslide information could be utilized as a reference for the mitigation of the future landslide hazards.

© 2018 IEEE. In this study, an accelerating method of oriented FAST and rotated BRIEF combined with principal component analysis (ORB/PCA) is proposed for splicing detection of unmanned aerial vehicle (UAV) images. Compared to traditional scale-invariant feature transform (SIFT) and speeded up robust features (SURF) methods, the proposed ORB/PCA can not only be faster but also produce more accurate. Moreover, in order for the proposed ORB to be effective for image stitching process in near real-time, the Compute Unified Device Architecture (CUDA) application programming interface of graphics processing unit (GPU) is cooperated to speed up the proposed method. Experimental results show that the proposed GPU based ORB/PCA framework is suitable for splicing detection of UAV images in Earth remote sensing. It can improve the image stitching process both in time and accuracy compared to conventional methods.