林冠の炭素：コロナダル市の再造林地におけるリモートセンシングと森林インベントリデータを用いた地上部炭素蓄積評価
Carbon in the Canopy: An Aboveground Carbon Stock Assessment Using Remote Sensing and Forest Inventory Data of Reforested Sites in The City of Koronadal (原題)
Krizzel Jan A. Batislaon, Keth Lorenz Corre, Riz Jorich Franco, Zamantha Janylle Funa, Dannah Mae Pagod, Janne Paulo Panzo, Mia Joy A. Inocencio, Carlos F. Gaygay
🤖 gxceed AI 要約
日本語
フィリピン・コロナダル市の再造林地3地区を対象に、森林インベントリ調査とLandsat 9のNDVI解析を組み合わせ、地上部バイオマスと炭素蓄積を推定した研究。マホガニーが優占する地区で炭素蓄積が高い傾向が示され、NDVIと現地データの正の関係を確認。地方政府の森林管理や国家植林プログラムの基礎データとして活用可能と結論づけている。
English
This study estimates aboveground carbon stocks in three reforested barangays of Koronadal City, Philippines, combining field forest inventory (DBH, height, wood density) with Landsat 9 NDVI analysis. Mahogany-dominated sites showed higher biomass and carbon stocks, and NDVI correlated positively with field data. Results provide baseline data for local forest management and the National Greening Program.
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
日本企業のGX文脈では直接の接続は薄いが、Scope 3や自然資本・生物多様性開示（TNFD）に関心を持つ企業にとって、途上国再造林の炭素蓄積をリモートセンシングで定量化する手法は、クレジット調達やサプライチェーン上流の森林リスク評価の参考になり得る。
In the global GX context
While not tied to TCFD/ISSB disclosure frameworks directly, this work contributes to the growing body of MRV (measurement, reporting, verification) methods for nature-based carbon removals, relevant to voluntary carbon markets and emerging biodiversity/TNFD reporting. It offers a replicable remote-sensing + inventory approach for tropical reforestation carbon accounting.
👥 読者別の含意
🔬研究者:熱帯再造林地の炭素蓄積評価におけるNDVIと現地調査の統合手法の実証例として参考になる。
🏢実務担当者:自然資本・炭素クレジット調達を検討する企業にとって、途上国再造林プロジェクトのMRV手法の一例として活用可能。
🏛政策担当者:地方政府の植林プログラム評価や森林炭素モニタリング体制構築の基礎資料として示唆を与える。
📄 Abstract（原文）
Reforestation is an important component to mitigate climate change because trees absorb carbon from the air and store it in their biomass. But even though people know that reforestation is good for the environment, there isn’t enough local data on how much carbon is stored in these areas, which makes it hard to tell how well they work to fight climate change. This study helped to fix the deficiency of local carbon stock data in reforested areas within the City of Koronadal by employing forest inventory data and remote sensing techniques. The study employed a quantitative research design that integrated field-based forest measurements with remote sensing analysis. NDVI results showed a positive relationship with field data, indicating that remote sensing is a useful tool in measuring NDVI. Measurements were done on tree species, diameter at breast height (DBH), height, and wood density in 200 m perimeter Barangay San Isidro, Barangay Assumption and Barangay San Jose. Allometric equations were used to determine aboveground biomass, which was further transformed into carbon stock according to IPCC. The Landsat 9 satellite images were provided in QGIS and used to compute the Normalized Difference Vegetation Index (NDVI) and to evaluate vegetation cover. The findings indicate a difference between the sites with Barangay San Jose (0.16 t C/ha) and Barangay Assumption (NDVI 0.50) having higher biomass and carbon stock which are dominated mainly by Swietenia macrophylla (Mahogany) for monitoring forest biomass. The findings provide baseline information that can help local government units improve forest management such as the National Greening Program and support climate change mitigation efforts.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.54536/ijfe.v2i1.7697first seen 2026-09-19 05:09:51
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