SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA

SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA

Under the background of the increasingly unified management of natural resources, remote sensing big-data will become the main data source to support a number of major projects. How to sample the natural resources results efficiently and reliably in the process of quality evaluation is always a rese...

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Main Authors: Y. Dang, J. X. Zhang, P. C. Zhang, F. J. Luo, J. Bai
Format: Article
Language:English
Published: Copernicus Publications 2020-02-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W10/11/2020/isprs-archives-XLII-3-W10-11-2020.pdf
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spelling doaj-1e52a892982a45fab822442576797dce2020-11-25T01:48:02ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-02-01XLII-3-W10111610.5194/isprs-archives-XLII-3-W10-11-2020SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATAY. Dang0J. X. Zhang1P. C. Zhang2F. J. Luo3J. Bai4National Quality Inspection and Testing Centre for Surveying and Mapping Products, P. R. ChinaNational Quality Inspection and Testing Centre for Surveying and Mapping Products, P. R. ChinaNational Quality Inspection and Testing Centre for Surveying and Mapping Products, P. R. ChinaNational Quality Inspection and Testing Centre for Surveying and Mapping Products, P. R. ChinaNational Quality Inspection and Testing Centre for Surveying and Mapping Products, P. R. ChinaUnder the background of the increasingly unified management of natural resources, remote sensing big-data will become the main data source to support a number of major projects. How to sample the natural resources results efficiently and reliably in the process of quality evaluation is always a research hotspot when it comes to the natural resources results involving remote sensing big-data. A sequential quality evaluation model based on root mean square error (RMSprop) optimization algorithm is constructed by theoretical analysis with an numerical experiments to validate the effectiveness of this method.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W10/11/2020/isprs-archives-XLII-3-W10-11-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Y. Dang
J. X. Zhang
P. C. Zhang
F. J. Luo
J. Bai
spellingShingle Y. Dang
J. X. Zhang
P. C. Zhang
F. J. Luo
J. Bai
SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet Y. Dang
J. X. Zhang
P. C. Zhang
F. J. Luo
J. Bai
author_sort Y. Dang
title SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA
title_short SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA
title_full SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA
title_fullStr SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA
title_full_unstemmed SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA
title_sort sampling method analysis and quality evaluation strategy for remote sensing big data
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2020-02-01
description Under the background of the increasingly unified management of natural resources, remote sensing big-data will become the main data source to support a number of major projects. How to sample the natural resources results efficiently and reliably in the process of quality evaluation is always a research hotspot when it comes to the natural resources results involving remote sensing big-data. A sequential quality evaluation model based on root mean square error (RMSprop) optimization algorithm is constructed by theoretical analysis with an numerical experiments to validate the effectiveness of this method.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W10/11/2020/isprs-archives-XLII-3-W10-11-2020.pdf
work_keys_str_mv AT ydang samplingmethodanalysisandqualityevaluationstrategyforremotesensingbigdata
AT jxzhang samplingmethodanalysisandqualityevaluationstrategyforremotesensingbigdata
AT pczhang samplingmethodanalysisandqualityevaluationstrategyforremotesensingbigdata
AT fjluo samplingmethodanalysisandqualityevaluationstrategyforremotesensingbigdata
AT jbai samplingmethodanalysisandqualityevaluationstrategyforremotesensingbigdata
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