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2 - Influence of image registration on validation efforts

from PART I - The Importance of Image Registration for Remote Sensing

Published online by Cambridge University Press:  03 May 2011

By
Bin Tan  and
Curtis E. Woodcock
Edited by
Jacqueline Le Moigne ,
Nathan S. Netanyahu  and
Roger D. Eastman
Bin Tan
Affiliation:
Earth Resources Technology Inc., Maryland
Curtis E. Woodcock
Affiliation:
Boston University, Massachussets
Jacqueline Le Moigne
Affiliation:
NASA-Goddard Space Flight Center
Nathan S. Netanyahu
Affiliation:
Bar-Ilan University, Israel and University of Maryland, College Park
Roger D. Eastman
Affiliation:
Loyola University Maryland
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Summary

Abstract

Currently, several high level satellite-based data products relevant to Earth science system and global change research are derived from medium spatial resolution remote sensing observations. Because of their high temporal frequency and important spatial coverage, these products, also called biophysical variables, are very useful to describe the mass and energy fluxes between the Earth's surface and the atmosphere. In order to check the relevance of using such products as inputs into land surface models, it is of importance to assess their accuracy. Validation activity consists in evaluating by independent means the quality of these biophysical variables. Currently, these variables are derived from coarse-resolution remote sensing observations. Validation methods consist in generating a ground truth map of these products at high spatial resolution. It is produced by using ground measurements of the biophysical variable and radiometric data from a high spatial resolution sensor. The relationship between biophysical variable and radiometric data, called the transfer function, allows extending the local ground measurements to the whole high spatial resolution image. The resulting biophysical variable map is aggregated to be compared with the medium spatial resolution satellite biophysical products. Three important geometrical issues influence the validation results: (1) The localization error of the local ground measurements, (2) the localization error between high and medium resolution images, and (3) the point spread function (PSF) associated with the medium spatial resolution remote sensing observations. This work aims at analyzing the influence of these issues within the validation process.

Type
Chapter
Information
Image Registration for Remote Sensing , pp. 24 - 34
Publisher: Cambridge University Press
Print publication year: 2011

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