KEYWORDS: Mathematical modeling, Monte Carlo methods, Remote sensing, Geographic information systems, Roads, Data conversion, Data modeling, Analytical research, Landsat, Earth observing sensors
Prediction of farmland change is a basic work of farmland protection, and also provides basic data for land use
planning. According to non-linear characteristic of farmland change, a new method which employs Cellular Automata
and Logistic Regression Model to simulate and predict farmland change is discussed in this paper, and structure of
Logistic-CA Model and parameters calculation are analyzed. And then, taking Xiantao City as a case, Logistic-CA
Model mentioned in this paper was applied to simulate and predict farmland change in this area. Results show:
(1)Logistic-CA Model can get rid of disadvantages of traditional mathematic models and get higher accuracy in farmland
change prediction; (2)Logistic-CA Model can not only predict quantitative change of farmland, but also simulate pattern
evolvement of farmland; (3)Logistic-CA Model can simulate and predict farmland change in various scenarios, and give
evidences for establishing policies to protect farmland.
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