基于回归克里格的生态水文无线传感器网络布局优化

doi:10.11867/j.issn.1001-8166.2012.09.1006

地球科学进展 ›› 2012, Vol. 27 ›› Issue (9): 1006 -1013. doi: 10.11867/j.issn.1001-8166.2012.09.1006

葛咏 ¹，王江浩 ^{1, 3}，王劲峰 ¹，晋锐 ²，胡茂桂 ^1

1.中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室，北京 100101;2. 中国科学院寒区旱区环境与工程研究所，甘肃兰州 730000; 3. 中国科学院大学，北京 100049

收稿日期:2012-05-18 修回日期:2012-07-10 出版日期:2012-09-10
通讯作者: 葛咏（1972-），女，新疆奎屯人,研究员，主要从事空间数据分析与质量评价研究.E-mail:gey@lreis.ac.cn
基金资助:
国家高技术研究发展计划重大项目“星机地综合定量遥感系统与应用示范（一期）”课题“遥感产品真实性检验关键技术及其试验验证”（编号：2012AA12A305）资助.

Regression Kriging Model-based Sampling Optimization Design for the Eco-hydrology Wireless Sensor Network

Ge Yong ¹, Wang Jianghao ^1,3, Wang Jinfeng ¹, Jin Rui ², Hu Maogui ^1

1.State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;2.Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences,Lanzhou 730000, China; 3.Graduate University of Chinese Academy of Sciences, Beijing 100049, China

Received:2012-05-18 Revised:2012-07-10 Online:2012-09-10 Published:2012-09-10

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在黑河上游八宝河流域建立自动化、时空协同、智能观测的生态水文无线传感器网络，实现分布式的地面观测，对于定量刻画流域尺度时空异质性较强的生态水文要素的动态特征及其不确定性具有重要意义。在观测网设计过程中，节点的空间布局将直接影响到无线传感器网络的观测水平。为准确捕捉流域内关键生态水文要素的时空变异性和场分布，探讨了一种基于回归克里格模型的空间采样布局优化方法，并以地表温度观测网优化为例，应用到八宝河流域生态水文无线传感器网络布局方案设计中。研究结果表明，该优化方法同时考虑了目标变量与环境变量之间的相关关系以及残差在空间上的自相关特征，可以同时优化目标变量的地理空间和属性空间。优化后的无线传感器网络可以较好地捕捉流域内生态水文要素的时空动态特征。

关键词: 采样优化, 回归克里格, 无线传感器网络, 黑河上游

The Babao River Basin is the upstream region of the Heihe River which is the second largest inland river basin in the arid regions of northwest China. To monitor the characteristics of space-time of the eco-hydrological processes in the Babao River Basin, this paper discussed a regression kriging modelbased sampling optimization method. Land surface temperature, as one of eco-hydrological variables in the Babao River Basin, has been exemplified. The experiment results demonstrate that this sampling optimization method can consider the relationship of target variable and environmental variables and the spatial autocorrelation of regression residuals to obtain the optimization design in the geographic space and attribute space simultaneously. The optimized WSN is more efficient to capture the temporal and spatial variations of the eco-hydrological variables for monitoring the eco-hydrology process in the Babao River Basin.

Key words: Babao River Basin, Sampling optimization, Regression Kriging, Wireless sensor network.

中图分类号:

TN919.3
P33

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