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広東省沿岸におけるマングローブブルーカーボン吸収源の評価と予測:リモートセンシングとモデリングの統合

Assessment and projection of mangrove blue carbon sink along the Guangdong coastline: integrating remote sensing and modeling techniques (原題)

Hafiz Hassan Javed, You‐Shao Wang, Hao Cheng, ABD Ullah

Ecological Indicators📚 査読済 / ジャーナル2026-09-25#気候科学Origin: CN
DOI: 10.1016/j.ecolind.2026.115559
原典: https://doi.org/10.1016/j.ecolind.2026.115559

🤖 gxceed AI 要約

日本語

広東省沿岸のマングローブを対象に、衛星時系列データとInVEST・CA-Markovモデルを統合し、1994〜2024年の炭素貯留変化を評価するとともに2034年まで予測した。2014〜2024年に面積が10.71%拡大し、2034年にはさらに19.45%増加、炭素貯留は2024年比24.62%増と推定された。沿岸空間計画やカーボンニュートラル目標、自然基盤型解決策に資する再現可能な枠組みを提示する。

English

Integrating satellite time-series with InVEST and CA-Markov models, this study assesses and projects mangrove blue carbon storage along Guangdong's coastline from 1994 to 2034. Mangrove area expanded 10.71% during 2014–2024, with a projected 19.45% further increase and a 24.62% rise in carbon storage by 2034. It offers a scalable framework for coastal planning and nature-based climate mitigation.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本でもブルーカーボンはJ-クレジット制度や港湾・沿岸域の脱炭素施策で注目されており、リモートセンシングとモデルを組み合わせた評価手法は、国内の沿岸自治体や企業の自然基盤型クレジット創出の参考になる。ただし開示制度やSSBJとの直接の接続は薄い。

In the global GX context

Blue carbon is increasingly recognized under global nature and climate frameworks (e.g., SBTN, TNFD, and voluntary carbon markets), yet it remains peripheral to TCFD/ISSB disclosure. This paper's integrated remote-sensing and modeling approach contributes a transferable methodology for quantifying and projecting coastal carbon sinks, relevant to nature-based solutions and national carbon-neutrality accounting.

👥 読者別の含意

🔬研究者:リモートセンシングと土地利用モデルを統合したブルーカーボン評価の再現可能な枠組みを提供する。

🏢実務担当者:沿岸域の自然基盤型クレジットやカーボンオフセット戦略を検討する企業にとって、評価手法の参考になる。

🏛政策担当者:沿岸空間計画やカーボンニュートラル目標に向けたマングローブ保全・拡大政策の科学的根拠を提供する。

📄 Abstract(原文)

Mangrove ecosystems along the Guangdong coastline serve as a vital blue carbon sink, yet their carbon sequestration potential under changing climatic conditions requires rigorous assessment and forward-looking evaluation. This study develops an integrated framework combining remote sensing techniques and spatial modeling approaches to quantify historical changes and project future trajectories of mangrove blue carbon stocks in Guangdong Province, China. Time-series satellite imagery was used to quantify changes in mangrove extent and associated carbon storage over the period 1994 to 2024. Field-validated sediment core data, coupled with the InVEST and CA-Markov models, were utilized to assess historical carbon storage and forecast future challenges along the coastline. Our results reveal substantial spatial variability in mangrove carbon storage across Guangdong. A non-significant increase in mangrove area was observed during the first decade of the study period (1994–2004). In contrast, a significant area expansion of 10.71% occurred between 2014 and 2024, with projections indicating a further increase of 19.45% by 2034. The eastern coast of Guangdong exhibited greater potential for mangrove expansion than the western coast. Based on the projected mangrove extent and the adopted carbon-density framework, the InVEST model estimated a potential 24.62% increase in mangrove carbon storage by 2034 relative to 2024. By explicitly integrating spatiotemporal remote sensing analysis with predictive land-use and carbon storage modeling, this study advances a scalable and transferable framework for assessing mangrove blue carbon dynamics under climate and development pressures. The findings provide critical evidence to inform adaptive coastal management, strengthen Guangdong's carbon neutrality goals, and support nature-based solutions for climate mitigation. Overall, this integrated approach provides a robust scientific basis for coastal spatial planning and offers actionable insights for conserving and enhancing mangrove blue carbon resources along this ecologically and economically important coastline.

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