A Review of General Methods for Quantifying and Estimating Urban Trees and Biomass

编号 010034005

推送时间 20220425

研究领域 森林生态 

年份 2022 

类型 期刊 

语种 英语

标题 A Review of General Methods for Quantifying and Estimating Urban Trees and Biomass

来源期刊 forest

期 第340期

发表时间 20220415

关键词 iomass model;  forest carbon;  individual tree;  tree biomass;  tree model;  urban forest; 

摘要 Understanding the biomass, characteristics, and carbon sequestration of urban forests is crucial for maintaining and improving the quality of life and ensuring sustainable urban planning. Approaches to urban forest management have been incorporated into interdisciplinary, multifunctional, and technical efforts. In this review, we evaluate recent developments in urban forest research methods, compare the accuracy and efficiency of different methods, and identify emerging themes in urban forest assessment. This review focuses on urban forest biomass estimation and individual tree feature detection, showing that the rapid development of remote sensing technology and applications in recent years has greatly benefited the study of forest dynamics. Included in the review are light detection and ranging-based techniques for estimating urban forest biomass, deep learning algorithms that can extract tree crowns and identify tree species, methods for measuring large canopies using unmanned aerial vehicles to estimate forest structure, and approaches for capturing street tree information using street view images. Conventional methods based on field measurements are highly beneficial for accurately recording species-specific characteristics. There is an urgent need to combine multi-scale and spatiotemporal methods to improve urban forest detection at different scales. View Full-Text

服务人员 王璐

服务院士 蒋有绪

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