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玉米生育期空间插值方法比较
引用本文:杨 扬,杨建宇,李绍明,张晓东,朱德海.玉米生育期空间插值方法比较[J].农业工程学报,2009,25(9):163-167.
作者姓名:杨 扬  杨建宇  李绍明  张晓东  朱德海
作者单位:中国农业大学信息与电气工程学院,北京,100083
基金项目:“十一五”国家科技支撑计划重大项目(2006BAD10A01)
摘    要:采用合适的空间插值方法可以估计全国主产区玉米生育期的空间分布情况,从而指导不同地区的种植生产。该文通过比较反距离加权法、径向基函数法、克里格法等插值方法的异同,以调查县夏播玉米5个阶段的生育期为数据源,对黄淮海夏播玉米区生育期的数据进行空间插值处理,并使用交叉验证对表面精度进行分析。结果表明:播种期、出苗期和成熟期的最适合插值方法为径向基函数法,其均方根预测误差分别为5.077、5.320、5.243 d,拔节期和抽雄期的最佳插值方法为反距离加权法,其均方根预测误差分别为7.826、6.403 d;播种期和出苗期由西南至东北逐渐延后,其余阶段生育期以东南至西北为中轴线向两侧逐渐延后。

关 键 词:插值,人工智能,数值分析,玉米生育期,反距离加权法,径向基函数法,克里格法
收稿时间:2008/11/20 0:00:00
修稿时间:9/6/2009 12:00:00 AM

Comparison of spatial interpolation methods for maize growth period
Yang Yang,Yang Jianyu,Li Shaoming,Zhang Xiaodong and Zhu Dehai.Comparison of spatial interpolation methods for maize growth period[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(9):163-167.
Authors:Yang Yang  Yang Jianyu  Li Shaoming  Zhang Xiaodong and Zhu Dehai
Institution:College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China,College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China,College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China,College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China and College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Abstract:For guiding the cultivation of different regions, accurately estimating the maize growing period of the main maize-growing areas is of great significance. The different methods of interpolation principle were studied, such as inverse distance weighting(IDW), radial basis functions(RBF), and Kriging. Data source of five stages summer maize growing period was deal with spatial interpolation in the Huang-Huai-Hai summer maize area. The final surface accuracy was analyzed by the cross-certification. The results showed that in the sowing stage or seeding stage, or maturity stage, the most suitable method for interpolation was RBF, of which root-mean-squares were 5.077, 5.320, 5.243 d, while in the jointing stage and heading stage, interpolation of the best method was IDW, of which root-mean-squares were 7.826, 6.403 d. The distribution of sowing and seeding from southwest to northeast was gradually postponed, and the remaining stages of reproductive age, on both sides based on the axis of southeast and northwest were gradually postponed.
Keywords:interpolation  artificicial intelligence  numerical analysis  the maize growing period  inverse distance weighting  radial basis functions  Kriging
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