無節制的城都市擴張，可能會導致許多污染問題，並需要面臨都市管理策略的重新規劃。瓜地馬拉有著美洲最高的都市化率，而瓜地馬拉市是該國最大的城市，並且有著快速增長的人口，從1994年的1813,825人成長至2013年的257,616人。因此這個城市的擴張和人口的增加，政府需要對未來土地利用和都市資源的分配進行合理的規劃。
本研究主要使用遙測影像技術及統計分析對瓜地馬拉市做都市成長情況的土地覆蓋變遷分析。為了實現未來17年的城市土地覆蓋預測，該時期的歷史資料必須被觀察。首先，收集相關的衛星影像、統計數據和地理資訊來觀察近來17年的都市變化。本研究蒐集了1997、2000、2003、2009和2014年的Landsat影像進行地表覆蓋分類，並根據現有的土地覆蓋調查圖層以進行分類精度的評估。最後，蒐集其他地理和人口資料來建立都市變遷的預測模式。此模式使用了邏輯回歸分析(logistic regression analysis)為基礎的細胞自動機模式來模擬都市未來的擴張情形。本研究使用1997年和2003年的影像來校正模式，而2003、2009和2014年的影像則被用來驗證此模式。本研究成果可做為一個未來都市成長的可能情境，並為瓜地馬拉市未來17年的都市發展規劃提供了有用的參考資訊。

Remote sensing has proven to be an efficient tool to study the urban development. The uncontrolled expansion of the urban can bring many challenges and problems like the increase in carbon dioxide concentration and the need for a larger transportation and services network.
Guatemala is the country with the highest urbanization rate in America, and its largest city is Guatemala City, which shows a rapid increase in population from 1,813,825 inhabitants in 1994 to 3,257,616 in 2013. Governmental institutions need to prepare for this city’s expansion and population increase by making the most sustainable decisions for land use, services distribution and natural disasters prevention to mention a few.
The objective of this thesis is to monitor and predict the urban development of Guatemala City using spatial data and statistical analysis. In order to achieve a prediction for the next seventeen years, at least the same amount of time had to be monitored.
First, the related satellite images, statistical data and GIS (Geographical Information Systems) data were collected to observe the urban changes of the city in the last seventeen years. Then, the changes were studied through the analysis of a supervised classification performed on four Landsat images of Guatemala City, corresponding to the dates of 1997, 2003, 2009 and 2014 respectively. Statistics of the four images were then processed and integrated with other geographical and demographical databases to examine the changes in the city and provide information for the creation of a model.
A logit-based CA (cellular automata) model was applied to simulate the city’s expansion. Images of 1997 and 2003 were used to calibrate the model and images from the year 2003, 2009 and 2014 were used to confirm its accuracy.
The model is expected to be able to create different urban growth scenarios that can serve as base to predict and plan the development of Guatemala City for the next seventeen years.

ABSTRACT ii
ACKNOWLEDGEMENTS iii
LIST OF FIGURES vi
LIST OF TABLES x
ACRONYMS xi
Chapter 1. INTRODUCTION 1
1.1. Presentation of urban areas and their expansion 1
1.2. Selection of the study area 3
1.3. Geographic information systems 5
1.4. Landsat imagery 5
1.5 Prediction models 6
1.6. Purpose of research 7
1.6.1. Research question 7
1.6.2 Research objectives 7
1.6.3. Research scope and limitations 8
Chapter 2. BACKGROUND INFORMATION AND STUDY AREA 9
2.1. General information about Guatemala 9
2.2. The urban area of Guatemala City 11
2.2.1. History 11
2.2.2. The current situation of Guatemala City 13
2.3. Determination of the study area 19
Chapter 3. LITERATURE REVIEW 23
3.1. Background on urban studies 23
3.2. Geographic information systems applied to urban studies 25
Chapter 4. MATERIALS AND METHODS 29
4.1. Work flow diagram 29
4.2. Data acquisition 31
4.2.1 Exploring the area and the urban growth 31
4.2.2. Data acquisition 34
4.2.3. Image classification 49
4.3.3. Accuracy assessment 58
4.4. Urban model 64
4.4.1. Theory 64
4.4.2. Input variables 70
4.4.3. Model performance 74
Chapter 5. RESULTS 76
5.1. Results of image classification 76
5.1.1. Classified and corrected maps 76
5.1.2. Maps reclassified into urban and non urban 82
5.1.3. Accuracy test results 83
5.1.4.Urban area change in the classified images 85
5.2. Urban modeling 86
5.2.1. Model calibration 86
5.2.2. Model validation 96
5.2.3. Urban prediction 110
5.2.4. Prediction of urban change 118
Chapter 6. DISCUSSION 123
6.1. Urban area growth 123
6.2. Area change compared to other urban index 129
6.3. Urban growth related to city features 134
6.4. Potential impacts due to urban growth in the future 134
6.5. Model Assessment 135
6.6. Limitations 136
Chapter 7. CONCLUSIONS 137
Chapter 8. SUGGESTIONS 140
BIBLIOGRAPHY 141
Annexed 1: 2013, Population by municipality in the study area (SEGEPLAN, 2014) 145
Annexed 2: Extension, rehabilitation and paving of roads. (Ministry of comunications infrastructures and housing and general office of roads, 2007) 148
Annexed 3: Expansion and new routes. (Ministry of comunications infrastructures and housing and general office of roads, 2007) 149

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