Listar por tema "Kriging"
Mostrando ítems 1-7 de 7
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A 3-D indoor analysis of path loss modeling using kriging techniques
This study proposes a novel measurement-based method to predict and model three-dimensional (3-D) path loss in indoor scenarios, which first regresses 28 GHz measurements via median path loss modeling and then includes ... -
Análisis regional de frecuencias de las precipitaciones diarias extremas en Navarra. Elaboración de los mapas de cuantiles
La determinación de la ley de frecuencias de precipitaciones resulta imprescindible para el diseño de diferentes infraestructuras hidráulicas así como para el análisis y determinación de zonas inundables. El objetivo de ... -
Improving the quality of satellite imagery based on ground-truth data from rain gauge stations
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 ... -
Machine learning procedures for daily interpolation of rainfall in Navarre (Spain)
(Springer, 2023) Capítulo de libro / Liburuen kapituluaKriging 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 ... -
Optimización de la cartografía de malas hierbas mediante técnicas geoestadísticas y teledetección con UAV
(Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, 2017) Contribución a congreso / Biltzarrerako ekarpenaSe evalúa una metodología para la cartografía de malas hierbas en época tardía del cultivo combinando datos espaciales georreferenciados (variable primaria) con información espectral (variables secundarias). Como variable ... -
Stochastic spatio-temporal models for analysing NDVI distribution of GIMMS NDVI3g images
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 ... -
Tuning selection impact on kriging-aided in-building path loss modeling
How do you know you select enough tuning dataset from measurements to guarantee model prediction accuracy? Tuning datasets are often selected based on simple random sampling with predefined rates. Usually, these rates ...