Acta Geographica Sinica ›› 2008, Vol. 63 ›› Issue (2): 156-164.doi: 10.11821/xb200802005

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Simulation on Spatial Land Use Patterns Using AutoLogistic Method: A Case Study of Yongding County, Zhangjiajie

WU Guiping, ZENG Yongnian, ZOU Bin, QI Qingchao, YANG Song   

  1. School of Info-Physics and Geomatics Engineering, Central South University, Changsha 410083, China
  • Received:2007-05-08 Revised:2007-10-08 Online:2008-02-25 Published:2008-02-25
  • Supported by:

    National Natural Science Foundation of China, No.40771198

Abstract:

Land use/land cover change (LUCC) is an important content of geographical research on global change today, while spatial simulation on regional land use patterns is one of the key contents of LUCC research because modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cover and the associated drivers. Spatial data, like land-use data, have a tendency to be dependent (spatial autocorrelation), which means that when using spatial models, a part of the variance may be explained by neighbouring values. The classic regression model can only analyze the correlation between land use types and driving factors, but cannot depict spatial autocorrelation. Land uses in Yongding County, which is one of the typical karst mountain areas in northwestern Hunan province, were investigated by means of modeling the spatial autocorrelation of land use types for the purpose of deriving better spatial land use patterns on the basis of terrain characteristics and infrastructural conditions. All driving factors such as distance to town, distance to river, distance to road, population density, altitude, slope and aspect were produced with ArcGis spatial analysis means. Then the weighting coefficient of every land use type was analysed with SPSS13.0. Through incorporating components describing the spatial autocorrelation into a classic Logistic model, this paper sets up a regression model (AutoLogistic model), which considers the spatial autocorrelation factor, and uses the model to simulate and analyze the spatial land use patterns in Yongding County. In addition, the results of two different models are validated by an ROC method. The ROC can compare a map of actual land use distribution to maps of modeled probability for land use types. Through comparison with the classic logistic model without considering the spatial autocorrelation, this model showed better goodness of fitting and higher accuracy of fitting. The ROC curves (AUC) of cultivated land, forest land, construction land and virgin land from classic Logistic regression model were 0.851, 0.913, 0.877 and 0.852 respectively. They were improved to 0.893, 0.940, 0.907 and 0.863 accordingly when using AutoLogistic model. It is argued that the improved model based on autologistic method is reasonable to some degree. At the same time, these types of analysis can provide valuable information for modeling future land use change scenarios that need to consider local and regional conditions of actual land use, and the probability maps of land use types obtained from this study can also support government decisions on land use management for Yongding County and similar areas.

Key words: spatial land use patterns, spatial simulation, AutoLogistic regression models, spatial autocorrelation, Yongding County of Zhangjiajie City