ネパール・チュリア地域ラトゥワ川流域における土地被覆変化の要因と炭素貯留への影響
Drivers of Land Cover Change and Their Implications for Carbon Storage in the Ratuwa River Basin, Churia Region, Nepal (原題)
Sita Ram Kandel, Hari Prashad Joshi, Hari Prasad Ghimire, B. Pant
🤖 gxceed AI 要約
日本語
ネパール・チュリア地域のラトゥワ川流域を対象に、1990〜2020年の土地被覆変化の要因と炭素貯留への影響を分析。Random Forest分類とInVEST炭素モデルを用い、森林が25%減少し炭素貯留が252万トン（14.7%）減、年平均30.8万tCO₂の排出に相当すると推計。道路・集落への近接と人口密度が森林→農地転換の主要因で、REDD+資金による保全策を提言。
English
This study analyzes drivers of land cover change and carbon storage impacts in Nepal's Ratuwa River Basin (1990-2020) using Random Forest classification and the InVEST carbon model. Forest cover fell 25% and total carbon storage dropped 2.52 Mt (14.7%), equal to ~308,000 tCO2/yr, with forest-to-agriculture conversion causing 78% of losses. Road/settlement proximity and population density were key drivers; the authors recommend REDD+-financed, spatially targeted conservation.
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開示に直接関係する内容ではないが、Scope 3上流の土地利用変化・森林由来排出（FLAG）や自然資本・生物多様性開示（TNFD）を検討する日本企業にとって、地域レベルの炭素ストック変化の定量手法として参考になる。
In the global GX context
While regionally focused on Nepal, this work speaks to the growing global agenda on land-use emissions, FLAG (Forest, Land and Agriculture) accounting, and nature-related disclosure (TNFD). It offers a replicable remote-sensing plus InVEST methodology for quantifying carbon stock change relevant to REDD+ and supply-chain land-use footprinting.
👥 読者別の含意
🔬研究者:森林被覆変化と炭素貯留を統合的に定量するLULCC研究の手法（RF分類＋InVEST）と要因分析の実例として有用。
🏢実務担当者:農産物・林産物サプライチェーンを持つ企業が、上流の土地利用変化由来排出（FLAG/Scope 3）を評価する際の地域モデル例として参照可能。
🏛政策担当者:REDD+の成果連動型支払いや空間的に標的化した保全インセンティブ設計の根拠として、途上国森林政策に示唆を与える。
📄 Abstract（原文）
Land use and land cover change (LULCC) in the Churia region of Nepal has accelerated over recent decades, with uncertain consequences for carbon storage and climate regulation. This study examined the drivers of land cover change and quantified their implications for carbon storage in the Ratuwa River Basin (1,245 km²) from 1990 to 2020. Using Landsat imagery (1990, 2005, 2020) with a Random Forest classifier, we produced land cover maps achieving >88 % accuracy. Drivers were analysed using logistic regression and semi structured household interviews (n=90). Carbon storage was modelled using the InVEST carbon model, calibrated with field measurements from 150 sample plots. Forest cover declined by 25 % (17,031 ha), while agricultural land expanded by 35 % and settlements by 431 %. Proximity to roads (OR = 0.81 per km) and settlements (OR = 0.75 per km) and population density (OR = 1.45 per 100 persons km⁻²) were the strongest drivers of forest to agriculture conversion. Total carbon storage decreased by 2.52 million tonnes ( 14.7 %), equivalent to an average annual emission of 308,000 t CO₂. Forest to agriculture transitions accounted for 78 % of the carbon loss. Despite national forest recovery trends in Nepal’s mid hills, the Ratuwa Basin continues to lose carbon at an alarming rate. These findings highlight the urgent need for targeted conservation interventions. We recommend establishing a spatially explicit, incentive based programme that prioritises high carbon, high risk forests within 2 km of roads and settlements, combined with assisted natural regeneration of degraded shrublands, financed through REDD+ results based payments.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://journalsrj.com/article/drivers-of-land-cover-change-and-their-implications-for-carbon-storage-in-the-ratuwa-river-basin-churia-region-nepal-1/downloadfirst seen 2026-09-19 05:48:45 · last seen 2026-09-22 05:16:22
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