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丘陵地貌区高程内插适宜方法选择——以长春净月潭为例
引用本文:费龙,田秋艳.丘陵地貌区高程内插适宜方法选择——以长春净月潭为例[J].地理科学,2016,36(4):597-602.
作者姓名:费龙  田秋艳
作者单位:1.长春师范大学城市与环境科学学院,吉林 长春 130032
2.中国人民解放军装甲兵技术学院电子工程系,吉林 长春 130117
基金项目:吉林省科技发展计划项目(20130101114JC);吉林省教育厅十二五计划自然科学项目(吉教科合字[2014]第262号);长春师范大学自然科学基金项目(长师大自科合字[2010]第005号)资助~~
摘    要:对不同的地貌区进行空间内插时选择的适宜方法不同,以典型丘陵地貌区长春市净月潭地区的高程为研究对象,用ArcGIS 9.2分别作反距离权重法、最近邻点法、趋势面分析和克里金法做高程内插。应用交叉检验方法对其内插的精度作出分析,检验其科学性和可靠性,得出反距离权重法、最近邻点法、趋势面法、样条函数法和克里金法高程内插的不同精度,并对各种方法的适用性进行讨论。结果表明最近邻点法精度最高,以下依次为普通克里金插值法、样条函数、反距离权重法、趋势面法。为类似于净月潭地区的丘陵地貌区高程内插提供选择参考。

关 键 词:空间内插  反距离权重法  趋势面分析  克里金内插法  
收稿时间:2015-11-23
修稿时间:2016-02-29

The Choose of Altitude Interpolation Appropriate Methods at Hills Landform Area:Taking the Jingyuetan Area of Changchun as An Example
Fei Long;Tian Qiuyan.The Choose of Altitude Interpolation Appropriate Methods at Hills Landform Area:Taking the Jingyuetan Area of Changchun as An Example[J].Scientia Geographica Sinica,2016,36(4):597-602.
Authors:Fei Long;Tian Qiuyan
Affiliation:1.College of Urban and Environment Sciences, Changchun Normal University, Changchun 130032, Jilin, China
2. Department of Electronic Engineering, Armor Technique Institute of Chinese People’s Liberation Army, Changchun 130017, Jilin, China
Abstract:The suitable method used to realize spatial interpolation of different landforms is different. Elevation of Changchun Jingyuetan area is the research object, this area is typical hilly and gully region,we interpolated elevation with inverse distance weighting, nearest neighbor,trend interpolation and Kriging on ArcGIS9.2. We obtained the accuracy of elevation of inverse distance weighting method, nearest neighbor, trend surface method, spline function and Kriging with Cross Validation, the conclusion is the nearest neighbor is the most accurate, followed Kriging, spline function, elevation of inverse distance weighting method, trend surface method. This research provide reference of selection for interpolation of the elevation data such as Jingyuetan area of hill landform.
Keywords:spatial interpolation  IDW  trend interpolation  Kriging  
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