遙測(Remote Sensing, RS)資訊的出現，提供人們大量的時序影像資料，其周期性觀察地表所提供的資訊，有助於掌握土地變遷及變化，取代以往若人工探勘所需耗費之時間。 土地變遷中除了自然環境的演化外，都市成長的行為及規畫更是全球各大城市政府首要重視的現象。都市的成長層面包含社會、經濟、人文、藝術、環境等影響，且其地表的變動具有一定複雜性，但往往規劃人員僅單單以人口及社經資料對地區未來發展進行解讀，解讀的方式通常皆為硬式決策或線性的預測。因此國內外有許多相關研究開始利用統計模型進行探討，然而統計模型僅能利用現有之現況，得知未來可能會發生的機率，對於規劃上少了前瞻性，因此於20世紀後人們進而開始發展出結合科學理論模式為基礎之方法來模擬都市土地變遷。 綜合上述，本研究利用衛星影像所提供之時序資料為底，並透過統計分析模型結合科學理論模式，創建一套動態模擬模式，預測未來地表變化趨勢，來探討未來都市發展狀況。;Remote sensing provides of spatio-temporal information that can successfully observe the land-cover change. It replaces traditional implementation using the ground survey data. It is costly and time-consuming. Land cover change has been seen as a transformation of natural environment. In addition, urbanization has also become a global major issue in recent years. The phenomenon of urbanization includes society, economic development, culture, art, and environmental impact. The land cover change is exceedingly complex, however the urban policy makers sometimes only consider factors such as population and socioeconomic status. The results usually are Hard Decision or Linear Prediction. Many correlation studies start to use other statistical models on domestic and international research. However, statistical models aim at the prediction of the future development probability that has a proactive vision. After the 20th century, people developed a dynamic algorithm to simulate the land cover change. The main objective of this study demonstrates to use spatio-temporal data of remote sensing (RS) imagery in combination with statistical model and science theory to create the dynamic simulation model in urban development and prediction.
