构建全球造林数据集,评估位置信息可靠性,揭示多数项目存在地理数据缺陷。
A Global Dataset of Location Data Integrity-Assessed Reforestation Efforts
- 基于卫星影像与多源数据,标准化评估10项位置数据完整性指标。
- 79%的种植点在至少一项位置数据指标上不达标,15%项目无机器可读坐标。
- 数据集适用于碳市场监管与遥感图像分析任务,支持计算机视觉研究。
造林与再造林是通过增强碳封存来缓解气候变化的常见策略。然而,这些项目的有效性通常由开发者自我报告,或通过外部验证有限的认证流程进行确认,引发对数据可靠性和项目真实性的担忧。为应对自愿碳市场日益增加的审查压力,本研究整合原始(元)信息,并结合时序卫星影像及其他次级数据,构建了涵盖全球33年、45,628个项目的1,289,068个种植点的数据集。由于所有遥感验证均依赖于种植点地理边界的准确性,本数据集引入标准化的位置数据完整性评估,以单一可理解的指标——地理位置数据完整性评分(LDIS)进行总结。结果显示,约79%的被监测种植点在至少一项LDIS指标上未达标,而15%的监测项目根本缺乏机器可读的地理坐标数据。该数据集不仅有助于提升自愿碳市场的问责性,还可作为计算机视觉任务的训练数据,包含数百万张关联的Sentinel-2与Planetscope卫星图像。
原文摘要 · Abstract (English)
Afforestation and reforestation are popular strategies for mitigating climate change by enhancing carbon sequestration. However, the effectiveness of these efforts is often self-reported by project developers, or certified through processes with limited external validation. This leads to concerns about data reliability and project integrity. In response to increasing scrutiny of voluntary carbon markets, this study presents a dataset on global afforestation and reforestation efforts compiled from primary (meta-)information and augmented with time-series satellite imagery and other secondary data. Our dataset covers 1,289,068 planting sites from 45,628 projects spanning 33 years. Since any remote sensing-based validation effort relies on the integrity of a planting site's geographic boundary, this dataset introduces a standardized assessment of the provided site-level location information, which we summarize in one easy-to-communicate key indicator: LDIS -- the Location Data Integrity Score. We find that approximately 79\% of the georeferenced planting sites monitored fail on at least 1 out of 10 LDIS indicators, while 15\% of the monitored projects lack machine-readable georeferenced data in the first place. In addition to enhancing accountability in the voluntary carbon market, the presented dataset also holds value as training data for e.g. computer vision-related tasks with millions of linked Sentinel-2 and Planetscope satellite images.
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