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Structural and Statistical Properties of the Collocation Technique for Error Characterization : Volume 19, Issue 1 (09/02/2012)

By Zwieback, S.

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Book Id: WPLBN0003977076
Format Type: PDF Article :
File Size: Pages 12
Reproduction Date: 2015

Title: Structural and Statistical Properties of the Collocation Technique for Error Characterization : Volume 19, Issue 1 (09/02/2012)  
Author: Zwieback, S.
Volume: Vol. 19, Issue 1
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Wagner, W., Dorigo, W., Scipal, K., & Zwieback, S. (2012). Structural and Statistical Properties of the Collocation Technique for Error Characterization : Volume 19, Issue 1 (09/02/2012). Retrieved from

Description: Vienna University of Technology, Institute of Photogrammetry and Remote Sensing, Vienna, Austria. The validation of geophysical data sets (e.g. derived from models, exploration techniques or remote sensing) presents a formidable challenge as all products are inherently different and subject to errors. The collocation technique permits the retrieval of the error variances of different data sources without the need to specify one data set as a reference. In addition calibration constants can be determined to account for biases and different dynamic ranges. The method is frequently applied to the study and comparison of remote sensing, in-situ and modelled data, particularly in hydrology and oceanography. Previous studies have almost exclusively focussed on the validation of three data sources; in this paper it is shown how the technique generalizes to an arbitrary number of data sets. It turns out that only parts of the covariance structure can be resolved by the collocation technique, thus emphasizing the necessity of expert knowledge for the correct validation of geophysical products. Furthermore the bias and error variance of the estimators are derived with particular emphasis on the assumptions necessary for establishing those characteristics. Important properties of the method, such as the structural deficiencies, dependence of the accuracy on the number of measurements and the impact of violated assumptions, are illustrated by application to simulated data.

Structural and statistical properties of the collocation technique for error characterization

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