用卫星影像追踪全球光伏与风电建设，精度高达96%。
Global Renewables Watch: A Temporal Dataset of Solar and Wind Energy Derived from Satellite Imagery
- 用深度学习分析13万亿像素卫星图，识别可再生能源设施。
- 覆盖2017至2024年，定位37.5万台风力发电机和8.6万座光伏电站。
- 数据可用于政策制定，验证各国可再生能源部署进展。
我们构建了一个涵盖全球范围的时序数据集，基于高分辨率卫星影像，每季度从2017年第四季度至2024年第二季度，识别商业光伏电站和陆上风力涡轮机。通过训练深度学习分割模型，在超过13万亿像素的全球影像上部署，对每个检测到的设施估算建设时间及前期土地利用类型。最终数据集包含375,197个独立风力涡轮机和86,410个光伏安装单元。我们将结果聚合至国家层面，依据建设时间、光伏面积和风机数量估算总装机容量，与IRENA 2023年国家级数据相比，光伏和陆上风电的拟合度分别为r²=0.96和r²=0.93，验证了数据可靠性。该数据集为可持续发展目标评估提供了关键支持，是政策制定者与研究机构的重要资源。
原文摘要 · Abstract (English)
We present a comprehensive global temporal dataset of commercial solar photovoltaic (PV) farms and onshore wind turbines, derived from high-resolution satellite imagery analyzed quarterly from the fourth quarter of 2017 to the second quarter of 2024. We create this dataset by training deep learning-based segmentation models to identify these renewable energy installations from satellite imagery, then deploy them on over 13 trillion pixels covering the world. For each detected feature, we estimate the construction date and the preceding land use type. This dataset offers crucial insights into progress toward sustainable development goals and serves as a valuable resource for policymakers, researchers, and stakeholders aiming to assess and promote effective strategies for renewable energy deployment. Our final spatial dataset includes 375,197 individual wind turbines and 86,410 solar PV installations. We aggregate our predictions to the country level -- estimating total power capacity based on construction date, solar PV area, and number of windmills -- and find an $r^2$ value of $0.96$ and $0.93$ for solar PV and onshore wind respectively compared to IRENA's most recent 2023 country-level capacity estimates.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。