An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products

Joint Authors

Su, Hongbo
Chen, Shaohui

Source

Advances in Meteorology

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-04-30

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Physics

Abstract EN

This letter first proposes the eigenpoint concept for quantitative remote sensing products (QRSPs) after discussing the eigenhomogeneity and eigenaccuracy for land surface variables.

The eigenpoints are located according to the á trous wavelet planes of the QRSP.

Based on these concepts, this letter proposes an eigenpoint based multiscale method for validating the QRSPs.

The basic idea is that the QRSPs at coarse scales are validated by validating their eigenpoints using the QRSP at fine scale.

The QRSP at fine scale is finally validated using observation data at the ground based eigenpoints at instrument scale.

The ground based eigenpoints derived from the forecasted QRSP can be used as the observation positions when the satellites pass by the studied area.

Experimental results demonstrate that the proposed method is manpower-and time-saving compared with the ideal scanning method and it is satisfying to perform simultaneous observation at these eigenpoints in terms of efficiency and accuracy.

American Psychological Association (APA)

Chen, Shaohui& Su, Hongbo. 2014. An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products. Advances in Meteorology،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-490993

Modern Language Association (MLA)

Chen, Shaohui& Su, Hongbo. An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products. Advances in Meteorology No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-490993

American Medical Association (AMA)

Chen, Shaohui& Su, Hongbo. An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products. Advances in Meteorology. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-490993

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-490993