INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSION

INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSION

The flourished development of wireless sensor network technology sheds light to the effective and inexpensive collection of in-situ networking measurements. This will contribute to the temporal validation of coarse resolution remote sensing products. However, the quality evaluation of the in-situ ne...

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Main Authors: G. Yin, A. Li
Format: Article
Language:English
Published: Copernicus Publications 2017-09-01
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-2-W7/567/2017/isprs-archives-XLII-2-W7-567-2017.pdf
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spelling doaj-49cf7d446b1a44a6bc30eaa1a5343d3c2020-11-25T01:01:01ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-09-01XLII-2-W756757110.5194/isprs-archives-XLII-2-W7-567-2017INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSIONG. Yin0A. Li1Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaThe flourished development of wireless sensor network technology sheds light to the effective and inexpensive collection of in-situ networking measurements. This will contribute to the temporal validation of coarse resolution remote sensing products. However, the quality evaluation of the in-situ networking measurements and upscaling is still problematic. This study proposed an evaluation method based on Gaussian Process Regression (GPR). Specifically, the qualities of networking measurements and upscaling were evaluated through the relevance of each plot, and the pixelwise coefficient of variation of the scaling results. Both of which can be generated by GPR. The preliminary results demonstrated the potential of the proposed method on quality evaluation of upscaling. Its potential on measurements (per se) quality evaluation will be analysed future.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/567/2017/isprs-archives-XLII-2-W7-567-2017.pdf
collection DOAJ
language English
format Article
sources DOAJ
author G. Yin
A. Li
spellingShingle G. Yin
A. Li
INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSION
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet G. Yin
A. Li
author_sort G. Yin
title INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSION
title_short INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSION
title_full INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSION
title_fullStr INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSION
title_full_unstemmed INTEGRATED QUALITY EVALUATION OF THE IN-SITU NETWORKING MEASUREMENTS AND UPSCALING USING GAUSSIAN PROCESS REGRESSION
title_sort integrated quality evaluation of the in-situ networking measurements and upscaling using gaussian process regression
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2017-09-01
description The flourished development of wireless sensor network technology sheds light to the effective and inexpensive collection of in-situ networking measurements. This will contribute to the temporal validation of coarse resolution remote sensing products. However, the quality evaluation of the in-situ networking measurements and upscaling is still problematic. This study proposed an evaluation method based on Gaussian Process Regression (GPR). Specifically, the qualities of networking measurements and upscaling were evaluated through the relevance of each plot, and the pixelwise coefficient of variation of the scaling results. Both of which can be generated by GPR. The preliminary results demonstrated the potential of the proposed method on quality evaluation of upscaling. Its potential on measurements (per se) quality evaluation will be analysed future.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/567/2017/isprs-archives-XLII-2-W7-567-2017.pdf
work_keys_str_mv AT gyin integratedqualityevaluationoftheinsitunetworkingmeasurementsandupscalingusinggaussianprocessregression
AT ali integratedqualityevaluationoftheinsitunetworkingmeasurementsandupscalingusinggaussianprocessregression
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