臺灣博碩士論文加值系統

快速都市化所造成的人口成長對於土地資源的壓力在過去數十年已成為雅加達首要的課題之一，特別是對於Ciliwung集水區而言。為了解都市化及相關之變遷對於環境可能的影響，都市土地利用模擬對於規劃者而言是相當具有潛力的工具。有鑑於此，本研究希望透過整合不同方法來探討Ciliwung集水區過去及未來的土地利用變遷情形以及相對應應的因子，期望能成為制定相關政策之參考依據。本研究透過遙測影像判識來獲得1997、2007以及2018年的土地利用資料作為建構模型之基礎，並將其分類為森林、水體、植被以及建成環境四種利用別。多準則評估法則用來建構模擬所需之轉移潛力圖層，過程中cramer’s V作為計算因子權重之重要方法，分析結果顯示運輸與地價為影響本地區土地利用變遷之兩個最具影響力因子。模型驗證的結果顯示Kappa=0.6907為可接受之模擬精確程度。根據上述分析基礎，本研究進一步透過馬可夫練細胞自動機模型模擬未來2028以及2038年的土地利用型態。整體結果顯示集水區內將可能有大量之新建成地產生，其將可能對於環境造成之負面衝擊值得深入探討。本研究期望所建構的模型未來能夠實際應用於規劃上，為雅加達相關政府單位提供有效之集水區規劃策略評估工具。

The steep increase in the urban population in Jakarta city has exerted heavy pressure on the land resources periphery since the last few decades, especially in the Ciliwung watershed that significantly contributes to the environmental issue in Jakarta. Land use simulations are of particular interest to rural-urban, regional planners, and the government owing to the future impacts of actions and policies are decisive in order for a more sustainable future. The purposes of this thesis are to explore drivers and components and to simulate future land use and land cover change. Remote Sensing data were used to generate classification maps for 1997, 2007, and 2018 classified as forest, waterbody, vegetation, and built-up area, respectively. Multicriteria decision-making and fuzzy parameter standardisation approaches were applied to produce transition suitability image. Cramer's V method was used to determine the significant contributor and driver of land use and land cover change, and the results showed that transportation and land price are two of the most influential factors. Markov chain and cellular automata were employed to generate simulated maps of the Ciliwung watershed in 2028 and 2038. The model was validated against actual land use map in 2018 and the Kappa value is 0.6907, indicating acceptable simulation accuracy. Based on the simulation, it is found that the area of the forest might decrease from 4.987 ha to 4.916 ha. Moreover, the vegetation cover might decrease from 10.666 ha to 8.560 ha, and water body might slightly decrease from 84 ha to 81 ha. Conversely, the built-up area might increase significantly from 22.873 ha to 25.052 ha. In the end, this thesis indicates that it is essential to simulate land use and land cover to help local authorities and government centres to give better understand a complex land-use system and to develop an improved land use management strategy considering the possible development trend in the future.

ACKNOWLEDGEMENTS…………………………………………………………... i
ABSTRACT (Chinese)………………………………………………………………... ii
ABSTRACT (English)………………………………………………………………… iii
TABLE OF CONTENTS……………………………………………………………... v
LIST OF FIGURES…………………………………………………………………… viii
LIST OF TABLES…………………………………………………….......................... x

CHAPTER 1 INTRODUCTION……………………………………………………... 1
1.1 Background………………..…………………………………………………… 1
1.2 Study Area……………………………………………………………………... 3
1.2.1 Ciliwung Watershed……………………………………………………. 5
1.2.2 Incidences of Flooding in Jakarta………………………………………. 5
1.3 Research Question…………………………………………………………….. 6
1.4 Structure of Thesis…………………………………………………………….. 7

CHAPTER 2 LITERATURE REVIEW…………………………………………….. 8
2.1 Land Use and Land Cover …………………………………………………….. 8
2.2 The need for models……………………………………………………………. 9
2.3 Remote Sensing and GIS……………………………………………………... 10
2.3.1 Supervised Classification……………………………………................... 11
2.3.2 Maximum likelihood classification……………………………………… 12
2.3.3 Image Enhancement…………………………………………................... 13
2.4 Multi-Criteria Decision and Evaluation …….………………………………… 13
2.5 Spatial Planning Law in Indonesia As A Controlling Land Allocates Decision 14
2.6 Method of predicting land use and land cover ……..……………………….... 15
2.7 Markov-Chain & Cellular Automata ………………………………………… 16
2.7.1 Markov-Chain…………………………………………......................... 16
2.7.2 Definition of Cellular Automata……………………………………….. 17
2.7.3 Element of Cellular Automata…………………………......................... 17

CHAPTER 3 METHODOLOGY AND DATA……………………………………… 19
3.1 Image Data…………………………………………………………………….. 19
3.2 Other Data Resource…………………………………………………………… 19
3.3 Tools…………………………………………………………………………… 20
3.4 Data Processing and Study Area Selection....…………………………………. 20
3.5 Image Enhancement Implementation………………………………………….. 22
3.6 Image Satellite Classification in the Ciliwung watershed……………………… 23
3.7 Multi Criteria Evaluation….…………………………………………………... 25
3.7.1 Factor Weight and Test the Explanatory Power of Variables…………… 27
3.7.2 Fuzzy Set Membership………………………………………………….. 27
3.8 Land Use Change Modelling………………………………………………… 29
3.8.1 Markov chain model……………………………………………………. 29
3.8.2 Cellular automata model………………………………………………... 32
3.8.3 Validation of Land Use and Land Cover Change Models……………….. 32

CHAPTER 4 ANALYSIS AND RESULT…………………………………………………...34
4.1 Detecting Change Analysis …………………………………………………… 34
4.2 Factor Weight & Driving Factor Analysis…………………………………….. 36
4.3 Determining Suitability Map…………………………………………………… 38
4.3.1 Constraints……………………………………………………………… 38
4.3.2 Factors…………………………………………………………………... 39
4.4 Employment Markov Chain and Cellular Automata Methods in Study Area….. 51
4.5 Model Validation………………………………………………………………. 52
4.6 Simulated change 2028 and 2038 …………………………………................... 54
4.7 Brief Result…………………………………………………………………...... 55

CHAPTER 5 CONCLUSION………………………………………………………… 58
REFERENCE………………………………………………………………………….. 60
APPENDICES…………………………………………………………………………. 66
Appendix 1 Accuracy Assessment……………………………………………….. 66
Appendix 2 Final Defence Question……………………………………………… 69

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