Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold

The annual flood and the alteration in hydrological regimes are the most vital concerns in the Vietnamese Mekong Delta (VMD). Although synthetic aperture radar (SAR) Sentinel-1 imagery is widely used for water management, only a few studies have used Sentinel-1 data for mapping surface water and monitoring flood events in the VMD. This study...

Sentinel-1 Backscatter Time Series for Characterization of Evapotranspiration Dynamics over Temperate Coniferous Forests

Forests’ ecosystems are an essential part of the global carbon cycle with vast carbon storage potential. These systems are currently under external pressures showing increasing change due to climate change. A better understanding of the biophysical properties of forests is, therefore, of paramount importance for research and monitoring...

An MBO scheme for clustering and semi-supervised clustering of signed networks

We introduce a principled method for the signed clustering problem, where the goal is to partition a weighted undirected graph whose edge weights take both positive and negative values, such that edges within the same cluster are mostly positive, while edges spanning across clusters are mostly negative. Our method relies on a graph-based...

Optimal Estimate of Global Biome: Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method

Terrestrial remote sensing data products retrieved from radiometric measurements in the optical and thermal infrared spectrum such as vegetation spectral indices can be heavily contaminated by atmospheric conditions, including cloud and aerosol layers. This contamination results in gaps or noisy observations. The harmonic analysis of time series...

Flood Extent Mapping in the Caprivi Floodplain Using Sentinel-1 Time Series

Deployment of Sentinel-1 (S1) satellite constellation carrying a $C$-band synthetic aperture radar (SAR) enables regular and timely monitoring of floods from their onset until returning to nonflooded (NF) conditions. The major constraint on using SAR for near-real-time (NRT) flood mapping has been the inability to rapidly process the obtained...

Forecasting Multi-Dimensional Processes Over Graphs

The forecasting of multi-variate time processes through graph-based techniques has recently been addressed under the graph signal processing framework. However, problems in the representation and the processing arise when each time series carries a vector of quantities rather than a scalar one. To tackle this issue, we devise a new framework and...

Clustering time series of repeated scan data of sandy beaches

Sandy beaches are highly dynamic areas affected by different natural and anthropogenic effects. Large changes, caused by a storm for example, are in general well-understood and easy to measure. Most times, only small changes, at the centimeter scale, are occurring, but these changes accumulate significantly over periods from weeks to months....

Policy reforms and productivity change in the judiciary system: A cost function approach applied to time series of the Dutch judiciary system between 1980 and 2016

The judiciary is constantly undergoing change in order to respond to a wide range of social developments that have brought the sector under increasing pressure. In order to deal with the constant call for enhancing budgets, different policy measures have been taken to downsize the appeal to the judiciary and to improve productivity. One of...

Steering Micro-Robotic Swarm by Dynamic Actuating Fields

We present a general solution for steering microrobotic<br/>swarm by dynamic actuating fields. In our approach, the<br/>motion of micro-robots is controlled by changing the actuating<br/>direction of a field applied to them. The time-series sequence<br/>of actuating field’s directions can be computed automatically.<br/>Given a target position in...

Analyzing the inundation pattern of the Poyang Lake floodplain by passive microwave data

The soil wetness condition is a useful indicator of inundation hazard in floodplains, such as the Poyang Lake floodplain. Special Sensor Microwave Imager (SSM/I) passive microwave data were used to monitor water-saturated soil and open water areas of the Poyang Lake floodplain from 2001 to 2008, capturing the inundation patterns of this area in...

Smooth Graphs for Visual Exploration of Higher-Order State Transitions

In this paper, we present a new visual way of exploring state sequences in large observational time-series. A key advantage of our method is that it can directly visualize higher-order state transitions. A standard first order state transition is a sequence of two states that are linked by a transition. A higher-order state transition is a...

Five Separate Bias Contributions in Time Series Models for Equidistantly Resampled Irregular Data

The use of time series models for irregular data requires resampling of the data on an equidistant grid. Slotted resampling transforms an irregular randomly sampled process into an equidistant signal where data are missing. An approximate maximum-likelihood time series estimator has been developed to estimate the power spectral density and the...

Modified Durbin Method for Accurate Estimation of Moving-Average Models

Spectra with narrow valleys can accurately be described with moving-average (MA) models by using only a small number of parameters. Durbin's MA method uses the estimated parameters of a long autoregressive (AR) model to calculate the MA parameters. Probably all the pejorative remarks on the quality of Durbin's method in the literature are based...

Constrained stochastic simulation: Generation of time series around some specific event in a normal process

The method of so-called constrained stochastic simulation is introduced. This method specifies how to efficiently generate time series around some specific event in a normal process. All events which can be expressed by means of a linear condition (constraint) can be dealt with. Two examples are given in the paper: the generation of stochastic...

State space modeling of groundwater fluctuations

Groundwater plays an important role in both urban and rural areas. It is therefore essential to monitor groundwater fluctuations. However, data that becomes available need to be analyzed further in order to extract specific information on the groundwater system. Until recently, simple linear time series models have been applied for this purpose....

Systems Analysis of Tides

Quite a long time the analysis of tidal observations has been based on the knowledge of the frequencies of the tidal components. These frequencies follow from an analysis of the tidal potentialor the tide generating force. This analysis also yields amplitudes and phases, but they are not equal to those of the real tidal components, called tqe...