Listar Artículos de revista DEIM - EIMS Aldizkari artikuluak por autor UPNA "Militino, Ana F."
Mostrando ítems 1-8 de 8
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Filling missing data and smoothing altered data in satellite imagery with a spatial functional procedure
Outliers and missing data are commonly found in satellite imagery. These are usually caused by atmospheric or electronic failures, hampering the correct monitoring of remote-sensing data. To avoid distorted data, we propose ... -
Flexible Bayesian P-splines for smoothing age-specific spatio-temporal mortality patterns
In this paper age-space-time models based on one and two-dimensional P-splines with B-spline bases are proposed for smoothing mortality rates, where both xed relative scale and scale invariant two-dimensional penalties ... -
Interpolation of the mean anomalies for cloud filling in land surface temperature and normalized difference vegetation index
When monitoring time series of remote sensing data, it is advisable to fill gaps, i.e., missing or distorted data, caused by atmospheric effects or technical failures. In this paper, a new method for filling these gaps ... -
Locally adaptive change-point detection (LACPD) with applications to environmental changes
We propose an adaptive-sliding-window approach (LACPD) for the problem of change-point detection in a set of time-ordered observations. The proposed method is combined with sub-sampling techniques to compensate for the ... -
Logistic regression versus XGBoost for detecting burned areas using satellite images
Classical statistical methods prove advantageous for small datasets, whereas machine learning algorithms can excel with larger datasets. Our paper challenges this conventional wisdom by addressing a highly significant ... -
On the performances of trend and change-point detection methods for remote sensing data
Detecting change-points and trends are common tasks in the analysis of remote sensing data. Over the years, many different methods have been proposed for those purposes, including (modified) Mann-Kendall and Cox-Stuart ... -
Unpaired spatio-temporal fusion of image patches (USTFIP) from cloud covered images
Spatio-temporal image fusion aims to increase the frequency and resolution of multispectral satellite sensor images in a cost-effective manner. However, practical constraints on input data requirements and computational ... -
Using RGISTools to estimate water levels in reservoirs and lakes
The combination of freely accessible satellite imagery from multiple programs improves the spatio-temporal coverage of remote sensing data, but it exhibits barriers regarding the variety of web services, file formats, and ...