Spatial statistics is a field of applied statistics dealing with spatial data.
It involves stochastic processes (random fields, point processes), sampling, smoothing and interpolation, regional (areal unit) and lattice (gridded) data, point patterns, as well as and stereology.
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This course teaches how to apply exploratory spatial data analysis to health data. Teaching focuses on the basics of spatial statistics and of epidemiology, and proposes a context to analyse geodatase
Ce cours a pour objectif de familiariser les étudiants avec les principaux concepts, instruments et techniques de la télédétection environnementale. Les interactions ondes/matière, les différents type
Acquisition de concepts et compétences de base liées à la représentation numérique des données géographiques et à leur insertion dans des SIG. Apprentissage de processus d'analyse spatiale pour les in
In probability, statistics and related fields, a Poisson point process is a type of random mathematical object that consists of points randomly located on a mathematical space with the essential feature that the points occur independently of one another. The Poisson point process is often called simply the Poisson process, but it is also called a Poisson random measure, Poisson random point field or Poisson point field.
Spatial analysis is any of the formal techniques which studies entities using their topological, geometric, or geographic properties. Spatial analysis includes a variety of techniques using different analytic approaches, especially spatial statistics. It may be applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, or to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures.
A detailed theoretical and experimental study on the effect of the superposition of uncorrelated speckle patterns with polarization diversity on the spatial statistics of the superposed speckle pattern is presented. It is shown that depending on the mutual ...
Inadequate sodium and potassium dietary intakes are associated with major, yet preventable, health consequences. Local public health interventions can be facilitated and informed by fine-scale geospatial analyses. In this study, we assess the existence of ...
MDPI2021
Statistical methods for inference on spatial extremes of large datasets are yet to be developed. Motivated by standard dimension reduction techniques used in spatial statistics, we propose an approach based on empirical basis functions to explore and model ...