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天然牧草生育期平均气温插值方法研究
引用本文:于士凯 姚艳敏 王德营 唐鹏钦 陈仲新 王道龙. 天然牧草生育期平均气温插值方法研究[J]. 中国农学通报, 2012, 28(32): 35-40
作者姓名:于士凯 姚艳敏 王德营 唐鹏钦 陈仲新 王道龙
作者单位:农业部农业信息技术重点实验室,北京100081;中国农业科学院农业资源与农业区划研究所,北京100081
基金项目:国家"973"计划子课题"气候变化对我国粮食生产资源要素的影响机理研究",国家科技基础性工作专项课题"大豆、牧草光温数据数字化图集编制"
摘    要:天然牧草生育期平均气温是牧草生长、生态环境保护等模型的重要参数。为了找出适宜天然牧草生育期平均气温的差值方法,以内蒙古自治区为研究区域,根据气温的垂直变化规律,将不同经纬度和海拔高度上的气象站点牧草生育期平均气温数据根据海拔高程投影到虚拟0海平面上,利用反距离插值(IDW)、样条函数(Spline)插值、克里金(Kriging)插值3种插值方法进行研究区域牧草生育期平均气温的空间分布推算,再运用DEM数据进行校正,比较分析最适宜的牧草生育期平均气温空间插值方法。3种插值方法平均误差为:IDW插值(-1.34%)>Spline插值(1.11%)>Kriging插值(0.36%);RMSE值:Kriging插值

关 键 词:造林  造林  
收稿时间:2012-07-26
修稿时间:2012-09-06

Study on the Average Temperature of Forage Growth Period Interpolation Method
Yu Shikai , Yao Yanmin , Wang Deying , Tang Pengqin , Chen Zhongxin , Wang Daolong. Study on the Average Temperature of Forage Growth Period Interpolation Method[J]. Chinese Agricultural Science Bulletin, 2012, 28(32): 35-40
Authors:Yu Shikai    Yao Yanmin    Wang Deying    Tang Pengqin    Chen Zhongxin    Wang Daolong
Abstract:

The average temperature of forage growth period is an important parameter for the model of grass crop growth and eco-environmental protection. In order to find out the optimum method for the average temperature interpolation of grass growth period, this paper takes the Inner Mongolia Autonomous Region as the study areas. First, according to the temperature vertical changing regularities, the average temperature data in pasture growth period of all climate sites were projected in different longitude and latitude to the virtual 0 sea level based on the latitude. Spline, IDW, Kriging interpolation methods were used to carry on the data interpolation. And then DEM data was used to conduct the temperature correction. The average errors of three interpolation methods were: IDW interpolation (-1.34%) > Spline Interpolation (1.11%) > the Kriging Interpolation (0.36%). The RMSE value: Kriging interpolation < IDW interpolation < Spline interpolation and the values were 0.36 < 0.69 < 0.74. The MAE value: Kriging interpolation < Spline Interpolation < IDW interpolation, the values were 0.14 < 0.33 < 0.35. The results showed that, Kriging interpolation was the optimum method for the average temperature interpolation of grass growth period via comparative analysis.

Keywords:

Inner Mongolia

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