Ecosystem Resilience Monitoring and Early Warning Using Earth Observation Data: Challenges and Outlook

Abstract
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.

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Details

Published: May 03, 2024
Vol/Issue: 46(2)
Pages: 265-301
License: View

Authors

Wanda De Keersmaecker

Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research (WUR), Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands

C

Cornelius Senf

Instituto de Ciencias Forestales ICIFOR (INIA‐CSIC) Madrid Spain

Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research (WUR), Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands

N

Niklas Boers

Funding

Technische Universität München

Cite This Article

Sebastian Bathiany, Robbin Bastiaansen, Ana Bastos, et al. (2024). Ecosystem Resilience Monitoring and Early Warning Using Earth Observation Data: Challenges and Outlook. Surveys in Geophysics, 46(2), 265-301. https://doi.org/10.1007/s10712-024-09833-z

Ecosystem Resilience Monitoring and Early Warning Using Earth Observation Data: Challenges and Outlook

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