Listar INAMAT2 - Institute for Advanced Materials and Mathematics por autor UPNA "Pérez-Goya, Unai"
Mostrando ítems 1-8 de 8
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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. ... -
Improving the quality of satellite imagery based on ground-truth data from rain gauge stations
Militino, Ana F. ; Ugarte Martínez, María Dolores ; Pérez Goya, Unai (MDPI, 2018)
Artículo / Artikulua
Multitemporal imagery is by and large geometrically and radiometrically accurate, but the residual noise arising from removal clouds and other atmospheric and electronic effects can produce outliers that must be mitigated ... -
Large-scale unsupervised spatio-temporal semantic analysis of vast regions from satellite images sequences
Echegoyen Arruti, Carlos; Pérez, Aritz; Santafé Rodrigo, Guzmán ; Pérez-Goya, Unai ; Ugarte Martínez, María Dolores (Springer, 2024)
Artículo / Artikulua
Temporal sequences of satellite images constitute a highly valuable and abundant resource for analyzing regions of interest. However, the automatic acquisition of knowledge on a large scale is a challenging task due to ... -
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 ... -
Stochastic spatio-temporal models for analysing NDVI distribution of GIMMS NDVI3g images
Militino, Ana F. ; Ugarte Martínez, María Dolores ; Pérez Goya, Unai (MDPI, 2017)
Artículo / Artikulua
The normalized difference vegetation index (NDVI) is an important indicator for evaluating vegetation change, monitoring land surface fluxes or predicting crop models. Due to the great availability of images provided by ... -
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 ...
