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基于GIS和PCA的冬小麦需水量影响因子分析
  • 期刊名称:武汉大学学报(工学版)
  • 时间:0
  • 页码:640-643
  • 语言:中文
  • 分类:S274.1[农业科学—农业水土工程;农业科学—农业工程]
  • 作者机构:[1]水利部中国农业科学院农田灌溉研究所、农业部作物需水与调控重点开放实验室,河南新乡453003
  • 相关基金:国家自然科学基金(编号:50609030);国家863计划(编号:2006AA100203,2006AA100209,2006AA100217).
  • 相关项目:作物需水的空间变异性及其支持向量机估算模型
中文摘要:

影响作物需水量的各因子之间由于存在相关性,不仅难以满足传统的回归分析方法对独立变量的要求,而且会影响大尺度数据处理的运行效率.采用主成分分析方法和GIS技术,对影响作物需水的主导因子进行识别分析.结果表明:热力因子和水分因子相互作用共同构成影响作物需水量的第1主成分,其空间分布呈西北到东南逐渐升高趋势;第2主成分主要为动力因子,基本上是从西向东逐渐增高;热力因子的生育期平均最高温度为第3主成分,在石家庄、邢台等地出现一相对低值区;而第4主成分坡向的空间分布没有明显规律,低值区与高值区相互交错,但都是在地形变化较大的地区,表明微地形也具有一定影响,但其贡献率仅为总信息量的6.64%,不考虑其影响也能反映华北地区冬小麦需水量空间分布大的趋势.

英文摘要:

It is difficult to estimate winter wheat water requirements with classical regression analysis method because there is obvious correlation among the influencing factors of crop water requirements. The principal components analysis method and the GIS technology are adopted to analyze the dominant factors influencing crop water requirement. The results indicate that the thermal factor and water factor jointly formed the first principal component of affecting crop water requirement; the spatial distribution of which increases gradually from northwest to southeast. As the second principal component, the dynamic factor increases gradually from west to east. The third principal component (thermal factor), the mean maximum temperature during wheat growth period appears a relative low value area in Shijiazhuang, Xingtai, etc. The spatial distribution of slope direction, as being the fourth principal component, has no obviously regularity; and the high value and low value of it staggers in the region with a great change of terrain. It is shown that the microtopography has some influences but its contribution rate occupies 6.64% of total information amount. Winter wheat water requirements in North China represent a great spatial distribution even if the effect of terrain is not considered.

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