土地利用/覆盖变化及其对森林碳收支影响研究综述  

Review of research on land use/cover change and its impact on forest carbon b

作　　者：黄子豪 杜华强[1,2,3] 李雪建 毛方杰[1,2,3] HUANG Zihao;DU Huaqiang;LI Xuejian;MAO Fangjie(State Key Laboratory of Subtropical Silviculture,Zhejiang A&F University,Hangzhou 311300,China;Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province,Zhejiang A&F University,Hangzhou 311300,China;School of Environmental and Resources Science,Zhejiang A&F University,Hangzhou 311300,China)

机构地区：[1]浙江农林大学省部共建亚热带森林培育国家重点实验室,杭州311300 [2]浙江农林大学浙江省森林生态系统碳循环与固碳减排重点实验室,杭州311300 [3]浙江农林大学环境与资源学院,杭州311300

出　　处：《遥感学报》2025年第1期49-69,共21页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金(编号:32171785,32201553);浙江省科技厅领雁项目(编号:2023C02035);百山祖国家公园科学研究项目(编号:2022JBGS02)。

摘　　要：土地利用/覆盖变化(LUCC)是影响陆地生态系统碳收支平衡的直接驱动因素,其对全球变暖的影响仅次于化石燃料和工业排放。森林是陆地生态系统中最大的碳库,在应对全球气候变化和实现碳中和目标中具有重要的作用。目前,有限的LUCC数据导致LUCC对碳排放的影响大大低估,同时缺乏未来气候背景下的LUCC时空分布,引起了森林碳循环对LUCC的响应研究面临诸多不确定性。如何模拟LUCC,分析LUCC对森林生态系统碳循环的影响是国内外研究的热点。本文系统归纳了国内外LUCC时空模拟方法、森林碳收支估算方法和LUCC对森林碳循环影响研究进展,并列举分析不同LUCC时空模拟、森林碳收支估算模型的优势、适用性、存在的问题。通过文献综述,指出以遥感数据为基础,模拟LUCC并驱动生态系统过程模型,实现森林生态系统碳循环时空精准模拟,是今后碳循环研究的发展趋势之一。Land Use/Cover Change(LUCC)is a direct driver of the carbon balance in terrestrial ecosystems,and its impact on global warming is second only to fossil fuel and industrial emissions.The forest ecosystem is the largest carbon pool in terrestrial ecosystems and has an important role to play in addressing global climate change and achieving carbon neutrality targets.However,the limited availability of LUCC data has led to a significant underestimation of its impact on carbon emissions,and the lack of spatiotemporal LUCC data under future climate scenarios also introduced considerable uncertainty in exploring the response of the forest carbon cycle to LUCC.How to simulate LUCC and analyze the impact of LUCC on the carbon cycle of forest ecosystems have become key research focuses both domestically and internationally.This study systematically reviewed the progress of research on past LUCC extraction,spatiotemporal LUCC simulations,forest carbon balance estimation methods,and the impact of LUCC on the forest carbon cycle.The advantages,applicability,and existing challenges of different LUCC simulation models and forest carbon balance estimation models were listed and analyzed.First,this review summarized historical LUCC extraction methods and highlights the urgent need to integrate deep learning techniques to improve the accuracy of LUCC change detection,thereby providing more reliable data for future LUCC simulations.Second,this review generalized the mainstream models for future LUCC spatiotemporal simulations.It emphasized the importance of coupling deep learning algorithms with the SD model while integrating meteorological and socioeconomic driving factors.This approach would more comprehensively account for feedback mechanisms between natural and anthropogenic factors,thereby enhancing the accuracy and applicability of simulations.Subsequently,this review organized the commonly used methods in current forest carbon cycle modeling and highlights recent developments in the field.It noted that carbon balance estimat

关 键 词：土地利用/覆盖变化 时空模拟模型 森林碳循环模型 碳中和 遥感 

分 类 号：TP701[自动化与计算机技术—检测技术与自动化装置] P2[自动化与计算机技术—控制科学与工程]