AI 中文总结
研究利用地球观测数据进行处理几何与因果识别，介绍处理几何概念，通过多领域案例为将现实干预转化为可分析数据时的关键权衡提供指导，给出诊断重要几何决策的框架及综合问题。
AI 中文摘要
进行影响评估的核心任务是确定谁或什么受到了处理、何时受到处理以及受处理程度如何。在地理空间环境中，这些问题可能特别复杂，因为可能存在许多合理的暴露定义。本章介绍处理几何作为地理空间影响评估（GIE）的核心概念：数据中所表示的处理的时空足迹。这种足迹的定义方式塑造了识别策略和因果推断的可信度。通过跨越空气污染、野火、森林政策、基础设施、害虫和粮食安全文献的案例，本章为在将现实世界干预转化为可分析数据时出现的关键权衡（包括空间分辨率、时间对齐、溢出和边界不确定性）提供了实用指导。本章为研究人员提供了一个框架，用于诊断在其背景下哪些几何决策可能最为重要，并以综合问题结尾，以帮助读者应对这些决策。
英文摘要
A central task in conducting impact evaluations is determining who or what was exposed to a treatment, when, and to what degree. These questions can be especially complex in geospatial settings, where many reasonable definitions of exposure may exist. This chapter introduces treatment geometry as a core concept in geospatial impact evaluation (GIE): the spatial and temporal footprint of a treatment as represented in data. How this footprint is defined shapes identification strategies and the credibility of causal inference. Drawing on cases spanning the air pollution, wildfire, forest policy, infrastructure, pest, and food security literature, the chapter provides practical guidance on navigating key tradeoffs (including spatial resolution, temporal alignment, spillovers, and boundary uncertainty) that arise when translating real-world interventions into analyzable data. Rather than prescribing a single best approach, the chapter equips researchers with a framework for diagnosing which geometry decisions may matter most in their context, closing with synthesis questions to help readers navigate these decisions.
