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【目的】分析城市森林冠层温度与地上生物量的空间关联特征，揭示冠层温度季节变化对地上生物量的影响，为城市森林碳汇评估与气候适应性规划提供科学依据。【方法】融合无人机机载激光雷达、多光谱与热红外影像，结合野外样地调查、异速生长模型与随机森林模型估算地上生物量，采用随机森林回归与地理加权回归(GWR)模型分析冠层温度变化对地上生物量的影响及其空间异质性。【结果】1)覆盖参数GFP是地上生物量估算的主导预测因子，地上生物量估算模型精度为R2=0.89,RMSE=2.96 kg·m-2。2)冠层平均温度与地上生物量呈负相关(P<0.01)。当冠层温度最大值大于30℃时，地上生物量下降速率加剧。3)温度影响存在非平稳性，南部呈现正效应，北部则为负效应，且温度影响强度指数(TDEI)高值区随着季节迁移，春季以正向响应为主，夏季则逐渐呈现负向响应特征，这一过程与夏季高温胁迫树木生长密切相关。【结论】年均冠层温度与地上生物量整体呈负相关，且温度敏感性存在明显的空间分异；TDEI在春夏季呈现时空迁移特征。因此，在冠层温度最大值超过30℃的夏季热极端高发区域，应优先布局郁闭度高、耐热性强的树种，从而缓解高温胁迫对地上生物量的抑制作用。未来研究需进一步拓展样本范围，涵盖不同气候区，并延长观测时间序列，从而更深入地解析“温度胁迫-结构适应-地上生物量积累”之间的动态关系，为城市森林管理提供更具科学性的依据。
Abstract：【Objective】The study analyzes the characteristics of spatial correlation between canopy temperature and above-ground biomass(AGB) in urban forests and reveals the impact of canopy temperature on AGB, aiming to provide scientific evidence for carbon sink evaluation and climate adaptability planning of urban forests. 【Method】 LiDAR, multispectral, and thermal infrared images are combined to estimate above-ground biomass along with field plot surveys, allometric growth models and random forest models. Ultimately, Random Forest Regression and Geographically Weighted Regression(GWR) models are employed to analyze the impact of canopy temperature variation on AGB and its spatial heterogeneity. 【Result】1) The Gap Fraction Profile(GFP) emerged as the dominant predictor for AGB estimation, yielding a model accuracy of R2 = 0.89 and RMSE = 2.96 kg·m-2. 2) Canopy mean temperature exhibited a significant negative correlation with AGB(P<0.01). When Tmax exceeded 30 ℃, the rate of AGB decline accelerated. 3) Temperature impacts demonstrated non-stationarity: positive effects in southern areas contrasted with negative effects in northern regions. The high-value zones of the Temperature-Dependent Ecosystem Intensity Index(TDEI) shifted seasonally. Spring showed predominantly positive responses, while summer transitioned to negative responses, closely linked to high-temperature stress inhibiting tree growth in summer. 【Conclusion】 Canopy mean annual temperature generally exhibits a negative correlation with above-ground biomass, while temperature sensitivity presents pronounced spatial heterogeneity. The TDEI demonstrates the characteristics of spatio-temporal migration from spring to summer. Therefore, in the summer hot-spot areas where canopy maximum temperature is higher than 30 ℃, species with high canopy density and heat tolerance should be prioritized, thereby mitigating the suppression of above-ground biomass by high-temperature stress. Future studies should further expand the sample range to cover different climate zones and prolong the observation time series, so as to make a deeper analysis of the dynamic “temperature stress-structure adaptation-above-ground accumulation” relationship and provide more scientific evidence for urban forest management.
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基本信息:
中图分类号:S771.8
引用信息:
[1]王涵宇,李若楠,翟雅琳,等.基于无人机多源遥感影像的城市森林冠层温度季节变化对地上生物量的影响[J].中国城市林业,2025,23(06):1-8.
基金信息:
国家自然科学基金面上项目(42171246)