請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/46458完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃宏斌(Hung-Pin Huang) | |
| dc.contributor.author | Po-Wei Lin | en |
| dc.contributor.author | 林柏維 | zh_TW |
| dc.date.accessioned | 2021-06-15T05:10:05Z | - |
| dc.date.available | 2011-07-26 | |
| dc.date.copyright | 2010-07-26 | |
| dc.date.issued | 2010 | |
| dc.date.submitted | 2010-07-23 | |
| dc.identifier.citation | 王濟川、郭志剛(2004)，「Logistic迴歸模型－方法及應用」，五南出版社。
何春蓀(1986)，「臺灣地質概論－臺灣地質圖說明書，第二版」，經濟部中央地調所，163頁。 林惠玲、陳正倉(2002)，「應用統計學二版」，雙葉書廊出版社。 中華水土保持學會(2005)，「水土保持手冊」，行政院農業委員會水土保持局。 湯國安、楊昕(2006)，「ArcGIS地理信息系統空間分析實驗教程」，科學出版社。 中央氣象局全球資訊網http://www.cwb.gov.tw/ 林啟文、張徽正、盧詩丁、石同生、黃文正(2000)，「台灣活動斷層概論-五十萬分之一台灣活動斷層分布圖說明書」，經濟部中央地調所。 Ayalew, L. and Yamagishi, H., 2005. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology, 65(1-2): 15-31. Ayalew, L., Yamagishi, H. and Ugawa, N., 2004. Landslide susceptibility mapping using GIS-based weighed linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan. Landslides, 1: 73-81. Begueria, S., 2006. Changes in land cover and shallow landslide activity: A case study in the Spanish Pyrenees. Geomorphology, 74(1-4): 196-206. Can, T., Nefeslioglu, H.A., Gokceoglu, C., Sonmez, H. and Duman, T.Y., 2005. Susceptibility assessments of shallow earthflows triggered by heavy rainfall at three catchments by logistic regression analyses. Geomorphology, 72(1-4): 250-271. Carrara, A. and Merenda, L., 1976. Landslide Inventory in Northern Calabria, Southern Italy. Geological Society of America Bulletin, 87(8): 1153-1162. Chang, K.T., Chiang, S.H. and Hsu, M.L., 2007. Modeling typhoon- and earthquake-induced landslides in a mountainous watershed using logistic regression. Geomorphology, 89(3-4): 335-347. Chuang, S.C., Chen, H., Lin, G.W., Lin, C.W. and Chang, C.P., 2009. Increase in basin sediment yield from landslides in storms following major seismic disturbance. Engineering Geology, 103(1-2): 59-65. Chung, C.J. and Fabbri, A.G., 1993. The Representation of Geoscience Information for Data Integration. Nonrenewable Resources, 2(3): 122-131. Cox, D.R. and Snell, E.J., 1989. Analysis of binary data. Chapman & Hall, London. Dadson, S.J. et al., 2004. Earthquake-triggered increase in sediment delivery from an active mountain belt. Geology, 32(8): 733-736. Dai, F.C. and Lee, C.F., 2001. Terrain-based mapping of landslide susceptibility using a geographical information system: a case study. Canadian Geotechnical Journal, 38(5): 911-923. Dai, F.C. and Lee, C.F., 2002. Landslide characteristics and, slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology, 42(3-4): 213-228. De Rubeis, V., Tosi, P., Gasparini, C. and Solipaca, A., 2005. Application of kriging technique to seismic intensity data. Bulletin of the Seismological Society of America, 95(2): 540-548. den Eeckhaut, M. et al., 2006. Prediction of landslide susceptibility using rare events logistic regression: A case-study in the Flemish Ardennes (Belgium). Geomorphology, 76(3-4): 392-410. Einstein, H.H., 1988. Landslide risk assessment procedure. In: C. Bonnard (Editor), The Fifth International Symposium on Landslides, pp. 1075-1090. Evans, S.G., Guthrie, R.H., Roberts, N.J. and Bishop, N.F., 2007. The disastrous 17 February 2006 rockslide-debris avalanche on Leyte Island, Philippines: a catastrophic landslide in tropical mountain terrain. Natural Hazards and Earth System Sciences, 7(1): 89-101. Gomez, H. and Kavzoglu, T., 2005. Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela. Engineering Geology, 78(1-2): 11-27. Gupta, R.P. and Joshi, B.C., 1990. Landslide Hazard Zoning Using the Gis Approach - a Case-Study from the Ramganga Catchment, Himalayas. Engineering Geology, 28(1-2): 119-131. Hearn, E.L. and Wilson, R.C., 1995. Shaking Intensity Thresholds for Rock Falld and Slides: Evidence form 1987 Whittier Narrows and Superstition Hills Earthquake Storng-Motion Records. Bull. Seis. Soc. Am., 85(6): 1739-1757. Keefer, D.K., 1994. The Importance of Earthquake-Induced Landslides to Long-Term Slope Erosion and Slope-Failure Hazards in Seismically Active Regions. Geomorphology, 10(1-4): 265-284. Lee, S. and Min, K., 2001. Statistical analysis of landslide susceptibility at Yongin, Korea. Environmental Geology, 40: 1095-1113. Lee, S. and Pradhan, B., 2006. Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia. Journal of Earth System Science, 115(6): 661-672. Lee, S., Ryu, J.H. and Kim, I.S., 2007. Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea. Landslides, 4(4): 327-338. Lee, S., Ryu, J.H., Lee, M.J. and Won, J.S., 2003. Use of an artificial neural network for analysis of the susceptibility to landslides at Boun, Korea. Environmental Geology, 44(7): 820-833. Lee, S. and Sambath, T., 2006. Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environmental Geology, 50(6): 847-855. Lee, S.W. et al., 1990. An Assessment of Landslide Problems and Watershed Management in Taiwan. In: R.R. Ziemer (Editor), The Fiji Symposium on Research Needs and Applications to Reduce Erosion and Sedimentation in Tropical Steeplands. IAHS Publication, Suva, Fiji, pp. 238-246. Lin, G.W. et al., 2008. Effects of earthquake and cyclone sequencing on landsliding and fluvial sediment transfer in a mountain catchment. Earth Surface Processes and Landforms, 33(9): 1354-1373. Meunier, P., Hovius, N. and Haines, A.J., 2007. Regional patterns of earthquake-triggered landslides and their relation to ground motion. Geophysical Research Letters, 34(20): -. Moore, I.D., Grayson, R.B. and Ladson, A.R., 1991. Digital terrain modeling: a review of hydrological, geomorphological, and biological applications. Hydrological Processes, 5: 3-30. Muthu, K., Petrou, M., Tarantino, C. and Blonda, P., 2008. Landslide possibility mapping using fuzzy approaches. Ieee Transactions on Geoscience and Remote Sensing, 46(4): 1253-1265. Nagelkerke, N.J.D., 1991. A note on a general definition of the coefficient of determination. Biometrika, 78(3): 691-692. Nefeslioglu, H.A., Gokceoglu, C. and Sonmez, H., 2008. An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Engineering Geology, 97(3-4): 171-191. Ohlmacher, G.C. and Davis, J.C., 2003. Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Engineering Geology, 69(3-4): 331-343. Schenkova, Z. et al., 2007. Isoseismal maps drawing by the kriging method. Journal of Seismology, 11(1): 121-129. Sidle, R.C., 2006. Using weather and climate information for landslide prevention and mitigation. In: M.V.K. 1、1、1、Sivakumar and N. Ndiangui (Editors), International Workshop on Climate and Land Degradation. Springer-Verlag Berlin, Arusha, TANZANIA, pp. 285-307. Soeters, R. and Van Westen, C.J., 1996. Slope instability recognition, analysis, and zonation, Transportation Research Board, National Research Council, Washington, DC. Song, R.H., Hiromu, D., Kazutoki, A., Usio, K. and Sumio, M., 2008. Modeling the potential distribution of shallow-seated landslides using the weights of evidence method and a logistic regression model: a case study of the Sabae Area, Japan. International Journal of Sediment Research, 23(2): 106-118. Swets, J.A., 1988. Measuring the accuracy of diagnostic systems. Science, 240: 1285-1293. Tibaldi, A., Ferrari, L. and Pasquare, G., 1995. Landslides Triggered by Earthquakes and Their Relations with Faults and Mountain Slope Geometry - an Example from Ecuador. Geomorphology, 11(3): 215-226. Turer, D., Nefeslioglu, H.A., Zorlu, K. and Gokceoglu, C., 2008. Assessment of geo-environmental problems of the Zonguldak province (NW Turkey). Environmental Geology, 55(5): 1001-1014. van Westen, C.J., Castellanos, E. and Kuriakose, S.L., 2008. Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview. Engineering Geology, 102(3-4): 112-131. Varnes, D.J., 1984. Landslide Hazard Zonation: A Review of Principle and Practice. UNESCO Press, Paris. Yesilnacar, E. and Topal, T., 2005. Landslide susceptibility mapping: A comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey). Engineering Geology, 79(3-4): 251-266. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/46458 | - |
| dc.description.abstract | 臺灣位於西太平洋颱風帶上，颱風豪雨常造成不同規模之崩塌，因此，降雨量等水文因子和台灣特殊之地理、地質因子常被視為崩塌因子，雖然如此，台灣每年約千次之大小地震是否會加重崩塌發生之機率和規模，卻較少人探討。因此，本研究是假設地震對邊坡之破壞具累加性，利用地震累積水平加速度值來代表地震之累積能量大小，也就是假設每一次地震即會影響地質結構，造成大小不一的結構破壞，是考慮地震的潛在破壞到底會不會增加崩塌之機率，而非考慮其外在破壞，來探討地震對崩塌潛勢之影響，以及增加地震因子可否提昇崩塌潛勢模型之準確度。
為瞭解地震因子對於崩塌潛勢模型的影響大小，本研究蒐集2004年艾利颱風後之全臺灣崩塌地區位資料，做為崩塌與否的基準，以及1991年~2004年臺灣地區16場災害之累積水平地表最大加速度資料，與2004年之數值高程模型、2000~2004年臺灣地區年平均雨量，共11個崩塌影響因子，運用地理資訊系統和多變量羅吉斯迴歸，得到包含地震因子及不包含地震因子的兩個崩塌潛勢模型。同時，利用分類誤差矩陣、概似比檢驗、類R2指標、簡單統計指標及ROC curve共5種檢驗方法判別地震因子對於崩塌潛勢模型之影響權重。再以2003年及2006年之崩塌地資料，與2008年石門水庫集水區在經歷辛樂克颱風後之崩塌區位做驗證，以評估崩塌潛勢模型之準確率，並對其結果做卡方檢定，檢定此兩模型在判釋高、中、低崩塌潛勢是否有顯著差異。最後再針對臺灣地區崩塌地的空間分布進行分析，並與羅吉斯迴歸結果做比較，探討這11個崩塌因子可能影響崩塌之機制。 結果顯示，加入地震因子的崩塌潛勢模型對預測崩塌發生之準確性較佳，顯示在地震頻繁區域，使用歷史資料評估崩塌潛勢時，應該納入地震因子，以免錯誤估計該區域之崩塌潛勢。 | zh_TW |
| dc.description.abstract | Taiwan is located in the Western Pacific typhoon zone, and typhoons and its inducing heavy rains often result in different scale of landslides. Hence, rainfall and other hydrologic factors, as well as special geographic, geologic factors in Taiwan are selected as landslide factors. Even though, the topic about thousands of earthquakes a year might increase the probability and scale of landslides is seldom cared about by researchers. Therefore, this study assumes that every earthquake will affect the geological structure, causes structural damages and uses cumulative horizontal seismic acceleration to represent the cumulative energy of earthquakes. That is to consider the potential earthquake damage Not destruction of the external to explore the effect of earthquakes on landslides. Is it possible that seismic factor can increase the accuracy of landslide susceptibility model? This research will discuss about it.
To understand how the seismic factor influences the landslide susceptibility model, we collected all landslides area after Typhoon Aere in 2004, which is used as a baseline of landslide. We also collected Cumulate Horizontal Peak Ground Acceleration of sixteen events of seismic disasters from 1991 to 2004 in Taiwan, the DEM from SWCB in 2004 and average annual rainfall from 2000 to 2004. In this study, we investigate eleven factors of landslides. And, GIS and Logistic regression are used to get two landslide susceptibility models, which are carried out with and without seismic factor. Meanwhile, five kinds of test methods such as classification error matrix, likelihood ratio test, analogous R2 index, simple statistical indicators and the ROC curve are calculated to determine how the seismic factor affect the landslide susceptibility model. Then, the landslide data in 2003 and 2006, and Shihmen Reservoir landslide locations after Typhoon Sinlaku in 2008 are collected to evaluate the accuracy of landslide susceptibility model. Finally, the spatial distribution of landslide in Taiwan are plotted and compared with the result of Logistic regression, and exploration of the relation between landslide and landslide factors. The result showed that the landslide susceptibility model which adds seismic factor is better on predicting the occurrence of landslide. So it showed that the assessment of the landslide susceptibility with historical data must consider the effect of the seismic factor to avoid misjudge the occurrence of landslide in earthquake-prone area. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T05:10:05Z (GMT). No. of bitstreams: 1 ntu-99-R97622024-1.pdf: 3629345 bytes, checksum: 473faf777809a2a53d42c1d4bfe87562 (MD5) Previous issue date: 2010 | en |
| dc.description.tableofcontents | 摘要.......................................................I
Abstract..................................................II 圖目錄...................................................VII 表目錄..................................................VIII 一、前言...................................................1 二、文獻回顧...............................................5 2.1崩塌之定義..............................................5 2.2崩塌之分類..............................................5 2.3崩塌影響因子............................................7 2.4崩塌潛勢研究方法.......................................14 2.4.1定性法...............................................14 2.4.2定量法...............................................14 三、研究方法..............................................18 3.1羅吉斯迴歸.............................................18 3.1.1羅吉斯迴歸模型估計的假設條件.........................24 3.2模型優劣檢驗...........................................25 3.2.1分類誤差矩陣.........................................25 3.2.2模型卡方統計與概似比檢驗.............................26 3.2.3類R2指標(Analogous R2)...............................28 3.2.4簡單統計指標.........................................29 3.2.5ROC curve............................................30 四、研究資料..............................................31 4.1研究區域概況...........................................31 4.1.1地理環境位置.........................................31 4.1.2地質條件.............................................31 4.2崩塌因子資料來源.......................................35 4.3研究資料之建立.........................................36 4.3.1崩塌地分布資料.......................................37 4.3.2崩塌因子資料.........................................38 4.4崩塌因子資料分析.......................................48 五、結果與討論............................................50 5.1羅吉斯迴歸.............................................50 5.2模型優劣檢驗...........................................53 5.2.1分類誤差矩陣.........................................53 5.2.2模型卡方統計及概似比檢驗.............................55 5.2.3類R2指標.............................................56 5.2.4簡單統計指標.........................................57 5.2.5 ROC curve...........................................58 5.3模式驗證...............................................59 5.3.1 2003年全臺灣崩塌地區位驗證模組......................59 5.3.2 2006年全臺灣崩塌地區位驗證模組......................61 5.3.3 2008年石門水庫集水區崩塌地區位驗證模組..............63 5.3.4小結.................................................65 5.4崩塌因子之討論.........................................66 5.4.1坡度因子.............................................66 5.4.2坡向因子.............................................67 5.4.3高程因子.............................................68 5.4.4地形曲率因子.........................................70 5.4.5地質因子.............................................71 5.4.6雨量因子.............................................74 5.4.7地震因子.............................................75 5.4.8與斷層距離...........................................76 5.4.9距道路距離因子.......................................77 5.4.10距水系距離..........................................78 5.4.11土壤濕度指數........................................79 5.5崩塌潛勢圖.............................................80 六、結論與建議............................................82 6.1結論...................................................82 6.2建議...................................................83 七、參考文獻..............................................84 | |
| dc.language.iso | zh-TW | |
| dc.subject | 羅吉斯迴歸 | zh_TW |
| dc.subject | 地震因子 | zh_TW |
| dc.subject | 崩塌潛勢模型 | zh_TW |
| dc.subject | Logistic Regressio | en |
| dc.subject | Seismic factor | en |
| dc.subject | Landslide Susceptibility Model | en |
| dc.title | 以羅吉斯迴歸探討累積水平地震加速度對崩塌潛勢影響之研究 | zh_TW |
| dc.title | The Effect of Cumulative Horizontal Seismic Acceleration on Landslide susceptibility with Logistic Regression Model | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳信雄,吳輝龍,段錦浩,游繁結 | |
| dc.subject.keyword | 地震因子,羅吉斯迴歸,崩塌潛勢模型, | zh_TW |
| dc.subject.keyword | Seismic factor,Landslide Susceptibility Model,Logistic Regressio, | en |
| dc.relation.page | 87 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2010-07-26 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
| 顯示於系所單位： | 生物環境系統工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-99-1.pdf 未授權公開取用 | 3.54 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。