Listar Dpto. Estadística, Informática y Matemáticas - Estatistika, Informatika eta Matematika Saila [desde mayo 2018 / 2018ko maiatzetik] por autor UPNA "Militino, Ana F."
Mostrando ítems 1-12 de 12
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Detecting change-points in the time series of surfaces occupied by pre-defined NDVI categories in continental Spain from 1981 to 2015
Militino, Ana F.
; Ugarte Martínez, María Dolores ; Pérez Goya, Unai (Springer, 2018)
Capítulo de libro / Liburuen kapitulua 
The free access to satellite images since more than 40 years ago has provoked a rapid increase of multitemporal derived information of remote sensing data that should be summarized and analyzed for future inferences. ... -
Filling missing data and smoothing altered data in satellite imagery with a spatial functional procedure
Militino, Ana F. ; Ugarte Martínez, María Dolores ; Montesino San Martín, Manuel (Springer, 2019)
Artículo / Artikulua
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
Goicoa Mangado, Tomás; Adin Urtasun, Aritz ; Etxeberria Andueza, Jaione ; Militino, Ana F. ; Ugarte Martínez, María Dolores (SAGE, 2019)
Artículo / Artikulua
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
Militino, Ana F. ; Ugarte Martínez, María Dolores ; Pérez Goya, Unai ; Genton, Marc G. (IEEE, 2019)
Artículo / Artikulua
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 ... -
An introduction to the spatio-temporal analysis of satellite remote sensing data for geostatisticians
Militino, Ana F. ; Ugarte Martínez, María Dolores ; Pérez Goya, Unai (Springer International Publishing, 2018)
Capítulo de libro / Liburuen kapitulua
Satellite remote sensing data have become available in meteorology, agriculture, forestry, geology, regional planning, hydrology or natural environment sciences since several decades ago, because satellites provide routinely ... -
Locally adaptive change-point detection (LACPD) with applications to environmental changes
Moradi, Mohammad Mehdi ; Montesino San Martín, Manuel ; Ugarte Martínez, María Dolores ; Militino, Ana F. (Springer, 2021)
Artículo / Artikulua
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
Militino, Ana F. ; Goyena Baroja, Harkaitz; Pérez-Goya, Unai ; Ugarte Martínez, María Dolores (Springer, 2024)
Artículo / Artikulua
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 ... -
Machine learning procedures for daily interpolation of rainfall in Navarre (Spain)
Militino, Ana F. ; Ugarte Martínez, María Dolores ; Pérez Goya, Unai (Springer, 2023)
Capítulo de libro / Liburuen kapitulua
Kriging is by far the most well known and widely used statistical method for interpolating data in spatial random fields. The main reason is that it provides the best linear unbiased predictor and it is an exact interpolator ... -
On the performances of trend and change-point detection methods for remote sensing data
Militino, Ana F. ; Moradi, Mohammad Mehdi ; Ugarte Martínez, María Dolores (MDPI, 2020)
Artículo / Artikulua
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 ... -
Software tools and statistical methods for downloading, processing, and analysing satellite images
Pérez Goya, Unai (2019)
Tesis doctoral / Doktoretza tesia
El principal objetivo de esta tesis es la introducción y desarrollo de métodos estadísticos en imágenes satelitales para mejorar el procesamiento, suavizado, predicción, e inferencia de los datos de teledetección. Este ... -
Unpaired spatio-temporal fusion of image patches (USTFIP) from cloud covered images
Goyena Baroja, Harkaitz; Pérez Goya, Unai ; Montesino San Martín, Manuel ; Militino, Ana F. ; Wang, Qunming; Atkinson, Peter M.; Ugarte Martínez, María Dolores (Elsevier, 2023)
Artículo / Artikulua
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
Militino, Ana F. ; Montesino San Martín, Manuel ; Pérez Goya, Unai ; Ugarte Martínez, María Dolores (MDPI, 2020)
Artículo / Artikulua
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 ...
