Feature Information Extraction of Landslide Based on the UAV Big-Slant-Angle Side-Look Image after Earthquake

Abstract:

Unmanned Aerial Vehicle (UAV) remote sensing technology has the real-time ability to obtain ground images at earthquake landslide area. It makes it possible to extract landslide disaster information, support emergency rescue and decrease losses at the first second after earthquake. However, UAV remote sensing is prone to produce images with big-slant-angle. Although it is not fit for object measuring by traditional photogrammetry, it is benefit for observing slope at a better angle and extracting slope characteristics quantitatively. In this research, we define UAV big-slant-angle data as side-look images for earthquake landslide, which is based on an UAV close range photogrammetry idea. Image recognition of earthquake landslide area and three dimensional measuring of slope features will be researched. First of all, a projection datum plane along slope normal will be simulated according to the terrain surface. Appropriate images will be selected by evaluating camera pose and landslide overlapping rate. Secondly, orthogonal rotation matrixes are used to do 3D datum transformation with big-rotation-angle. Settlement of collinearity equations considering big-slant-angle condition will be researched. On this basis, dependent relative orientation among image series will be done to construct a three dimensional side-look-image model. At last, landslide image recognition, slope terrain surface reconstruction and landslide feature measurement is considered to cover the contents of earthquake landslide information extraction. Structural features and combined features can be analyzed and calculated on this basis. A rigorous solution of forward intersection in close range photogrammetry with big-slant-angle will be researched. Slope feature geometry and its relationship among images are to be considered to make a credible characteristic matching thinking big-rotation-angle exists. It has potentiality to provide variety landslide information with higher geometrical precision for cartography and risk analysis of earthquake landslide.

• Periodical: Applied Mechanics and Materials (Volumes 373-375)
• Pages: 638-643
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.373-375.638
• Online since: August 2013
• Authors: Zhuo Wei Hu, Lai Wei, Qian Zhang
• Keywords: Feature Measurement, Information Extraction, Landslide, Side-Look Image, UAV

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