应用生态学报2017，Vol.28Issue(8)：2527-2534,8.DOI:10.13287/j.1001-9332.201708.007
基于区域剖分算法的土壤碳通量空间采样策略
A spatial sampling strategy for soil carbon flux estimation based on the region division
摘要
Abstract
Regional soil carbon flux can not be accurately estimated using traditional sampling methods due to the strong spatial heterogeneity of its spatial distribution,so it is significant to determine appropriate sampling strategies for the estimation of regional soil carbon flux.In this paper,a point-by-point incremental sampling strategy,region division based on point-growing (RDPG),was proposed.According to RDPG,initial sampling points were set firstly,the Delaunay triangulations were constructed using an improved convex hull interpolation algorithm,the discrete degree values at the intersection points of each side perpendicular bisectors of triangles were calculated with interpolation based on known values of sampling points,and then the point with the biggest discrete degree was chosen as a new sampling point.Using the RDPG method,multiple experiments were carried out in some simulation fields with coefficients of variation from 0.42 to 0.59.The results showed that,based on the same experimental conditions,compared with random sampling and uniform sampling strategies,the RDPG strategy could lead to higher accuracy of regional soil carbon flux estimation.The RDPG strategy took the spatial heterogeneity of soil carbon flux into account,which improved the fitting accuracy of regional soil carbon flux.关键词
土壤呼吸/碳通量/区域剖分/采样策略Key words
soil respiration/carbon flux estimation/region division/sampling strategy.引用本文复制引用
李楠,莫路锋,王国英,周健,高洪娣..基于区域剖分算法的土壤碳通量空间采样策略[J].应用生态学报,2017,28(8):2527-2534,8.基金项目
本文由国家自然科学基金项目(61190114,61303236)、浙江省科技计划项目重大科技专项(2012C13011-1)和浙江省省院合作林业科技项目(2015SY12)资助 This work was supported by the National Natural Science Foundation of China (61190114,61303236),the Major Science and Technology Project of Zhejiang Province (2012C13011-1) and the Cooperative Project of Zhejiang Province and Chinese Academy of Forestry(2015SY12). （61190114,61303236）
