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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Main Authors: Shaohui Chen, Hongbo Su
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Advances in Meteorology
Online Access:http://dx.doi.org/10.1155/2014/692313
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spelling 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
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