Time series

AngleCam: Predicting the Temporal Variation of Leaf Angle Distributions from Image Series with Deep Learning

Vertical leaf angles and their variation through time are directly related to several ecophysiological processes and properties. However, there is no efficient method for tracking leaf angles of plant canopies under field conditions. Here, we present …

Performance of Singular Spectrum Analysis in Separating Seasonal and Fast Physiological Dynamics of Solar-Induced Chlorophyll Fluorescence and PRI Optical Signals

High temporal resolution measurements of solar-induced chlorophyll fluorescence (F) and the Photochemical Reflectance Index (PRI) encode vegetation functioning. However, these signals are modulated by time-dependent processes. We tested the …

Predicting Forest Cover in Distinct Ecosystems: The Potential of Multi-Source Sentinel-1 and -2 Data Fusion

The fusion of microwave and optical data sets is expected to provide great potential for the derivation of forest cover around the globe. As Sentinel-1 and Sentinel-2 are now both operating in twin mode, they can provide an unprecedented data source …

Time-Frequency Causal Inference Uncovers Anomalous Events in Environmental Systems

Causal inference in dynamical systems is a challenge for different research areas. So far it is mostly about understanding to what extent the underlying causal mechanisms can be derived from observed time series. Here we investigate whether anomalous …

A National Assessment of Wetland Status and Trends for Canada’s Forested Ecosystems Using 33 Years of Earth Observation Satellite Data

Wetlands are important globally for supplying clean water and unique habitat, and for storing vast amounts of carbon and nutrients. The geographic extent and state of wetlands vary over time and represent a dynamic land condition rather than a …

An Image Transform Based on Temporal Decomposition

Today, very dense synthetic aperture radar (SAR) time series are available through the framework of the European Copernicus Programme. These time series require innovative processing and preprocessing approaches including novel speckle suppression …

Detecting the Spread of Invasive Species in Central Chile with a Sentinel-2 Time-Series

The presented work evaluates the potential of a Sentinel-2 time-series to detect Pinus radiata (Monterey Pine) invasions in endemic Nothofagus (Southern Beeches) forests in the Maule region, central Chile. Suitable cloud free images of the …

Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series

© 2015 by the authors.Generating annual land cover maps in the tropics based on optical data is challenging because of the large amount of invalid observations resulting from the presence of clouds and haze or high moisture content in the atmosphere. …

Lake Water Footprint Identification from Time-Series ICESat/GLAS Data

To provide high-quality data for time-series change detection of lake water level, an automatic and robust algorithm for lake water footprint (LWF) identification is developed. Based on the Ice, Cloud, and Land Elevation Satellite GLA14 data file, …

State-Dependent Errors in a Land Surface Model across Biomes Inferred from Eddy Covariance Observations on Multiple Timescales

Characterization of state-dependent model biases in land surface models can highlight model deficiencies, and provide new insights into model development. In this study, artificial neural networks (ANNs) are used to estimate the state-dependent …