基于空间自相关的区域农地变化驱动力研究——以珠三角地区为例
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曹祺文, 吴健生, 仝德, 张晓娜, 卢志强, 司梦林
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Drivers of regional agricultural land changes based on spatial autocorrelation in the Pearl River Delta,China
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CAO Qiwen,WU Jiansheng,TONG De,ZHANG Xiaona,LU Zhiqiang,SI Menglin
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| 表6 珠三角地区林地变化驱动力回归模型对比 |
| Table 6 Comparison of regression models for driving forces of forest |
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| 解释变量 | Logistic | AutoLogistic | 参数β值
估计 | 标准误差
SE | 检验统计量
Wald χ2 | Pr>χ2 | 发生比率 | 参数β值
估计 | 标准误差
SE | 检验统计量
Wald χ2 | Pr>χ2 | 发生比率 | | θ_preciptation | -0.001 04 | 0.000 9 | 1.233 | 0.267 | 0.998 9 | -0.000 27 | 0.001 1 | 0.064 | 0.801 | 0.999 7 | | θ_temperature | -2.335 57 | 1.447 0 | 2.607 | 0.106 | 0.096 8 | -1.134 94 | 1.507 7 | 0.567 | 0.452 | 0.321 4 | | θ_sunshine | -0.000 57 | 0.001 9 | 0.094 | 0.760 | 0.999 4 | 0.000 16 | 0.001 9 | 0.007 | 0.935 | 1.000 2 | | Elevation | -0.001 37 | 0.001 2 | 1.284 | 0.257 | 0.998 6 | -0.001 62 | 0.001 2 | 1.705 | 0.192 | 0.998 4 | | Slope | -0.070 50** | 0.016 7 | 17.778 | 0.000 | 0.931 9 | -0.063 08** | 0.017 2 | 13.497 | 0.000 | 0.938 9 | | Aspect | -0.039 22 | 0.114 4 | 0.118 | 0.732 | 0.961 5 | -0.080 62 | 0.120 4 | 0.448 | 0.503 | 0.922 5 | | OM | -0.003 00 | 0.001 6 | 3.394 | 0.065 | 0.997 0 | -0.002 55 | 0.001 6 | 2.390 | 0.122 | 0.997 5 | | Pop_density | 0.000 40** | 0.000 1 | 16.222 | 0.000 | 1.000 4 | 0.000 37** | 0.000 1 | 13.079 | 0.000 | 1.000 3 | | Rural_pop_density | 0.000 20 | 0.005 0 | 0.163 | 0.686 | 1.000 2 | 0.000 28 | 0.000 5 | 0.265 | 0.607 | 1.000 2 | | Invest | -8.83E-8 | 5.69E-8 | 2.409 | 0.121 | 0.999 9 | -9.75E-8 | 5.64E-8 | 2.985 | 0.084 | 0.999 9 | | Power | -0.04E-8** | 0.01E-8 | 9.064 | 0.003 | 0.999 9 | -0.01E-8 | 0.01E-8 | 1.057 | 0.304 | 0.999 9 | | GDP | 0.000 11** | 0.000 1 | 113.823 | 0.000 | 1.000 1 | 0.000 10** | 0.000 1 | 86.566 | 0.000 | 1.000 1 | | DIS2center | -0.08E-8 | 0.000 1 | 0.033 | 0.855 | 0.999 9 | -0.000 03 | 0.000 1 | 0.484 | 0.487 | 0.999 9 | | DIS2road | -0.000 15** | 0.000 1 | 8.119 | 0.004 | 0.999 8 | -0.000 11* | 0.000 1 | 4.085 | 0.043 | 0.999 8 | | DIS2railway | -0.000 03** | -0.08E-8 | 12.458 | 0.000 | 0.999 9 | -0.000 02* | 0.08E-8 | 3.954 | 0.047 | 0.999 9 | | DIS2residential | -0.000 03 | 0.000 1 | 1.052 | 0.305 | 0.999 9 | 0.000 01 | 0.000 0 | 0.179 | 0.672 | 1.000 1 | | DIS2river | -0.000 02 | 0.000 1 | 0.726 | 0.394 | 0.999 9 | -0.09E-8 | 0.000 1 | 0.091 | 0.763 | 0.999 9 | | Lag_forest | | | | | | 3.046 55** | 0.344 2 | 78.340 | 0.000 | 21.042 6 | | Lag_light | | | | | | -0.005 87* | 0.002 6 | 4.957 | 0.026 | 0.994 1 | | 常数Constant | -0.436 20 | 0.624 6 | 0.488 | 0.485 | 0.646 5 | -1.172 19 | 0.657 0 | 3.183 | 0.074 | 0.309 7 | | 模型参数 | LR χ2（17）=1 190.91;P=0.000
ROC=0.937 1;预测正确率PCP=90.20% | LR χ2（19）=1 273.22;P=0.000
ROC=0.949 5;预测正确率PCP=91.00% |
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