Search results for " gap filling"

showing 3 items of 3 documents

Filling in long gap sequences by performing jointly EOF and FDA

2012

In this paper the EOF methodology is performed jointly with the FDA approach on a spatiotemporal multivariate data set with the aim to fill in missing values as accurately as possible when long gap sequences occur. Simulated data sets, containing ”artificial” gaps, are considered in order to test the performance of two proposed procedures; in the first one, observed data are reconstructed by EOF and then converted into functional ones; in the second one, observed data are transformed into functional ones and then EOF reconstruction is applied. By comparing some performance indicators computed for the two procedures, it is shown that a pre-processing of data by FDA, followed by the EOF, may …

FDA EOF gap filling
researchProduct

Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine

2021

For the last decade, Gaussian process regression (GPR) proved to be a competitive machine learning regression algorithm for Earth observation applications, with attractive unique properties such as band relevance ranking and uncertainty estimates. More recently, GPR also proved to be a proficient time series processor to fill up gaps in optical imagery, typically due to cloud cover. This makes GPR perfectly suited for large-scale spatiotemporal processing of satellite imageries into cloud-free products of biophysical variables. With the advent of the Google Earth Engine (GEE) cloud platform, new opportunities emerged to process local-to-planetary scale satellite data using advanced machine …

Earth observationGoogle Earth Engine (GEE); Gaussian process regression (GPR); machine learning; Sentinel-2; gap filling; leaf area index (LAI)010504 meteorology & atmospheric sciencesComputer scienceScienceleaf area index (LAI)0211 other engineering and technologiesCloud computing02 engineering and technologycomputer.software_genre01 natural sciencesKrigingGaussian process regression (GPR)021101 geological & geomatics engineering0105 earth and related environmental sciencesPixelbusiness.industryQGoogle Earth Engine (GEE)machine learningKernel (image processing)Ground-penetrating radarGeneral Earth and Planetary SciencesData miningSentinel-2Scale (map)businesscomputergap fillingLevel of detailRemote Sensing; Volume 13; Issue 3; Pages: 403
researchProduct

EOFs for gap filling in multivariate air quality data: a FDA approach

2010

Missing values are a common concern in spatiotemporal data sets. During recent years a great number of methods have been developed for gap filling. One of the emerging approaches is based on the Empirical Orthogonal Function (EOF) methodology, applied mainly on raw and univariate data sets presenting irregular missing patterns. In this paper EOF is carried out on a multivariate space-time data set, related to concentrations of pollutants recorded at different sites, after denoising raw data by FDA approach. Some performance indicators are computed on simulated incomplete data sets with also long gaps in order to show that the EOF reconstruction appears to be an improved procedure especially…

Settore SECS-S/01 - StatisticaFDA EOF missing data gap filling
researchProduct