Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-1/C22, 195-200, 2011
© Author(s) 2011. This work is distributed
under the Creative Commons Attribution 3.0 License.
06 Sep 2012
J. Y. Rau1, J. P. Jhan1, C. F. Lo2, and Y. S. Lin2 1Department of Geomatics, National Cheng Kung University, Tainan City 701, Taiwan
2Geosat Informatics & Technology Co., Tainan City 701, Taiwan
Keywords: UAV, Mapping, Landslides Detection Abstract. In Taiwan, the average annual rainfall is about 2,500 mm, about three times the world average. Hill slopes where are mostly under meta-stable conditions due to fragmented surface materials can easily be disturbed by heavy typhoon rainfall and/or earthquakes, resulting in landslides and debris flows. Thus, an efficient data acquisition and disaster surveying method is critical for decision making. Comparing with satellite and airplane, the unmanned aerial vehicle (UAV) is a portable and dynamic platform for data acquisition. In particularly when a small target area is required. In this study, a fixed-wing UAV that equipped with a consumer grade digital camera, i.e. Canon EOS 450D, a flight control computer, a Garmin GPS receiver and an attitude heading reference system (AHRS) are proposed. The adopted UAV has about two hours flight duration time with a flight control range of 20 km and has a payload of 3 kg, which is suitable for a medium scale mapping and surveying mission. In the paper, a test area with 21.3 km2 in size containing hundreds of landslides induced by Typhoon Morakot is used for landslides mapping. The flight height is around 1,400 meters and the ground sampling distance of the acquired imagery is about 17 cm. The aerial triangulation, ortho-image generation and mosaicking are applied to the acquired images in advance. An automatic landslides detection algorithm is proposed based on the object-based image analysis (OBIA) technique. The color ortho-image and a digital elevation model (DEM) are used. The ortho-images before and after typhoon are utilized to estimate new landslide regions. Experimental results show that the developed algorithm can achieve a producer's accuracy up to 91%, user's accuracy 84%, and a Kappa index of 0.87. It demonstrates the feasibility of the landslide detection algorithm and the applicability of a fixed-wing UAV for landslide mapping.
Conference paper (PDF, 1538 KB)

Citation: Rau, J. Y., Jhan, J. P., Lo, C. F., and Lin, Y. S.: LANDSLIDE MAPPING USING IMAGERY ACQUIRED BY A FIXED-WING UAV, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-1/C22, 195-200, doi:10.5194/isprsarchives-XXXVIII-1-C22-195-2011, 2011.

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