Developing a science strategy and science priorities for FireSat, an upcoming high spatial and temporal resolution fire monitoring system
通过三场国际研讨会为FireSat卫星星座制定科学战略与研究优先事项。
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未标这个词，内容接近A Novel Data-Driven Framework for Stubble Burning Detection Using NASA FIRMS and Machine Learning
提出基于NASA FIRMS与机器学习的数据驱动框架，用于检测秸秆焚烧。
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Direct estimation of wildfire emissions at high latitudes from combined polar orbiter FRP and Sentinel-5P CO data
提出基于卫星观测的高纬度火灾排放估算方法HLFREM，直接关联辐射能与CO排放。
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Development of an Explainable GeoAI Wildfire Risk Analysis Model Using Multi-Source Geospatial Data
构建可解释GeoAI框架，融合多源地理数据评估土耳其野火风险并制图。
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Reducing redundancy in multi-temporal analysis to improve field-scale detection of crop residue burning
用多时相遥感与模糊机器学习减少重复检测，提升稻田秸秆焚烧田块尺度制图精度。
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Explainable GeoAI for urban wildfire structure loss: vegetation and built environment in the 2025 palisades fire
用可解释GeoAI建模2025年帕利塞兹火灾住宅损毁，强调空间验证。
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Advancing spatio-temporal fusion with spectral super-resolution for enhancing remote sensing of marine debris and landfills
提出融合Sentinel-2与PlanetScope的时空融合框架，结合光谱超分辨提升海洋垃圾与填埋
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Assessment of burn severity and vegetation recovery following the 2025 Palisades fire using Landsat-based spectral indices
用Landsat多时相光谱指数评估2025年Palisades火灾的烧毁严重度与植被恢复。
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