Resources Science ›› 2016, Vol. 38 ›› Issue (8): 1525-1537.doi: 10.18402/resci.2016.08.11

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Complex land use changes simulation in Ezhou City using cellular automata based on least squares support vector machine

YANG Jianxin1(), GONG Jian1,2(), LI Jiangfeng1   

  1. 1. School of Public Management,China University of Geosciences (Wuhan),Wuhan 430074,China
    2. Key laboratory of the Ministry of Land and Resources Law Evaluation,Wuhan 430074,China
  • Received:2015-05-11 Revised:2016-06-05 Online:2016-08-25 Published:2016-08-25

Abstract:

Here we validate the feasibility of gaining transformation rules for cellular automata modeling using Least Squares Support Vector Machine (LSSVM)methods,and apply it to the simulation and prediction of complex land use change. We took land use change information from 1991 to 2004 for Ezhou,Hubei as training data. With the application of LSSVM and Logistic Regression methods,we obtained two sets of transformation rules respectively. Comparison and analysis were made between them with the help of an enhanced ROC method. We then simulated land use scenarios for 2013 using a united LSSVM-CA model and predictions to 2020 and 2030. The results show that the LSSVM method has a better output than the Logistic Regression method in simulating the spatial distribution of land use types that have a large area and a complex change process,such as cultivated land,construction land,aquaculture land and other land. Compared with the actual land use scenarios in 2013,the precision of simulation output derived from the LSSVM-CA model is 0.80. The Kappa coefficient is 0.73,which is at a high level of consistency and better than the simulation results gained from Logistic-CA model. In the future,some districts will have a large demand of construction land and a large number of cultivated land will be occupied. Farmland in the eastern and southern low-hilly area will transform into forest land in a big way. We conclude that the LSSVM method can be used to obtain transformation rules in a cellular automata model and can gain a good result in simulating land use changes. The simulation results provide meaningful decision-making reference points for the study area in land planning,farmland protection and ecological environmental protection.

Key words: cellular automata, least squares support vector machine, land use, Ezhou City