title: [Simulation of vegetation landscape in Pingtan Island based on BP neural network model].
abstract: Taking GIS as technical platform and by using Matlab 7.0, the vegetation landscape in Pingtan Island was cut with 2 km x 2 km grid graph. The data of 50 quadrats were obtained. Forty-four of the 50 quadrates were used for model training, and the rest 6 were used for model checking. Fractal dimension, Shannon diversity index, and contagion index were selected as output data of the model, and the number of residential quarter, wind speed, and the distance from the coast were chosen as affecting factors. A BP neural network model of vegetation landscape in Pingtan Island was established, and was checked by error test. The results demonstrated that the major factors affecting the vegetation landscape spatial pattern and diversity in Pingtan Island were wind speed and the distance from the coast, and anthropogenic factors had greater effects on the spatial connection of vegetation landscape. The fitted results of the relationships between vegetation landscape and environmental and anthropogenic factors were basically accorded with the truth. The average error was 7.4%, and the minimum error was 0.2%, indicating that the model could be applied to quantitatively predict and simulate the vegetation landscape in Pingtan Island.
authors.affiliation: College of Geographical Sciences, Fujian Normal University, Fuzhou 350012, China. fen198558@126.com
authors.forename: Xio-fen
authors.initials: XF
authors.lastname: Liu
authors.forename: Yi-xiong
authors.initials: YX
authors.lastname: Huang
authors.forename: Gong-fu
authors.initials: GF
authors.lastname: Ye
authors.forename: Li
authors.initials: L
authors.lastname: Chen
mesh_terms: D002681:China; D003198:Computer Simulation; D017753:Ecosystem; D040362:Geographic Information Systems; D006802:Human Activities; D016571:Neural Networks, Computer; D014197:Trees / Q000254:growth & development*; D014329:Tropical Climate