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カリフォルニア州の山火事被害リスクマップを開発(UC Irvine Researchers Create California Wildfire Damage Risk Map)

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2026-07-27 カリフォルニア大学アーバイン校(UCI)

カリフォルニア大学アーバイン校(UC Irvine)の研究チームは、カリフォルニア州全域を対象とした100メートル解像度の建物被害リスクマップ「Wildfire Building Damage Risk Index(WBDRI)」を開発した。2013~2024年に実施された約10万件のCAL FIRE建物調査記録を解析した結果、約5万5,000棟が火災で全半壊し、その86%が森林と市街地が接するWUI(Wildland-Urban Interface)で発生していた。研究では、植生や地形、気象条件に加え、外壁材、フェンス、軒先など建物構造の可燃性を機械学習モデルに統合し、最大88%の予測精度を達成した。作成したリスクマップは建物被害の発生確率を連続的に示し、防火帯整備や植生管理、住宅の耐火改修などの優先順位付けに活用できる。特に被害確率が0.55を超える地域では対策投資の効果が高いとされ、土地利用計画や気候変動に対応した防災インフラ整備、地域の防災力向上を支援する実用的なツールとして期待される。

<関連情報>

カリフォルニアの山火事による建物の被害状況について解説 Explaining building damage from wildfires in California

Somnath Bar, Shu Li, and Tirtha Banerjee

Science Advances  Published:24 Jul 2026

DOI:https://doi.org/10.1126/sciadv.aed4197

カリフォルニア州の山火事被害リスクマップを開発(UC Irvine Researchers Create California Wildfire Damage Risk Map)

Abstract

A physically interpretable, data-driven framework was developed to elucidate causal interactions, model, and predict wildfire-induced building damage across California. More than 100,000 damage inspection records (2013 to 2024) were used to model building damage from static environmental variables (topography, vegetation, and human footprint), dynamic weather inputs, and a proposed Composite Building Flammability Rating (CBFR). Three model configurations were tested: (i) a comprehensive model integrating all variables, (ii) an enviro-weather hybrid excluding CBFR, and (iii) an environmental exposure model excluding both weather and CBFR. A strict 200-meter spatial dead-zone constraint was applied to eliminate local autocorrelation, and the comprehensive model achieved 88% (±0.4%) accuracy, which dropped to 82.9% (±0.6%) without CBFR and to 74.5% (±0.5%) without both weather and CBFR. Spatial grid-based cross-validation demonstrated a diverse accuracy of 68.0 (±17%), 66.0 (±16%), and 62.0 (±13%), respectively. Building flammability, dew point temperature, and near-surface wind speed were identified as the most important predictors of damage. Vapor pressure deficit had the strongest causal effect on damage probability, though spatial variability was observed in the causal effects of climate and geographic variables. A 100-meter-resolution Wildfire Building Damage Risk Index was also developed to highlight high-risk damage zones. Findings emphasize that wildfire impacts in the wildland-urban interface result from a confluence of structural vulnerability, atmospheric dryness, and fuel exposure, offering scalable tools for risk forecasting, defensible space planning, and climate-resilient infrastructure development.

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