There has been growing interest in using satellite data in environmental economics research. This is because satellite data are available for any region across the globe, provide frequent data over time, are becoming available at lower cost, and are becoming easier to process. While satellite data have the potential to be a powerful resource, these data have their own sources of biases and error, which could lead to biased inference, even if analyses are otherwise well-identified. This article discusses the potential benefits and pitfalls of using satellite data for causal inference, focusing on the more technical aspects of using satellite data. In particular, I discuss why it is critical for researchers to understand the error distribution of a given satellite data product and how these errors may result in biased inference. I provide examples of some common types of error, including nonrandom misclassification, saturation effects, atmospheric effects, and cloud cover. If researchers recognize and account for these potential errors and biases, satellite data can be a powerful resource, allowing for large-scale analyses that would otherwise not be possible.

中文翻译：

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使用卫星数据进行因果推理的好处和陷阱

在环境经济学研究中使用卫星数据的兴趣日益浓厚。这是因为卫星数据可用于全球任何区域，随时间推移提供频繁的数据，以较低的成本可用，并且变得易于处理。尽管卫星数据有可能成为强大的资源，但是这些数据有其自身的偏差和误差来源，即使分析得到了很好的识别，也可能导致偏差推断。本文讨论了使用卫星数据进行因果推理的潜在好处和陷阱，重点是使用卫星数据的更多技术方面。特别是，我讨论了为什么对研究人员来说，了解给定卫星数据产品的误差分布以及如何使这些误差导致偏差推断至关重要。我提供了一些常见错误类型的示例，包括非随机错误分类，饱和度影响，大气影响和云层覆盖。如果研究人员认识到并解决了这些潜在的错误和偏见，卫星数据将成为一种强大的资源，从而可以进行大规模的分析，否则将无法进行分析。