基于遥感特征变量的高山松碳储量抽样估算

Sampling Estimation of Pinus densata Carbon Storage Based on Remote Sensing Feature Variables

以Landsat 8 OLI遥感影像为数据源,结合香格里拉市森林资源二类调查数据,在可靠性为95%,抽样精度分别为95%、90%、85%的3种情况下,基于遥感特征变量采用分层抽样对高山松碳储量进行估算,并与一般分层抽样、系统抽样结果进行比较分析。结果表明:遥感特征变量的筛选中,相关性最强的4个依次为11窗口第4波段信息熵(R11B4EN)、11窗口第4波段均值(R11B4ME)、11窗口第7波段协同性(R11B7HO)、11窗口第2波段二阶矩(R11B2SM)。在相同抽样设计精度下,抽样单元数量均呈现系统抽样>一般分层抽样>遥感分层抽样的规律。在95%和85%的抽样设计精度下,采用11窗口第2波段二阶矩(R11B2SM)的实际抽样精度最高,误差最小。可见,基于遥感特征变量的分层抽样可为森林碳储量调查提供参考。

Using Landsat 8 OLI remote sensing image as data source,combined with the second-class survey data of forest resources in Shangri-La City,stratified sampling was used to estimate the carbon storage of Pinus densata based on remote sensing characteristic variables under 3 conditions of 95% reliability and 95%,90% and 85% sampling accuracy respectively.The results are compared with those of general stratified sampling and systematic sampling.The results show as follows:In the screening of remote sensing feature variables,4 with the strongest correlation are successively the information entropy of the fourth band in the 11^(th) window(R11B4EN),the mean of the 4^(th) band in the 11^(th) window(R11B4ME),the synergy of the 7^(th) band in the 11^(th) window(R11B7HO),and the 2nd moment in the 2nd band in the 11^(th) window(R11B2SM).Under the same sampling design accuracy,the number of sampling units presents the rule of system sampling>general stratified sampling>remote sensing stratified sampling.Under the sampling design accuracy of 95% and 85%,the actual sampling accuracy is the highest and the error is the smallest when using the 11^(th) window second-band 2nd moment(R11B2SM).Therefore,stratified sampling based on remote sensing characteristic variables can provide reference forforest carbon storage investigation.