Title :
The Geomorphometry of Rainfall-Induced Landslides in Alishan Area Obtained by Airborne Lidar and Digital Photography
Author :
Liu, Jin-King ; Shih, Tian-Yuan ; Liao, Zu-Yi ; Lau, Chi-Chung ; Hsu, Pai-Hui
Author_Institution :
Dept. of Civil Eng., NCTU, Hsinchu
Abstract :
For understanding the distribution of slope angles, OHM and roughness of the rainfall-induced landslides in Alishan Area of Central Taiwan, a survey was carried out with airborne Lidar and aerial digital camera to obtain DEM and DSM of 1 m grid and color orthophotos of 50 cm grid. DEM, DSM and orthophotos are georeferenced and co-registered. The 106 landslide polygons derived from photo-interpretation are used for extracting slopes, OHM and roughness. Results show that the average slope angle of landslides is 41 degrees with a standard deviation of 14 degrees; average OHM is 4.4 m with a standard deviation of 6.3 m; average roughness is 2.05 m with a standard deviation of 2.56 m. It is also observed that scale effects are obvious for roughness but not for slope and OHM when the grid is larger than 40 m, which is the average dimension of landslides. These morphometric parameters can be further applied in the automation of landslide inventory.
Keywords :
airborne radar; data acquisition; digital elevation models; geomorphology; geophysics computing; image sensors; object recognition; optical radar; photogrammetry; rain; remote sensing; Alishan area; Central Taiwan; DEM; DSM; OHM; aerial digital camera; airborne lidar; data acquisition; data preprocessing; digital elevation model; digital photography; digital surface model; geomorphometry; landslide classification; landslides; object height model; object-oriented expert system; orthophoto; photo-interpretation; rainfall; shaded-relief image; surface roughness; visual interpretation; Cities and towns; Civil engineering; Clouds; Digital cameras; Digital elevation models; Digital photography; Global Positioning System; Laser radar; Terrain factors; Vegetation mapping; Image shape analysis; Natural disaster; Object recognition; remote sensing;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-2807-6
Electronic_ISBN :
978-1-4244-2808-3
DOI :
10.1109/IGARSS.2008.4779221