Modeling and understanding the Earth system is a constant and challenging scientific endeavour. When a clear mechanistic model is unavailable, complex or uncertain, learning from data can be an alternative. While machine learning has provided …
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 …
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 …
The main objective of the current paper is to evaluate and explain differences between computed green-up dates of vegetated land surface derived from satellite observations and budburst dates from ground observational networks. Landscapes dominated …