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  • 學位論文

遙測技術應用於不同區域都市發展程度之監測

Monitoring Urbanization in Different Cities Using Remote Sensing Technologies

指導教授 : 鄭克聲

摘要


在進行都市規畫或是環境資源之管理前,先進行了解當地之地表空間組成,為必不可少的一步;因此本研究中利用日本ALOS大地資源衛星所裝載之感測器取得多光譜衛星影像,對台北及日本之東京與京都三個都市化程度各不相同的地區進行地表空間組成之分析與比較。研究中先將三個研究地區之多光譜衛星影像進行地表覆蓋分類,並以此結果為基礎,將影像劃分為等面積小格以計算夏儂多樣性指數(SHDI)分布,同時亦根據小格內各類地表覆蓋之比例繪製立體散佈圖,在此由數值及視覺化工具比較不同都市化程度地區差異:SHDI數值方面,東京地區的地表覆蓋其多樣性及均勻性均低,配合散佈圖中所有散佈點明顯集中於建地覆蓋處,表示東京地區的建物密集度確實高於其他地區,可做為高度都市化之證據;相對的,台北與京都地區地表覆蓋具有高多樣性且均勻性亦高,其中京都地區有相對最低之都市化程度與都市化區域面積,以及較高的地表覆蓋多樣性,可做為其不同地表覆蓋混合程度較高之證據,適於環境多樣性之未來發展。而以小格為基礎之升尺度影像,另外還可計算每個小格之常態化差異植生指標(NDVI)平均值,做為描述當地之地表覆蓋特性的證據;NDVI值不需經過影像分類過程即可求得可做為快速而簡易區分當地環境特性的工具。 在整合以上升尺度之空間資訊後,本研究提出一種區域都市化指標(Urbanization Index, UI),同時含有代表人類密集活動之建物面積比例及代表自然環境受人類活動影響的NDVI升尺度值,經由區域中UI值的分布可界定整個大區域中有不同之都市化程度區域,而藉以描繪都市化區域之輪廓。而以三個研究區域之UI區域平均值來看,東京地區為0.91,京都地區為0.55,而大台北地區則為0.72,此一結果與研究初期之預想及研究中對於不同研究區域之文字性質的都市化程度描述及地景指數比較結果,正好相互符合。 本研究由遙測領域出發,所提出之都市化指標跳出目前社會學所定義都市化之框架,可針對小區域進行都市化程度之量化評估;且經由升尺度影像之製作,更能去除以行政區域為劃分之限制,而直接以視覺化方式表現都市化區域於地理空間之分布情形。

並列摘要


Understanding the landcover pattern in a region is essential for landuse planning and resources management. In this study ALOS multispectral images were used to compare landcover patterns in three study areas, namely Tokyo, Kyoto, and Taipei, of different de-grees of urbanization. From the results of landuse/landcover classification, Shannon diver-sity index at cell level was used for landcover pattern analysis. Existing landcover pattern of the three study areas were also compared by investigating cell distribution in a landcover coverage-ratio space. Both the landcover type richness and evenness are low in the Tokyo study area and built-up is the single dominant landcover type in almost all cells. In compar-ison, landcover patterns of the Kyoto and Taipei study areas are more diversified, with sig-nificant amount of cells having mixed and non-dominant landcover types. Kyoto is least urbanized and enjoys a good mixture of different landcover types. It was found that cell-average NDVI alone can be used for delineating areas of certain dominant landcover types. Implementation of such method does not require an a priori LULC classification, and thus is particularly useful when good training data for LULC classification are not available. An urbanization index which integrates the coverage-ratio of built-up landcover type and the cell-average NDVI was proposed and used to explore the spatial variation of degree of ur-banization. Area-average urbanization indices of the Tokyo, Kyoto, and Taipei study areas were calculated to be 0.91, 0.55, and 0.72, respectively. Such results are consistent with the results of qualitative evaluation using different landscape metrics.

參考文獻


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被引用紀錄


蕭淩瑄(2013)。遙測影像分類之不確定性評估〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2013.02948

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