摘要
森林蓄积量的精准估测在森林资源管理中至关重要,也是重要的监测指标之一。以云南省曲靖市沾益区为研究区,以云南松为研究对象,构建基于Landsat 9遥感影像光谱特征的随机森林蓄积量估测模型。以网格搜索算法优化后的随机森林估测模型实现区域尺度的蓄积量估测。结果表明:网格搜索算法可以实现对随机森林模型精度的提升,GS-RF估测模型的建模精度:R^(2)=0.67、RMSE=1.11;验证精度:R^(2)=0.69、RMSE=1.22,研究区云南松蓄积总量为3.599×10^(6)m^(3)。指出了总体呈现西部和东部较多,中部分布较少的状态,可能与土地利用有一定关联性,同时单位蓄积量差异不明显,总体分布有一定的空间异质性。研究构建的GS-RF蓄积量估测模型可以实现较大范围的云南松蓄积量估测,能为区域尺度蓄积量估测提供一种方法。
Accurate estimation of forest stock is crucial in forest resource management and is one of the important monitoring indicators.In this study,Zhanyi District,Qujing City,Yunnan Province,was taken as the study area,and Pinus yunnanensis was used as the study object to construct a stochastic forest accumulation estimation model based on the spectral features of Landsat9 remote sensing images.The random forest estimation model was optimized by grid search algorithm to achieve the regional scale estimation.The results show that the grid search algorithm can realize the improvement of the accuracy of the random forest model,and the modeling accuracy of the GS-RF estimation model is:R^(2)=0.67,RMSE=1.11;the validation accuracy is:R^(2)=0.69,RMSE=1.22,and the total accumulation of Pinus yunnanensis in the study area is 3.599×10^(6)m^(3).It points out that the overall distribution of Pinus yunnanensis is more in the west and east,and less in the center,which may have some correlation with the land use,while the difference of unit accumulation is not obvious,and the overall distribution has some spatial heterogeneity.The GS-RF accumulation estimation model constructed in the study can realize the estimation of Pinus yunnanensis accumulation in a large scale,and can provide a method for the estimation of accumulation at the regional scale.
作者
郑增方
Zheng Zengfang(Fire Prevention Section,Forestry and Grassland Bureau,Zhanyi District,Qujing City,Qujing 655331,Yunnan,China)
出处
《绿色科技》
2024年第9期125-129,共5页
Journal of Green Science and Technology
关键词
森林蓄积量
云南松
随机森林
网格搜索算法
forest stock volume
Pinus yunnanensis
random forest
Grid Search Algorithm
