基于GIS的城市森林生物量抽样方法研究

GIS-based Sampling Method of Urban Forest Biomass

城市森林生物量中贮存了大量的碳,是反映城市森林生态系统功能的基本数据。针对城市森林空间破碎度高、聚集性与异质性强的特点,以南京市江宁区城市森林为研究对象,以2013年二类森林资源调查小班数据库为主要信息源,在抽样总体表面属性特征分析的基础上,分别利用传统抽样与空间抽样两种途径,进行森林生物量简单随机、空间分层,空间平衡等多种抽样方式的精度、成本、关联性、估计偏差分析。结果表明:1)从抽样成本来看,空间分层抽样与空间三明治抽样的调查成本最小; 2)从抽样误差和精度来看,空间三明治抽样误差最小、精度最高,空间简单抽样的误差最大、精度最低; 3)从空间关联性来看,空间抽样的样本间基本不存在空间相关性; 4)从抽样估计偏差来看,空间平衡抽样和系统抽样与统计值之间的估计偏差最小,空间分层抽样与空间三明治抽样次之。可见,在城市森林生物量抽样方法的选择上,可以优先考虑空间三明治抽样、空间平衡抽样。

The large amount of carbon is stored in urban forest biomass which is the basic data reflecting the function of urban forest ecosystem.In view of the characteristics of high fragmentation,aggregation and heterogeneity,urban forest in Jiangning District,Nanjing,was taken as the research object,while the data of forest resource management survey in 2013 were collected as the main information source.Followed by the analysis of general surface properties of sampling population,taking two approaches of traditional and spatial sampling,seven sampling methods of forest biomass in the study area,such as simple random sampling and spatial stratification sampling,spatial balanced sampling were conducted.Several indicators of accuracy,cost,correlation and deviation were calculated to evaluate the performance of seven sampling methods.The results show that:(1)From the viewpoint of sampling cost,the survey cost of spatial stratified sampling and sandwich sampling is the lowest;(2)From the sampling error and accuracy,the spatial sandwich sampling error is the smallest and the accuracy is the highest,while the spatial simple sampling error is the largest and the precision is the lowest;(3)For spatial correlation,there is no spatial correlation between sampling points of spatial sampling;(4)As to estimation error,the estimation deviation of spatial balanced sampling and system sampling is the smallest,followed by the spatial stratified sampling and spatial sandwich sampling.Therefore,the spatial sandwich sampling and spatial balanced sampling can be given the top priority.