城市森林结构多样性预测冠下地面温度的潜力研究

Investigating the Potential of Urban Forest Structural Diversity in Predicting Understorey Surface Temperature

城市森林冠层具有调控城市森林微气候的能力,但现有研究尚未阐明冠层结构对冠下地面温度的影响及其预测潜力。文章基于无人机机载激光雷达(UAV-LiDAR)提取哈尔滨林业示范基地的城市森林冠层结构多样性特征指标,探究单一结构多样性特征对冠下地面温度的影响,以及结构多样性多因子组合对温度的预测潜力。结果表明:1)城市森林结构多样性的8个特征因子与冠下地面温度呈显著相关关系(P<0.05),其中深间隙(DG)、深间隙分数(DGF)、覆盖分数(CF)、间隙分数分布(GFP)表征了结构多样性的覆盖/开放度特征;冠层高度标准差(H_(std))、冠层高度最大值(H_(max))、95%分位点高度(ZQ_(95))表征了高度特征;垂直复杂指数(VCI)表征了异质性特征。2)城市森林冠层结构多样性的覆盖/开放度特征对冠下地面温度的响应更强(R^(2)为0.15~0.5),强于高度指标(R^(2)为0.14~0.19)以及异质性指标(R^(2)=0.14)。3)结合高度指标、覆盖/开放度指标以及异质性指标的多因子预测模型2(R^(2)=0.61,RMSE=0.51,MSE=0.26,AIC=62.74),对于冠下地面温度的预测性能更优。研究明晰了城市森林结构多样性的多因子变量及其特征组合预测冠下地面温度的潜力,为城市森林冠层结构调控内部小气候环境研究提供了科学参考。

Urban forest canopy has the ability to regulate the microclimate of urban forests,but existing studies have yet clarified the impact of canopy structure on the temperature beneath the canopy and its potential in prediction.This study,based on Unmanned Aerial Vehicle-Light Detection and Ranging(UAV-LiDAR),extracts indices of urban forest canopy structural diversity at the Harbin Forestry Demonstration Base and investigates the impact of individual structural diversity characteristics on the surface temperature beneath the canopy,as well as the potential of a multifactorial combination of structural diversity in temperature prediction.The results show that:1)Eight characteristic factors of urban forest structural diversity are significantly correlated with the temperature beneath the canopy(P<0.05).These characteristics include Deep Gap(DG),Deep Gap Fraction(DGF),Cover Fraction(CF),and Gap Fraction Profile(GFP),which characterize the coverage/openness of structural diversity,while Canopy Height Standard Deviation(H_(std)),Maximum Canopy Height(H_(max)),and the 95th Percentile Height(ZQ_(95))represent height characteristics,and the Vertical Complexity Index(VCI)represents the feature of heterogeneity;2)The coverage/openness of urban forest canopy structural diversity shows a stronger response to the surface temperature beneath the canopy(R^(2)values range from 0.15 to 0.5),which is higher than the response of height indicators(R^(2)values range from 0.14 to 0.19)and heterogeneity indicators(R^(2)=0.14);and 3)A multifactorial predictive model2,which combines height indicators,coverage/openness indicators,and heterogeneity indicators(R^(2)=0.61,RMSE=0.51,MSE=0.26,AIC=62.74),demonstrates superior predictive performance for the surface temperature beneath the canopy.This study clarifies the potential of multifactorial variables and their characteristic combinations relevant to urban forest structural diversity in predicting the surface temperature beneath the canopy,providing a scientific reference for the research on urban forest canopies regulating the microclimate.