Share Email Print
cover

Proceedings Paper

A logistic-CA model for the simulation and prediction of cultivated land change by using GIS and RS
Author(s): Xinli Ke; Fulin Bian
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

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.

Paper Details

Date Published: 29 December 2008
PDF: 9 pages
Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853F (29 December 2008); doi: 10.1117/12.815752
Show Author Affiliations
Xinli Ke, Wuhan Univ. (China)
Fulin Bian, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 7285:
International Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Deren Li; Jianya Gong; Huayi Wu, Editor(s)

© SPIE. Terms of Use
Back to Top