基于遥感的森林碳储量显式计算模型

doi:10.11947/j.AGCS.2024.20230089

摘要/Abstract

摘要： 面向国家“双碳”目标和国际碳交易市场需求,陆地生态系统的固碳现状和未来固碳潜力亟须研究。森林是陆地生态系统中重要的碳库,目前基于地面观测的清查方法工作量大且抽样统计结果难以评价,基于卫星遥感反演的方法缺乏理论解释且普适性差。本文从单木级森林碳储量模型出发,提出一种基于遥感的森林碳储量显式计算模型。首先使用图像分辨率、森林郁闭度和森林高度3个关键变量构建森林碳储量显式计算模型,并对模型变量和参数进行误差分析;然后利用单木的生长特性,仿真不同饱和度的森林场景,从理论上解算不同树种的模型参数,并检验模型参数的精度与稳定性;最后验证模型在不同空间尺度、饱和度森林场景下的精度、稳健性和适用性。本文提出的森林碳储量模型解决了现有卫星遥感反演缺乏理论解释性和适用性差的难题,可实现大范围森林碳储量高分辨率制图和全球森林碳汇动态监测。

关键词: 森林碳储量, 遥感模型, 森林郁闭度, 森林高度, 仿真森林

Abstract: Facing the national carbon peaking and carbon neutrality goals, and the demand of international carbon trading market, the carbon sinks status and future carbon potential of terrestrial ecosystems are in urgent need of research. Forest is the important carbon sink in the terrestrial ecosystem, the method based on ground observation has a large workload and the sampling statistical results are difficult to evaluate, the method based on satellite remote sensing inversion lacks theoretical explanation and has poor universality. Based on the carbon storage model of single tree, this paper proposes an explicit forest carbon storage model. The forest carbon storage is expressed by remote sensing image resolution, vegetation coverage, and canopy height, the parameters are theoretically calculated by the characteristics of single trees. In order to verify the accuracy, robustness and applicability, forest simulation data under different conditions is constructed, the experimental results show the superiority of the model in various aspects, which can overcome the theoretical explanation in machine/deep learning inversion of forest carbon reserves, and realize high-resolution mapping of global forest carbon.

Key words: forest carbon storage, remote sensing model, forest canopy density, forest height, simulated forest

中图分类号:

P258

朱宁宁, 杨必胜, 董震. 基于遥感的森林碳储量显式计算模型[J]. 测绘学报, 2024, 53(1): 36-49.

ZHU Ningning, YANG Bisheng, DONG Zhen. The explicit model of forest carbon storage based on remote sensing[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(1): 36-49.

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