spatiotemporal analysis

Accounting for Multiple Testing in the Analysis of Spatio-Temporal Environmental Data

The statistical analysis of environmental data from remote sensing and Earth system simulations often entails the analysis of gridded spatio-temporal data, with a hypothesis test being performed for each grid cell. When the whole image or a set of …

Extreme Anomaly Event Detection in Biosphere Using Linear Regression and a Spatiotemporal MRF Model

Detecting abnormal events within time series is crucial for analyzing and understanding the dynamics of the system in many research areas. In this paper, we propose a methodology to detect these anomalies in multivariate environmental data. Five …

Extreme anomaly event detection in biosphere using linear regression and a spatiotemporal MRF model

Detecting abnormal events within time series is crucial for analyzing and understanding the dynamics of the system in many research areas. In this paper, we propose a methodology to detect these anomalies in multivariate environmental data. Five …

Multivariate anomaly detection for Earth observations: A comparison of algorithms and feature extraction techniques

Today, many processes at the Earth's surface are constantly monitored by multiple data streams. These observations have become central to advancing our understanding of vegetation dynamics in response to climate or land use change. Another set of …

Reviews and Syntheses: An Empirical Spatiotemporal Description of the Global Surface-Atmosphere Carbon Fluxes: Opportunities and Data Limitations

Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of …

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of …

A Few Extreme Events Dominate Global Interannual Variability in Gross Primary Production

Understanding the impacts of climate extremes on the carbon cycle is important for quantifying the carbon-cycle climate feedback and highly relevant to climate change assessments. Climate extremes and fires can have severe regional effects, but a …

An Extended Approach for Spatiotemporal Gapfilling: Dealing with Large and Systematic Gaps in Geoscientific Datasets

Spatiotemporal observations in Earth System sciences are often affected by numerous and/or systematically distributed gaps. This data fragmentation is inherited from instrument failures, sparse measurement protocols, or unfavourable conditions (e.g. …

Carbon Cycle Extremes during the 21st Century in CMIP5 Models: Future Evolution and Attribution to Climatic Drivers

Climate extremes such as droughts and heat waves affect terrestrial ecosystems and may alter local carbon budgets. However, it still remains uncertain to what degree extreme impacts in the carbon cycle influence the carbon cycle-climate feedback both …

Climate-Mediated Spatiotemporal Variability in Terrestrial Productivity across Europe

Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from …