Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1073/pnas.2025400118 |
Monitoring war destruction from space using machine learning | |
Hannes Mueller; Andre Groeger; Jonathan Hersh; Andrea Matranga; Joan Serrat | |
2021-06-08 | |
发表期刊 | Proceedings of the National Academy of Science |
出版年 | 2021 |
英文摘要 | Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete, and potentially biased. This lack of reliable data imposes severe limitations for media reporting, humanitarian relief efforts, human-rights monitoring, reconstruction initiatives, and academic studies of violent conflict. This article introduces an automated method of measuring destruction in high-resolution satellite images using deep-learning techniques combined with label augmentation and spatial and temporal smoothing, which exploit the underlying spatial and temporal structure of destruction. As a proof of concept, we apply this method to the Syrian civil war and reconstruct the evolution of damage in major cities across the country. Our approach allows generating destruction data with unprecedented scope, resolution, and frequency—and makes use of the ever-higher frequency at which satellite imagery becomes available. |
领域 | 地球科学 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/329813 |
专题 | 地球科学 |
推荐引用方式 GB/T 7714 | Hannes Mueller,Andre Groeger,Jonathan Hersh,et al. Monitoring war destruction from space using machine learning[J]. Proceedings of the National Academy of Science,2021. |
APA | Hannes Mueller,Andre Groeger,Jonathan Hersh,Andrea Matranga,&Joan Serrat.(2021).Monitoring war destruction from space using machine learning.Proceedings of the National Academy of Science. |
MLA | Hannes Mueller,et al."Monitoring war destruction from space using machine learning".Proceedings of the National Academy of Science (2021). |
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