Cokriging for spatial functional data
نویسندگان
چکیده
منابع مشابه
Statistics for Spatial Functional Data
Functional Data Analysis is a relatively new branch in Statistics. Experiments where a complete function is observed for each individual give rise to functional data. In this work we focus on the case of functional data presenting spatial dependence. The three classic types of spatial data structures (geostatistical data, point patterns and areal data) can be combined with functional data as it...
متن کاملDownscaling cokriging for image sharpening
The main aim of this paper is to show the utility of cokriging for image fusion (i.e. increasing the spatial resolution of satellite sensor images). It is assumed that co-registered images with different spatial and spectral resolutions of the same scene are available and the task is to generate new remote sensing images at the finer spatial resolution for the spectral bands available only at t...
متن کاملSpatial Estimation of Groundwater Quality Parameters Based on Water Salinity Data using Kriging and Cokriging Methods
Groundwater is one of earth’s most vital renewable and widely distributed resources as well as an important source of water supply worldwide. The increased exploitation of groundwater resources can decrease regional water quality as a whole. The estimation of sodium adsorption ratio (SAR) and chloride content, and also, Na, Ca and Mg concentration are much more timeconsuming and expensive than ...
متن کاملFlexible spatial models for kriging and cokriging using moving averages and the fast Fourier Transform (FFT)
Models for spatial autocorrelation and cross-correlation depend on the distance and direction separating two locations, and are constrained so that for all possible sets of locations, the covariance matrices implied from the models remain nonnegative-definite. Based on spatial correlation, optimal linear predictors can be constructed that yield complete maps of spatial fields from incomplete an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2010
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2009.03.005