张景雄, MichaelFGoodchild. 野外空间采样的渐进式策略[J]. 武汉大学学报 ( 信息科学版), 2008, 33(5): 441-445.
引用本文: 张景雄, MichaelFGoodchild. 野外空间采样的渐进式策略[J]. 武汉大学学报 ( 信息科学版), 2008, 33(5): 441-445.
ZHANG Jingxiong, Michael F Goodchild. Towards Progressive Strategies for Spatial Sampling in the Field[J]. Geomatics and Information Science of Wuhan University, 2008, 33(5): 441-445.
Citation: ZHANG Jingxiong, Michael F Goodchild. Towards Progressive Strategies for Spatial Sampling in the Field[J]. Geomatics and Information Science of Wuhan University, 2008, 33(5): 441-445.

野外空间采样的渐进式策略

Towards Progressive Strategies for Spatial Sampling in the Field

  • 摘要: 介绍了有关地统计学(geostatistics)的基本理论,论述了顾及样本点位之间空间依赖性的空间采样方案的设计。基于总体上极大限度地降低克里金方差的思想,阐述了一个快速确立采样点位的序贯算法和块段克里金方法。由于野外作业的计算环境所限,数值方法和启发式搜索相结合的策略才是开发实用系统的明智选择。以假想数据为例,验证了所提算法的有效性。

     

    Abstract: The geostatistical basis for adaptive/progressive sampling is discussed,following an introduction to the necessary statistical background and developments in geographic information technologies.Where computational resources are limited,as they are in the field,strategies that combine heuristic and numerical approaches are the key to successful field implementation.A sequential algorithm for rapid location of further samples is formulated,using the criterion of maximum global reduction in Kriging variance.Results from a test confirm the effectiveness of the proposed algorithms.

     

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