Browsing by Author "Hsu, Wei-Chen"

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A STATISTICAL ANALYSIS FOR CHARACTERIZING LANDSLIDE CAUSED BY HEAVY RAINFALL AND SEVERE EARTHQUAKE
(2013)
Chang, Kuan-Tsung
;
Liu, Jin-King
;
Hsu, Wei-Chen
;
Shih, Tian-Yuan
;
土木工程學系
Heavy rainfall and earthquakes are the two major factors inducing landslides in Taiwan. The distribution of area size is the most basic quantitative parameter of landslides. Therefore, the purpose of this study is to characterize the scale and spatial difference of rainfall-induced as compared with those of earthquake-induced landslides. Two representative landslide cases, Toraji typhoon occurred in 200 1 and 921 earthquake occurred in 1 999, are used to analyze the causes of different kinds of landslide disasters in the paper. The test area for the 921 earthquake case is 3700 km(2), the recognized number of landslide in the event is 7279, and total area for the landslides is 1 4766 Ha. Moreover, the maximum area of one landslide is 532 Ha, the average area for the landslides is 2 Ha, and its corresponding standard deviation is 1 3 Ha. In the test case of Toraji typhoon, the total study area is 8847 km(2), the number of landslides is 1 0359, and total area for the landslide is 22305 Ha. The maximum area of a landslide is 232 Ha, the average area for the landslides is 2.2 Ha, and its corresponding standard deviation is 6.2 Ha.
A Study on Factors Affecting Airborne LiDAR Penetration
(2015-04-01)
Hsu, Wei-Chen
;
Shih, Peter Tian-Yuan
;
Chang, Hung-Cheng
;
Liu, Jin-King
;
土木工程學系
This study uses data from different periods, areas and parameters of airborne LiDAR (light detection and ranging) surveys to understand the factors that influence airborne LiDAR penetration rate. A discussion is presented on the relationships between these factors and LiDAR penetration rate. The results show that the flight height above ground level (AGL) does not have any relationship with the penetration rate. There are some factors that should have larger influence. For example, the laser is affected by a wet ground surface by reducing the number of return echoes. The field of view (FOV) has a slightly negative correlation with the penetration rate, which indicates that the laser incidence angle close to zero should achieve the best penetration. The vegetation cover rate also shows a negative correlation with the penetration rate, thus bare ground and reduced vegetation in the aftermath of a typhoon also cause high penetration rate. More return echoes could be extracted from the full-waveform system, thereby effectively improving the penetration rate. This study shows that full-waveform LiDAR is an effective method for increasing the number of surface reflected echoes. This study suggests avoiding LiDAR survey employment directly following precipitation to prevent laser echo reduction.
Land Cover Classification Accuracy Assessment Using Full-Waveform LiDAR Data
(2015-04-01)
Chang, Kuan-Tsung
;
Yu, Feng-Chi
;
Chang, Yi
;
Hwang, Jin-Tsong
;
Liu, Jin-King
The geomorphology of Taiwan is characterized by marked changes in terrain, geological fractures, and frequent natural disasters. Because of sustained economic growth, urbanization and land development, the land cover in Taiwan has undergone frequent use changes. Among the various technologies for monitoring changes in land cover, remote sensing technologies, such as LiDAR, are efficient tools for collecting a broad range of spectral and spatial data. Two types of airborne LiDAR systems exist; full-waveform (FW) LiDAR and traditional discrete-echo LiDAR. Because reflected waveforms are affected by the land object material type and properties, the waveform features can be applied to analyze the characteristics specifically associated with land-cover classification (LCC). Five types of land cover that characterize the volcanic Guishan Island were investigated. The automatic LCC method was used to elucidate the spectral, geomorphometric and textural characteristics. Interpretation keys accompanied by additional information were extracted from the FW LiDAR data for subsequent statistical and separation analyses. The results show that the Gabor texture and geomorphometric features, such as the normalized digital surface model (nDSM) and slopes can enhance the overall LCC accuracy to higher than 90%. Moreover, both the producer and user accuracy can be higher than 92% for forest and built-up types using amplitude and pulse width. Although the waveform characteristics did not perform as well as anticipated due to the waveform data sampling rate, the data provides suitable training samples for testing the waveform feature effects.
LANDSLIDE DETECTION BY INDICES OF LIDAR POINT-CLOUD DENSITY
(2010)
Liu, Jin-King
;
Hsu, Wei-Chen
;
Yang, Mon-Shieh
;
Shieh, Yu-Chung
;
Shih, Tian-Yuan
The deliverables of an airborne LiDAR survey usually include all points, ground points, digital surface models (DSM) and digital elevation models (DEM). Indices of point clouds tested in this study include density of all points, density of ground points, density of only returns, and density of multiple returns. Shallow landslides are the most common landslides triggered by torrential rainfalls and explicit fresh scars after rainfall events. Multiple returns in forest area give the possibility of differentiating landslide scars from vegetated lands. Classification results from the indices derived from these four kinds of densities are verified by the result obtained by manual interpretation of the derived nDSM images. The experiment is carried out using the dataset obtained in I-Lan County after Typhoon Kalmaegi on 17 July 2008. The results show that a proper definition of the parameters for the indices is most critical for the detection of shallow landslides.
Observing Land Subsidence and Revealing the Factors That Influence It Using a Multi-Sensor Approach in Yunlin County, Taiwan
(2015-06-01)
Hsu, Wei-Chen
;
Chang, Hung-Cheng
;
Chang, Kuan-Tsung
;
Lin, En-Kai
;
Liu, Jin-King
Land subsidence is a worldwide problem that is typically caused by human activities, primarily the removal of groundwater. In Western Taiwan, groundwater has been pumped for industrial, residential, agricultural, and aquacultural uses for over 40 years. In this study, a multisensor monitoring system comprising GPS stations, leveling surveys, monitoring wells, and Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) was employed to monitor land subsidence in Western Taiwan. The results indicate that land subsidence in Yunlin County was mainly affected by the compaction of subsurface soils and over-pumping of groundwater from deep soils. The study area comprised western foothills, characterized by sediments containing predominantly gravel, and coastal areas, where clay was predominant. The subsidence in coastal areas was more severe than that in the western foothills, as a result of groundwater removal. An additional factor affecting subsidence was the compaction of deep layers caused by deep groundwater removal and the deep-layer compaction was difficult to recover. Based on multisensor monitoring results, severe subsidence is mainly affected by compaction of subsurface soils, over-pumping of groundwater from deep soils, and deep soil compaction.