[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2330":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"view_count":15,"doi":24,"paper":25,"created_at":52},2330,"An ensemble version of fire potential index (eFPI) integrating seasonal variability in sub-pixel fuel composition","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.isprsjprs.2026.09.010","Wildfire serves a critical function in shaping the structure, composition and processes of Earth’s ecosystems. However, anthropogenic climate change over the past century has catalyzed a shift in wildfire regimes, particularly in California, as evidenced by increases in the extent, frequency and severity of fires. The broad social-economic consequences of extreme wildfire events necessitate systematic frameworks that incorporate multi-source observations to support risk assessments and pre-fire interventions. This study presents an ensemble Fire Potential Index (eFPI) with multi-decadal Moderate Resolution Imaging Spectroradiometer (MODIS) and climatological data, along with a comprehensive validation of its accuracy in capturing wildfire susceptibility across Southern California between 2002 and 2024. The eFPI captures the fire susceptibility of both live and dead fuels by accounting for variability in ignitability and fuel moisture, while weighting fuel types according to their fractional coverage at the sub-pixel scale. Spectral mixture analysis was first applied on daily MODIS imagery at 500-m spatial resolution to quantify sub-pixel fractions of green vegetation (GV), non-photosynthetic vegetation (NPV) and substrate. Second, we adopted spatially-contiguous climate datasets and in-situ measurements to estimate the moisture content of live and dead fuels, which were subsequently synthesized with extinction coefficients and associated fractional coverage to produce daily estimates of fire potential. Our results indicate the eFPI, through spatially-explicit integration of sub-pixel fuel characteristics, demonstrated a promising capacity to discriminate between burned and unburned regions across Southern California (χ2 = 3247; AUC = 0.74). Substantial differences in antecedent FPI estimates were also found between fire and no-fire pixels, which facilitate short-term projections of fire risk in the absence of real-time remote sensing and climate data. This paper provides an integrative framework for wildfire risk assessments, and offers a new approach for land management and fire protection agencies for efficient pre-fire planning practices.","野火在塑造地球生态系统的结构、组成和过程方面发挥着关键作用。然而，过去一个世纪的人为气候变化催化了野火态势的转变，尤其是在加利福尼亚州，火灾范围、频率和严重程度的增加即为明证。极端野火事件所带来的广泛社会经济后果，要求建立系统性的框架，整合多源观测数据以支持风险评估和火灾前干预。本研究提出了一种集成火灾潜力指数（eFPI），基于多年代际的中分辨率成像光谱仪（MODIS）数据和气候数据，并对其在2002年至2024年间捕捉南加利福尼亚州野火易发性的准确性进行了全面验证。eFPI通过考虑可燃性和燃料含水量的变异性，捕捉活燃料和死燃料的火灾易发性，同时根据燃料类型在亚像元尺度上的覆盖比例对其进行加权。首先，对500米空间分辨率的每日MODIS影像应用光谱混合分析，以量化绿色植被（GV）、非光合植被（NPV）和基底物的亚像元比例。其次，我们采用空间连续的气候数据集和实地测量数据估算活燃料和死燃料的含水量，随后将其与消光系数及相关覆盖比例综合，生成每日火灾潜力估算。研究结果表明，eFPI通过空间显式整合亚像元燃料特征，在区分南加利福尼亚州过火区与未过火区方面展现出良好的能力（χ2 = 3247；AUC = 0.74）。火灾像元与无火像元之间的前期FPI估算值也存在显著差异，这有助于在缺乏实时遥感和气候数据的情况下进行火灾风险的短期预测。本文为野火风险评估提供了一个综合性框架，并为土地管理和消防机构开展高效的火灾前规划实践提供了一种新方法。",null,"ISPRS Journal of Photogrammetry and Remote Sensing","2026-09-10T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该研究聚焦野火潜势指数与遥感燃料组分反演，属生态与灾害遥感领域，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[19],{"name":10,"url":6},[21,22,23],"遥感监测","野火风险","植被覆盖","10.1016\u002Fj.isprsjprs.2026.09.010",{"doi":24,"openalex_id":26,"authors":27,"venue":10,"cited_by_count":15,"oa_url":44,"card":45,"direction":49,"ingested_from":51},"W7212194536",[28,31,34,37,39,41],{"name":29,"orcid":30},"Tuo Feng","https:\u002F\u002Forcid.org\u002F0000-0002-6417-3643",{"name":32,"orcid":33},"Dar A. Roberts","https:\u002F\u002Forcid.org\u002F0000-0002-3555-4842",{"name":35,"orcid":36},"Max A. Moritz","https:\u002F\u002Forcid.org\u002F0000-0002-8995-8893",{"name":38,"orcid":9},"S. Sweeney",{"name":40,"orcid":9},"Y. Zhan",{"name":42,"orcid":43},"Alan T. Murray","https:\u002F\u002Forcid.org\u002F0000-0003-2674-6110","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS092427162600451X\u002Fpdf",{"tldr":46,"method":47,"finding":48,"direction":49,"opportunity":50},"构建集成火灾潜力指数eFPI，融合亚像元燃料组成季节变化，评估南加州野火易发性。","MODIS日影像光谱混合分析、气候数据与实测燃料湿度，2002-2024年南加州","eFPI能有效区分火烧与未火烧区域（AUC=0.74），且火前FPI差异显著，可短期预测火险。","农业遥感与作物表型","可将亚像元燃料动态与机器学习结合，提升火险短期预测精度并推广至其他火险区域。","openalex","2026-09-13T23:30:26.097612Z"]