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標題: 細胞自動機與經驗模式模擬臺灣鄉鎮景觀格局變遷之差異比較
Compare the Difference of Landscape Patterns in Township Scale Simulated by CLUE-s and SLEUTH Models
作者: Chen-Fa Wu
Chu-Yu Huang
Yen-Fen Hsieh
Li-Pei Peng
關鍵字: Empirical model;Cellular automata model;Landscape pattern;Puli Township;CLUE-s;SLEUTH;景觀變遷;景觀指數;景觀格局
Project: 興大園藝, Volume 38, Issue 2, Page(s) 123-137.
Landscape change simulation models have been applied to discuss landscape change under various environment polices, to analysis impact on landscape pattern or bio-habitat. Some researches applied CLUE-s and SLEUTH models simulated landscape changed at urban or township areas in Taiwan. Differences of both models used to simulated landscape and landscape pattern change have not been discussed. Objective of this study is to compare the difference of landscape pattern in township scale simulated by CLUE-s and SLEUTH Models. A case study area was Puli Township located in central Taiwan. Results found that CLUE-s model is an empirical model base on landscape suitability. Soil, territory, social and economic factors impacted landscape suitability. Since Puli Township was a basin territory shown highly complex environment. Landscape pattern shows high fragmentation and highly mosaic among landscapes simulated by CLUE-s model. On the other hand, automata model, SLEUTH model, was an agent based model. Landscape change followed primarily landscape distribution, therefore landscape pattern shown aggregated simulated by SLEUTH model. Finally, a novel landscape change simulation method was set up. Result of landscapes area simulated by SLEUTH model input to CLUE-s model to simulate location of landscape change.

景觀變遷過程與格局是景觀生態學領域中相當重要的主題之一,其中細胞自動機理論為基礎的景觀/土地利用變遷模式 SLEUTH,及以機率理論為基礎的 CLUE-s 模式已廣泛應用於景觀/土地利用變遷模擬。本研究的目的在於比較細胞自動機(SLEUTH 模式)與經驗模式(CLUE-s 模式)模擬臺灣鄉鎮景觀格局變遷之差異。以埔里鎮為案例分析地區,研究結果顯示 CLUE-s 模式考量景觀變遷的影響因素較廣(土壤、地理、社會經濟因素),以各景觀類型的分佈適宜性為基礎,模擬的結果容易表現出環境差異產生景觀變化的現象,因此各種景觀類型間容易因為環境差異產生不同變化,以致於鑲嵌的現象較明顯。而 SLEUTH 模式以細胞擴張為基礎,景觀變遷模擬時是以現存的景觀分佈為起點向外擴張,因此模擬的景觀格局呈現聚集分佈的現象。未來的應用上,可整合兩個模型的優點,應用 SLEUTH 模式模擬未來面積數量,之後投入 CLUE-s 模式中,模擬變遷區位,可獲得兼具自體發展性及精確變遷區位之景觀分佈。
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