As the Earth system is exposed to large anthropogenic interferences, it becomes ever more important to assess the resilience of natural systems, i.e., their ability to recover from natural and human-induced perturbations. Several, often related, measures of resilience have been proposed and applied to modeled and observed data, often by different scientific communities. Focusing on terrestrial ecosystems as a key component of the Earth system, we review methods that can detect large perturbations (temporary excursions from a reference state as well as abrupt shifts to a new reference state) in spatio-temporal datasets, estimate the recovery rate after such perturbations, or assess resilience changes indirectly from stationary time series via indicators of critical slowing down. We present here a sequence of ideal methodological steps in the field of resilience science, and argue how to obtain a consistent and multi-faceted view on ecosystem or climate resilience from Earth observation (EO) data. While EO data offers unique potential to study ecosystem resilience globally at high spatial and temporal scale, we emphasize some important limitations, which are associated with the theoretical assumptions behind diagnostic methods and with the measurement process and pre-processing steps of EO data. The latter class of limitations include gaps in time series, the disparity of scales, and issues arising from aggregating time series from multiple sensors. Based on this assessment, we formulate specific recommendations to the EO community in order to improve the observational basis for ecosystem resilience research.

由于地球系统受到巨大的人为干扰，评估自然系统的恢复力（即它们从自然和人为扰动中恢复的能力）变得越来越重要。不同的科学界通常已经提出了几种通常相关的复原力衡量标准，并将其应用于建模和观测的数据。着眼于作为地球系统关键组成部分的陆地生态系统，我们回顾了能够检测时空数据集中的大扰动（从参考状态暂时偏离以及突然转变到新参考状态）的方法，估计之后的恢复率此类扰动，或通过严重放缓指标间接评估固定时间序列的弹性变化。我们在此提出了复原力科学领域的一系列理想方法步骤，并讨论了如何从地球观测（EO）数据中获得有关生态系统或气候复原力的一致且多方面的观点。虽然 EO 数据提供了在高时空尺度上研究全球生态系统复原力的独特潜力，但我们强调了一些重要的局限性，这些局限性与诊断方法背后的理论假设以及 EO 数据的测量过程和预处理步骤有关。后一类限制包括时间序列的间隙、尺度的差异以及聚合多个传感器的时间序列所产生的问题。基于此评估，我们向 EO 界提出具体建议，以改善生态系统复原力研究的观测基础。