本研究探討墾丁國家公園之後壁湖、南灣、大灣、小灣、船帆石與砂島沙灘共六座沙灘,於2010年3月至2011年2月間進行共15次沙灘地形測量。利用地理資訊系統建立一套工具模組,將15次測量資料匯入工具模組中,將輸出各次測量之高程為0m等高線作為海灘濱線,將各次之0m濱線等分為50個點,取各點座標[X, Y],作為類神經網路之輸入資料。研究中利用NeuroSolution軟體建立倒傳遞類神經網路模組,將測量資料依照時間與空間不同分類為方案一與方案二,藉此比較各個沙灘間在不同時期之關係。由成果顯示,颱風事件時對沙灘而言,是造成墾丁國家公園內沙灘體積急遽變化的主要原因,但進入了落山風季節時,沙灘體積有漸漸恢復的趨勢。經由類神經網路比較各沙灘間變化之關係顯示,方案一除了船帆石在全年資料之測試階段的判定係數為0.74、雨季為0.87外其餘各沙灘均有高於0.9之判定係數。此外,在方案二所得成果中可知,當考慮全年資料與雨季資料時,以後壁湖資料為輸入條件時,船帆石之判定係數分別大於0.85與0.9,當僅以落山風季節資料建模時,則以後壁湖、南灣與大灣為輸入條件之組合得判定係數在0.9以上為最佳組合。
In this study, the survey an discussion are focused on the six beaches, Houpihu, Nanwan, Dawan, Shiauwan, Tsunfansu and Shadau, at Kenting National Park between March, 2010 to February, 2011. A tool has been developed by using geographic information system (GIS) for establishing zero meter elevation contour line and exporting fifty coordinate [X, Y] at equal distance for the input of artificial neural network (ANN). The ANN involved in the study was back propagation neural network model which is available in the NeuroSolution software. Based on the data obtained, the relationship between or among beaches were categorized into two scenarios. The results showed typhoon event is the main reason that affect beach volume change in Kenting National Park. However, it is also found the beach volume change will recover on downslope wind season. Through the results of ANN study to compare changes between beaches, scenario 1: coefficient of determination 0.74 from all year round data and 0.87 from rainy season data of Tsunfansu was the lowest while the other beaches were all higher than 0.9. In addition, scenario 2: the results showed when Houpihu data was applied as input, the Tsunfansu coefficient of determination is respectively about 0.85 and 0.9 for rainy season and all year round data. Only using data of downslope wind season, the best model performance was found by applying Houpihu, Nanwan and Dawan as input which the coefficient of determination was higher than 0.9