Browsing by Author "Chang, Chung-Pai"

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Deriving landslide dam geometry from remote sensing images for the rapid assessment of critical parameters related to dam-breach hazards
(2014-02-01)
Dong, Jia-Jyun
;
Lai, Po-Jung
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Chang, Chung-Pai
;
Yang, Sheng-Hsueh
;
Yeh, Keh-Chia
Dam-breaches that cause outburst floods may induce downstream hazards. Because landslide dams can breach soon after they are formed, it is critical to assess the stability quickly to enable prompt action. However, dam geometry, an essential component of hazard evaluation, is not available in most cases. Our research proposes a procedure that utilizes post-landslide orthorectified remote sensing images and the pre-landslide Digital Terrain Model in the Geographic Information System to estimate the geometry of a particular dam. The procedure includes the following three modules: (1) the selection of the reference points on the dam and lake boundaries, (2) the interpolation of the dam-crest elevation, and (3) the estimation of dam-geometry parameters (i.e., the height, length, and width), the catchment area, the volumes of barrier lake and landslides dam. This procedure is demonstrated through a case study of the Namasha Landslide Dam in Taiwan. It was shown the dam-surface elevation estimated from the proposed procedure can approximate the elevation derived from profile leveling after the formation of the landslide dam. Thus, it is feasible to assess the critical parameters required for the landslide dam hazard assessment rapidly once the ortho-photo data are available. The proposed procedure is useful for quick and efficient decision making regarding hazard mitigation.
Monitoring severe aquifer-system compaction and land subsidence in Taiwan using multiple sensors: Yunlin, the southern Choushui River Alluvial Fan
(2010-02-01)
Hung, Wei-Chia
;
Hwang, Cheinway
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Chang, Chung-Pai
;
Yen, Jiun-Yee
;
Liu, Chih-Hsi
During 1992-2007, excessive pumping of ground-water caused large-scale aquifer-system compaction and land subsidence in the Choshui River Alluvial Fan, especially in the area of Yunlin county. The subsidence impedes surface-water runoff and endangers the operation of Taiwan High Speed Rail. Leveling, Global Positioning System (GPS), multi-level compaction monitoring well, and Differential Interferometric Synthetic Aperture Radar (DInSAR) are used to study the extent of subsidence in Yunlin and its mechanism. These sensors complement each other in spatial and temporal resolutions. A leveling network totaling 434 km in length was deployed to derive subsidence at every 1.5 km along the routes, and the result is accurate to few mm and shows a basin-like subsidence pattern centering at Tuku Township. Four multi-level compaction monitoring wells, co-located with GPS pillars, detect compactions at different depths, showing that the aquifer-system compaction (the cause of subsidence) occurs mostly below depths > 200 m, where reduction of ground-water pumping is most needed. The vertical displacements from GPS and leveling agree to within 1 cm, and are larger than the cumulative compaction detected by the compaction-monitoring wells, suggesting that compaction also occurs below 300 m (the depth of the wells). The vertical displacements derived using DInSAR and 8 ENVISAT SAR images agree with the leveling result to 1-2 cm.
Preface to the Special Issue on "Innovative Applications of Radar and LiDAR Remote Sensing"
(2016-08)
Shih, Peter Tian-Yuan
;
Tseng, Yi-Hsing
;
Tsai, Fuan
;
Chang, Chung-Pai
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土木工程學系
Surface deformation from persistent scatterers SAR interferometry and fusion with leveling data: A case study over the Choushui River Alluvial Fan, Taiwan
(2011-04-15)
Hung, Wei-Chia
;
Hwang, Cheinway
;
Chen, Yi-An
;
Chang, Chung-Pai
;
Yen, Jiun-Yee
The Choushui River Alluvial Fan (CRAF), one of the most important agricultural areas in Taiwan, suffers severe subsidence caused by groundwater withdrawal. We use 20 ENVISAT images from 2006 to 2008 to derive vertical deformation over CRAF by persistent scatterer interferometry (PSI), which effectively reduces errors affecting conventional DInSAR techniques. The pixel density over CRAF is 107.6 pixels/km(2), compared to 0.19 points/km(2) of the leveling benchmarks. PSI yields vertical displacements matching the leveling result to 0.6 cm/year (RMS), and provides a higher spatial resolution of subsidence than the latter. We also develop a data fusion method that considers the high-precision, low point-density leveling result as a smoothed correction to the PSI result. The combined field is more representative of overall deformation characteristics than the PSI-only or leveling-only field, and it is better suited for the assessment of the impact of subsidence over CRAF. (C) 2010 Elsevier Inc. All rights reserved.