机器学习算法在城市绿地碳储量估算中的应用

Application of Machine Learning Algorithm in the Estimation of Carbon Storage in Urban Green Space

在“碳达峰”“碳中和”的时代背景下,低碳城市的建设方法引人深思;尤其是城市绿地,作为重要的城市基础设施之一,估算其碳储量受到越来越多的关注。遥感技术结合机器学习算法可有效提取数据关系,显著提高生态系统碳储量的估算效率。综述近年来陆地生态系统碳储量估算中机器学习算法的应用,梳理城市绿地碳储量评估的传统方法及局限性,总结遥感技术结合机器学习算法的技术框架,以期为城市绿地碳储量的估算提供新思路。

Under the background of"carbon peak"and"carbon neutrality",the construction methods of low-carbon cities are thought-provoking.In particular,urban green space,as one of the important urban infrastructures,has attracted more and more attention to estimate its carbon storage.Remote sensing technology combined with machine learning algorithm can effectively extract data relationships,and significantly improve the estimation efficiency of ecosystem carbon storage.The paper reviews the application of machine learning algorithm in the estimation of carbon storage of terrestrial ecosystem in recent years,combs the traditional methods and limitations of carbon storage estimation of urban green space,and summarizes the technical framework of remote sensing technology combined with machine learning algorithm,in order to provide new ideas for carbon storage estimation of urban greenspace.