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目前农作物区域产量保险风险区划相关研究中,大多是选取几个主导指标,然后使用聚类分析进行划分。若指标更全面、数量更多且类别丰富,则不适宜直接进行聚类。本文以湖北水稻为例,选取气候、灾害、地形、水利、产量等6类共12个指标,联合运用因子分析和聚类分析,划分湖北中稻县域产量保险风险区划,效果较好。实证结果表明,鄂西北风险较高,鄂东南和鄂西南风险中等,其他地区风险较低。
At present, most regional crop insurance risk zoning related research, select a few dominant indicators, and then use cluster analysis to divide. If the indicators are more comprehensive, more quantitative and rich in categories, it is not suitable for direct clustering. Taking Hubei rice as an example, this paper selects 12 indicators of 6 categories, such as climate, disaster, topography, water conservancy, yield and so on. By combining factor analysis and cluster analysis, this paper divides the output risk insurance risk zoning of Hubei Midao and has good effect. The empirical results show that there is a higher risk in northwestern Hubei Province, a moderate risk in southeastern Hubei and southwestern Hubei, and a lower risk in other areas.