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研究生:張建輝
研究生(外文):Chien-Hui Chang
論文名稱:以多項式羅吉斯迴歸推估土壤有效深度
論文名稱(外文):Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis
指導教授:詹勳全詹勳全引用關係
指導教授(外文):Hsun-Chuan Chan
口試委員:呂珍謀林昭遠
口試日期:2017-06-29
學位類別:碩士
校院名稱:國立中興大學
系所名稱:水土保持學系所
學門:農業科學學門
學類:水土保持學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:115
中文關鍵詞:土地可利用限度土壤有效深度多項式羅吉斯迴歸
外文關鍵詞:slopeland utilizable limitationsoil depthmultinomial logistic regression
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隨著山坡地開發漸增,山坡地因土地利用不當和颱風豪雨影響,常發生坡地災害,而土壤深度為坡地災害中淺層崩塌之重要參數,政府更將土壤深度視為山坡地土地可利用限度查定之因子,顯示土壤深度於山坡地災害與管理佔有重要地位。本研究試以苗栗縣後龍溪流域上游集水區為研究區域,利用地理資訊系統結合多項式羅吉斯迴歸推估土壤有效深度,依其深度範圍不同分為甚深層、深層、淺層及甚淺層,選取坡度、坡向、高程、地形曲率及常態化差異植生指標為環境因子,進行土壤有效深度推估,並以分類誤差矩陣、Kappa指數進行模式結果評估,其中建模組之整體準確率為76.6%,Kappa指數為0.65,驗證組之整體準確率為70.5%,Kappa指數為0.57,結果並與空間內插法和地形濕度指數法之推估結果進行比較探討,其中一般克利金之整體準確率為45.7%,Kappa指數為0.15,迴歸克利金之整體準確率為46.7%,Kappa指數為0.16,地形濕度指數法之整體準確率為30.5%,Kappa指數為-0.05,由研究結果可知研究區內以多項式羅吉斯迴歸法進行土壤深度推估優於其他方法。
It is known that the slopeland disaster is usually related to the land development, improper land use and torrential rain. The soil depth is an important factor in the shallow landslide. The government of Taiwan also uses soil depth as a factor of slopeland utilizable limitation to regulate the development and conservation of a slopeland. That all shows the soil depth play an important role in shallow landslide and land management.
This research aimed to classify the effective soil depth by using multinomial logistic regression with the environmental factors. The upper watershed of the Houlong River located at the central Taiwan was selected as the study areas. The analysis of multinomial logistic regression is performed by the assistance of a Geographic Information Systems (GIS). The effective soil depth was categorized into four levels including deeper, deep, shallow and shallower. The environmental factors of slope, aspect, digital elevation model (DEM), curvature and normalized difference vegetation index (NDVI) were selected for classifying the soil depth. Error Matrix and Kappa index were then used to assess the model accuracy. In the modeling group, the overall accuracy was 76.6% and Kappa index was. 0.65. In the validation group, the overall accuracy was 70.5% and Kappa index was. 0.57.
Then, the results of model were compared with ordinary kriging, regression kriging and TWI method. In the ordinary kriging method, the overall accuracy was 45.7% and Kappa index was. 0.15. In the regression kriging method, the overall accuracy was 46.7% and Kappa index was. 0.16. In the TWI method, the overall accuracy was 30.5% and Kappa index was. -0.05. As the results, the multinomial logistic regression method is more accurate on classifying the effective soil depth among the investigated methods in the study areas.
摘要 i
Abstract ii
目錄 iv
表目錄 vii
圖目錄 ix
第一章 前言 1
1.1 研究動機與目的 1
1.2 研究流程 2
1.3 研究架構 4
第二章 文獻回顧 6
2.1 土壤深度於淺層崩塌之影響 6
2.2 山坡地土地可利用限度查定介紹 7
2.3 分析單元 13
2.2.1 地域單元 13
2.2.2 地貌單元 13
2.2.3 斜坡單元 13
2.2.4 行政單元 14
2.2.5 網格單元 14
2.2.6 特別條件單元 14
2.4 土壤深度推估 16
2.3.1 物理基礎法 17
2.3.2 經驗統計法 18
2.3.3 空間內插法 19
第三章 研究材料與方法 22
3.1 研究區域介紹 22
3.1.1 地理位置 22
3.1.2 地形 22
3.1.3 地質 24
3.1.4 水系 25
3.1.5 氣象 25
3.2 基本資料蒐集 30
3.3 研究方法 31
3.4 結果評估方法 35
第四章 土壤有效深度分析 37
4.1 現場點位調查 37
4.2 分析樣本選取 44
4.3 因子篩選及處理 45
4.3.1 地形 46
4.3.2 母岩 52
4.3.3 氣候 54
4.3.4 植生 59
4.3.5 化育時間 61
4.3.6 因子選取及處理 62
4.4 建模分析成果 66
4.5 不同分析類別或範圍於土壤有效深度分析之影響 68
4.6 不同分析方法比較 75
4.6.1 一般克利金法 76
4.6.2 迴歸克利金法 76
4.6.3 地形濕度指數法 77
4.6.4 結果比較 77
4.7 結果分析討論 82
第五章 結論與建議 88
5.1 結論 88
5.2 建議 89
參考文獻 90
附錄一 96
附錄二 110
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