Interpolation in time series: An introductive overview of existing methods, their performance criteria and uncertainty assessment
A thorough review has been performed on interpolation methods to fill gaps in time-series,
efficiency criteria, and uncertainty quantifications. On one hand, there are numerous …
efficiency criteria, and uncertainty quantifications. On one hand, there are numerous …
What we talk about when we talk about seasonality–A transdisciplinary review
O Kwiecien, T Braun, CF Brunello, P Faulkner… - Earth-Science …, 2022 - Elsevier
The role of seasonality is indisputable in climate and ecosystem dynamics. Seasonal
temperature and precipitation variability are of vital importance for the availability of food …
temperature and precipitation variability are of vital importance for the availability of food …
[图书][B] Singular spectrum analysis with R
Singular spectrum analysis (SSA) is a well-known methodology for analysis and forecasting
of time series. Since quite recently, SSA was also used to analyze digital images and other …
of time series. Since quite recently, SSA was also used to analyze digital images and other …
Filling the data gaps within GRACE missions using singular spectrum analysis
Dozens of missing epochs in the monthly gravity product of the satellite mission Gravity
Recovery and Climate Experiment (GRACE) and its follow‐on (GRACE‐FO) mission greatly …
Recovery and Climate Experiment (GRACE) and its follow‐on (GRACE‐FO) mission greatly …
Singular spectrum analysis: methodology and comparison
H Hassani - 2007 - mpra.ub.uni-muenchen.de
In recent years Singular Spectrum Analysis (SSA), used as a powerful technique in time
series analysis, has been developed and applied to many practical problems. In this paper …
series analysis, has been developed and applied to many practical problems. In this paper …
Sparse mobile crowdsensing with differential and distortion location privacy
Sparse Mobile Crowdsensing (MCS) has become a compelling approach to acquire and
infer urban-scale sensing data. However, participants risk their location privacy when …
infer urban-scale sensing data. However, participants risk their location privacy when …
CCS-TA: Quality-guaranteed online task allocation in compressive crowdsensing
Data quality and budget are two primary concerns in urban-scale mobile crowdsensing
applications. In this paper, we leverage the spatial and temporal correlation among the data …
applications. In this paper, we leverage the spatial and temporal correlation among the data …
Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect
The phenology of a landscape is a key parameter in climate and biogeochemical cycle
models and its correct representation is central to the accurate simulation of carbon, water …
models and its correct representation is central to the accurate simulation of carbon, water …
Water vapor‐weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend
Water vapor‐weighted mean temperature, Tm, is a vital parameter for retrieving precipitable
water vapor (PWV) from the zenith wet delay (ZWD) of Global Navigation Satellite Systems …
water vapor (PWV) from the zenith wet delay (ZWD) of Global Navigation Satellite Systems …
A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations
The presence of data gaps is always a concern in geophysical records, creating not only
difficulty in interpretation but, more importantly, also a large source of uncertainty in data …
difficulty in interpretation but, more importantly, also a large source of uncertainty in data …