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当前位置: 首页 > 文章 > 基于局域统计量的黑龙江省多尺度森林碳储量空间分布变化 应用生态学报 2014,25 (9) 2493-2500
Position: Home > Articles > Multiple-scale analysis on spatial distribution changes of forest carbon storage in Heilongjiang Province,Northeast China based on local statistics Chinese Journal of Applied Ecology 2014,25 (9) 2493-2500

基于局域统计量的黑龙江省多尺度森林碳储量空间分布变化

作  者：
刘畅;李凤日;贾炜玮;甄贞
单  位：
东北林业大学林学院
关键词：
Moran指数;局域统计量;森林碳储量;空间分布
摘  要：
基于黑龙江省一类样地和生态公益林监测样地(共4163块)数据,应用局域Moran I及局域统计量(局域均值及局域标准差)检验4个尺度(25、50、100和150 km)下黑龙江省森林碳储量的空间分布模式、空间变异和空间相关性,并研究了2005和2010年森林碳储量的变化.结果表明:黑龙江省森林碳储量空间分布存在显著空间正相关,森林碳储量均为相似的变化,而且都不是空间随机发生的;研究区森林碳储量受周围环境因子影响,空间分布存在异质性,且变异较大.2005—2010年,年均森林碳储量空间分布变化存在较大差异,呈增长趋势.局域统计量是描述森林碳储量随着空间和时间变化的有效方法,可以通过ArcGIS使结果可视化.
译  名：
Multiple-scale analysis on spatial distribution changes of forest carbon storage in Heilongjiang Province,Northeast China based on local statistics
作  者：
LIU Chang;LI Feng-ri;JIA Wei-wei;ZHEN Zhen;College of Forestry,Northeast Forestry University;
关键词：
Moran index;;local statistics;;forest carbon storage;;spatial distribution
摘  要：
Taking 4163 permanent sample plots from Chinese National Forest Inventory( CNFI)and key ecological benefit forest monitoring plots in Heilongjiang Province as basic data,and by using local Moran I and local statistics( local mean and local standard deviation),the spatial pattern,spatial variation and spatial autocorrelation of forest carbon storage in Heilongjiang Province with four bandwidths of 25,50,100 and 150 km were investigated,and the change in forest carbon storage across 2005 to 2010 was studied. The results showed that the spatial distribution of forest carbon storage in Heilongjiang Province had significantly positive spatial correlation,which indicated that the changes of carbon storage tended to be similar with their neighbors without a non-random manner. Forest carbon storage was affected by environmental factors,and the spatial heterogeneity strongly existed with a large variation in the study area. The spatial distribution of forest carbon storage was significantly different between 2005 and 2010 with an increasing trend. Local statistics are useful tools for characterizing forest carbon storage change across time and space,which are visualized by ArcGIS.

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