An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products
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...
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2014-01-01
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Series: | Advances in Meteorology |
Online Access: | http://dx.doi.org/10.1155/2014/692313 |
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doaj-4d536627ef9041fab180d18a57525f5d2020-11-24T20:54:17ZengHindawi LimitedAdvances in Meteorology1687-93091687-93172014-01-01201410.1155/2014/692313692313An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing ProductsShaohui Chen0Hongbo Su1Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaThis 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.http://dx.doi.org/10.1155/2014/692313 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shaohui Chen Hongbo Su |
spellingShingle |
Shaohui Chen Hongbo Su An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products Advances in Meteorology |
author_facet |
Shaohui Chen Hongbo Su |
author_sort |
Shaohui Chen |
title |
An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products |
title_short |
An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products |
title_full |
An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products |
title_fullStr |
An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products |
title_full_unstemmed |
An Eigenpoint Based Multiscale Method for Validating Quantitative Remote Sensing Products |
title_sort |
eigenpoint based multiscale method for validating quantitative remote sensing products |
publisher |
Hindawi Limited |
series |
Advances in Meteorology |
issn |
1687-9309 1687-9317 |
publishDate |
2014-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2014/692313 |
work_keys_str_mv |
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