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  • 學位論文

尖石鄉北區露營地時空變遷與崩坍潛勢分析

Analysis of Spatio-Temporal Changes and Landside Potential of the Campgrounds in the North Area of Jianshi Township

指導教授 : 陳哲銘
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摘要


台灣近年來露營活動十分盛行,根據中華民國露營協會的統計資料,常態性露營人口已經突破了200萬人,透過Google Trends關鍵字搜尋趨勢觀察露營活動的變化,顯示露營活動於2013年開始於搜尋熱度上呈現大幅度的成長。新竹縣尖石鄉因其地形與景觀特徵,已成為全台最多露營區的鄉鎮,露營地的大量開發,已對環境造成影響,諸如植被覆蓋減少、土壤退化等問題,而部分露營區位於崩塌潛勢高之地質敏感區,亦可能造成土石流或崩塌等災害。 為分析尖石鄉露營地之變遷,以義興、嘉樂、新樂、梅花與錦屏五村為研究對象,使用2008年農林航空測量所正射影像、2013年與2017年Google Earth共計三期影像數據,運用土地利用類型動態度、轉移機率矩陣和馬可夫鏈模式研究方法,分析尖石鄉北區露營地之開發變遷,並進行露營地坡地災害潛勢分析。 在露營地面積改變量的研究結果顯示,2008年至2017年露營地面積成長率為745.43%;在此期間露營地的面積共增加了819,823m2,年變化率為82.8%;而在露營地與非露營地面積變化轉移矩陣結果顯示,共有893,062m2的土地轉為露營地,轉換的面積相當於3.4個大安森林公園的面積,可看出2008年至2017年露營地的成長快速。為檢驗模型是否適合用於未來之預測,對2017年與2018年露營地與非露營地變化進行檢驗與預測。於適合度檢定方面,使用了三種不同的轉移機率矩陣模式進行預測。預測模式中,以第3個模式配適性較佳,p值為0.048,接近0.05,因此使用該平均轉移率矩陣預測2021年的面積,預估2021年露營地面積的成長率將比2017年成長46.5%,並推估2021年露營地的實際面積開發可能會大於預測結果,但也可能會因為政策關係有所改變。整體來看,馬可夫鏈模式預測結果和實際結果有顯著差異,未來可使用羅吉斯回歸進行後續研究。 最後,透過圖層疊合分析,在47個露營地中有20個露營地其90%以上的面積皆位於地質敏感區。有14家露營地位於高風險潛勢溪流處;5家露營地位於土石流潛勢溪流之影響範圍內。在套疊前人崩壞現象敏感度成果方面,研究區露營地所在位置以崩塌類型所佔比例最高,中敏感度占了43%,而高敏感度以上占了45%,另外有17個露營地位於兩種崩壞類型的高敏感度地區。 本研究分析尖石鄉北區露營地時空變遷與崩塌潛勢分析,祈能提供該區土地利用規劃上作為參考,對於位於高風險災害地區之已開發或未來將開發之營地,政府應進行有效的監測與管理。

並列摘要


Camping is one of Taiwan’s favorite outdoor activities. According to The Camping Association of the R.O.C., more than 2 million Taiwanese went camping in 2014. The camping activities also have shown a significant growth in 2013, found in Google Trends keyword research tool. However, the development of campground dramatically affect environment, such as decrease of vegetation cover, degradation of soil, and etc. Some campgrounds are located in geologically sensitive areas with high potential of geological hazards, such as landslides and debris flow. In order to know the temporal and spatial changes of campgrounds in recent years, this study used the spatial dataset obtained from the orthophoto of the Aerial Survey Office, Forestry Bureau in 2008, and the images of Google Earth in 2013 and 2017 of north area of Jianshi township, Hsinchu County. The research methods included the dynamic degree of the land use changes, transfer matrix and the Markov process. The transition probability between campgrounds and non-campgrounds were determined by using the amplitude of the land use pattern changes during the three different periods. In addition, Markov model of campgrounds change in this region was established and validated by the transition probability. The characteristics and tendency of campgrounds change were analyzed and forecasted with the Markov model. The results indicated that the growth rate of the campground area from 2008 to 2017 was 745.43%; in terms of the dynamics of land use type, the area of campgrounds from 2008 to 2017 increased by 819,823 m2, the annual rate of change was 82.8%; the transfer matrix showed that a total 893,348 m2 of land was converted to campgrounds, equivalent to a total area of 3.4 Daan Forest Parks, showing the growth of campgrounds between 2008 and 2017. In order to know if the process can predict the future change of land use, the hypothesis used the X2-test. The chi-square goodness-of-fit test indicated that the third mode of this research has better fit, p value is close to 0.05. Therefore, using the average transfer matrix to predict the campground area of 2021. It is estimated that the growth rate of campground area in 2021 will grow by 46.5% compared with 2017, and estimate that the actual area development of campgrounds in 2021 may be greater than the forecast results, but may also change due to the government policy. Due to the research limitations of Markov chain, it is recommended to use Logit regression as a follow-up method in the future. Finally, through the GIS tool, the high-risk landslide disaster of the campgrounds was assessed. In general, this research expected to provides suggestions of a reference for the land use planning in this area.

參考文獻


外文文獻
Bailey, T.C. and Gatrell, A.C. (1995). Interactive Spatial Data Analysis. Essex, UK: Longman Harlow.
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Bell, E. J. (1974). Markov analysis of land use change - an application of stochastic processes to remotely sensed data. Socio-Economic Planning Sciences, 8(6):311-316.
Boerner, R. E. J. (1996). Markov Models of inertia and Dynamism on Two Contiguous Ohio Landscapes. Geographical Analysis, 28(1):56-66.

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