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基于GIS的海洋底栖生物栖息密度空间插值方法
引用本文:刘春洋,李轶平,董婧.基于GIS的海洋底栖生物栖息密度空间插值方法[J].海洋环境科学,2012,31(3):443-447.
作者姓名:刘春洋  李轶平  董婧
作者单位:辽宁省海洋水产科学研究院,辽宁大连,116023
基金项目:辽宁省近岸海洋综合调查与评价专项
摘    要:在地理信息系统即GIS的支持下,分别采用反距离加权(inverse distance weighted,IDW)、普通克里格(ordinary krig-ing,OK)、规则样条(regularize spline,RS)和张力样条(tension spline,TS)4种插值方法对2006年7月获得的大连湾底栖生物栖息密度的数据进行空间插值处理,并对插值结果的精确度进行交叉验证,分析和比较不同插值方法获得的分布图。结果表明,插值精确度普通克里格>反距离加权>张力样条>规则样条;4种方法均能较客观的模拟出底栖生物栖息密度的分布趋势,但是在整体趋势和局部趋势两方面的综合考虑下,普通克里格的表现效果更好。文章进一步指出,在确定站位数量及分布前提下,插值结果的精确度可以通过选择空间插值方法得以改善,但其根本还是取决于站位布置的数量和其分布合理性。

关 键 词:GIS  底栖生物  栖息密度  空间插值

Study on spatial interpolation method of benthos density based on GIS
LIU Chun-yang , LI Yi-ping , DONG Jing.Study on spatial interpolation method of benthos density based on GIS[J].Marine Environmental Science,2012,31(3):443-447.
Authors:LIU Chun-yang  LI Yi-ping  DONG Jing
Institution:(Liaoning Ocean and Fisheries Science Research Institute,Dalian 116023,China)
Abstract:Under the acgis of Geostatistics and Geographic Information Systems,four interpolation methods including Inverse distance weighting(IDW),Ordinary Kriging(OK),Regularize Spline(RS) and Tension Spline(TS) are devoted to the spatial interpolation of density belong to the bentho,which obtained at DaLian Bay in 2006 Jul.At the Cross-validation linked to the accuracy of the interpolation results and analysis of the distribution maps were made.It was obtained from different methods.The conclusion shows the accuracy tendency,Ordinary Kriging>Inverse distance weighting>Tension Spline>Regularize Spline.From the observation of the distribution maps,four methods mentioned above can simulate the accuracy tendency of the benthos’ density objectively.However,the overall and local trend into account,the representation of Ordinary Kriging is the best.The investigation also showed that the accuracy of the interpolation results can be improved by option of the spatial interpolation methods,when the number and distribution of berths are unalterable.
Keywords:GIS(lgeographic information systems)  benthos  density  spatial interpolation
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