Progress in remote sensing monitoring of Mangrove carbon storage

  • role: First author第一作者
  • Affiliation:

    School of Marine Sciences, Guangxi University, Nanning530004, China

  • Email:dsw591603897@gmail.com
  • Introduction:邓淞文,研究方向为海洋遥感。E-mail:dsw591603897@gmail.com
DENG Songwen1,  
  • role: Corresponding author通信作者
  • Affiliation:

    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research of Chinese Academy of Sciences, Beijing100101, China

  • Email:yangfei@igsnrr.ac.cn
  • Introduction:杨飞,研究方向为生态灾害遥感。E-mail: yangfei@igsnrr.ac.cn
YANG Fei2*,  
  • Affiliation:

    School of Marine Sciences, Guangxi University, Nanning530004, China

WANG Yinghui1,  
  • Affiliation:

    School of Marine Sciences, Guangxi University, Nanning530004, China

ZHANG Wei1,  
  • Affiliation:

    School of Marine Sciences, Guangxi University, Nanning530004, China

WANG Wenhuan1

Resümee

Mangroves are important blue carbon ecosystems that play a key role in maintaining global marine carbon cycles and mitigating the rate of climate change. Remote sensing, due to its advantages of good repeatability, high resolution, and low cost, can better facilitate the monitoring and management of mangrove carbon resources. This study reviews the research progress of remote sensing-based mangrove carbon reservoirs and categorizes the development into three stages based on the research content and depth: the early exploration stage (2007—2012), which primarily focused on global mangrove mapping and the extraction of spatial structural information; the midterm application research stage (2013—2015), which estimated mangrove carbon stocks based on previous research achievements; and the comprehensive development stage (after 2016), characterized by improving accuracy in carbon stock estimation and a research focus on the impact mechanisms of environmental factors on mangrove carbon reservoirs. The current status of optical remote sensing and radar remote sensing methods is reviewed, and the degree of improvement in results through the fusion analysis of these two remote sensing techniques is explored. Furthermore, the performance of various mangrove carbon models in estimating carbon stocks and simulating carbon cycling in mangroves is discussed. From the two important carbon reservoirs of biomass and soil in mangroves, relevant research on their carbon stocks is reviewed. The biomass carbon reservoir is primarily composed of carbon stored in vegetation roots, stems, and leaves, and it is a major influencing factor in mangrove primary productivity. However, the biomass carbon stock is highly affected by human activities and natural influences, resulting in considerable fluctuations. The soil carbon reservoir, which accounts for approximately 49%—98% of the total carbon stock in mangroves, is the largest carbon reservoir in mangrove ecosystems. However, research on soil carbon reservoirs is relatively limited compared to biomass carbon reservoirs, primarily due to challenges in acquiring remote sensing data and dealing with complex optical characteristics. In consideration of the crucial role of mangrove ecosystems in carbon sequestration and the achievement of carbon-related goals, the need for improvements in applying mangrove carbon sinks to carbon accounting and statistics is analyzed, and the potential applications of unmanned aerial vehicle remote sensing technology and artificial intelligence in mangrove carbon stock estimation are explored.

Schlüsselwort

mangroves;remote sensing;Carbon model;Biomass carbon stock;Soil carbon stock;UAV remote sensing

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