Filtering by Subject: Longitudinal Data Analysis and Time Series
Published: 2022-02-28
Subjects: Applied Statistics, Geographic Information Sciences, Geography, Human Geography, Longitudinal Data Analysis and Time Series, Social and Behavioral Sciences, Spatial Science
Rural-urban classifications are essential for analyzing geographic, demographic, environmental, and social processes across the rural-urban continuum. Most existing classifications are, however, only available at relatively aggregated spatial scales, such as at the county scale in the United States. The absence of rurality or urbanness measures at high spatial resolution poses significant [...]
Published: 2021-11-09
Subjects: Earth Sciences, Longitudinal Data Analysis and Time Series, Speleology, Stratigraphy
The manual identification and count of laminae in layered textures is a common practice in the study of geological records, which can be time consuming and carry large uncertainty for dense or disturbed lamina textures. We present here a novel image analysis approach to detect and count laminae in geoscientific imagery, called WlCount. Based on Dynamic Time Warping and Wavelet analysis, WlCount [...]
Published: 2021-11-08
Subjects: Applied Statistics, Climate, Dynamic Systems, Earth Sciences, Geology, Longitudinal Data Analysis and Time Series, Multivariate Analysis, Non-linear Dynamics, Physical Sciences and Mathematics, Sedimentology, Statistical, Nonlinear, and Soft Matter Physics
Identifying and characterising dynamical regime shifts, critical transitions or potential tipping points in palaeoclimate time series is relevant for improving the understanding of often highly nonlinear Earth system dynamics. Beyond linear changes in time series properties such as mean, variance, or trend, these nonlinear regime shifts can manifest as changes in signal predictability, [...]
Published: 2021-08-20
Subjects: Environmental Monitoring, Longitudinal Data Analysis and Time Series
Time series reconstruction methods---used to generate gap-free time series of satellite observations---were historically designed for sensors with frequent image acquisitions. Since 2008, interest in leveraging time series methods has shifted from sensors such as AVHRR and MODIS to Landsat because of free, higher-resolution data availability and improved access to high-performance compute [...]
Published: 2021-07-13
Subjects: Aerospace Engineering, Atmospheric Sciences, Computational Engineering, Earth Sciences, Fluid Dynamics, Longitudinal Data Analysis and Time Series, Meteorology, Multivariate Analysis, Signal Processing
Atmospheric delay has a significant impact on synthetic aperture radar (SAR) interferometry, inducing spatial phase errors and decorrelation in extreme weather condition. For Low Earth Orbit (LEO) SAR missions, the atmosphere can be considered as being spatio-temporally frozen due to the short integration time. Geosynchronous (GEO) SAR missions, however, have short revisit times and extensive [...]
Published: 2021-06-08
Subjects: Applied Statistics, Atmospheric Sciences, Longitudinal Data Analysis and Time Series, Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability
This article presents state-of-the-art statistical learning methods for analyzing rain gauge data over the Natuna Islands. By using shape preserving piecewise cubic interpolation, we managed to interpolate 671 null values from the daily precipitation data. Dominant periodicity analysis of daily precipitation signals using Lomb-Scargle Power Spectral Density shows annual, intraseasonal, and [...]
Published: 2021-03-01
Subjects: Climate, Earth Sciences, Geology, Geomorphology, Hydrology, Longitudinal Data Analysis and Time Series, Other Earth Sciences, Sedimentology, Statistical Methodology, Stratigraphy
Changes in lake status are often interpreted as palaeoclimate indicators due to their dependence on precipitation and evaporation. The Global Lake Status Database (GLSDB) has since long provided a standardised synopsis of qualitative lake status over the last 30,000 14C years. Potential sources of uncertainty however are not recorded in the GLSDB. Here we present an updated and improved [...]
Published: 2018-02-15
Subjects: Categorical Data Analysis, Computer Sciences, Earth Sciences, Environmental Sciences, Geographic Information Sciences, Geography, Longitudinal Data Analysis and Time Series, Numerical Analysis and Scientific Computing, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Statistics and Probability
Monitoring global land cover changes is important because of concerns about their impact on environment and climate. The release by the European Space Agency (ESA) of a set of worldwide annual land cover maps covering the 1992–2015 period makes possible a quantitative assessment of land change on the global scale. While ESA land cover mapping effort was motivated by the need to better [...]