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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Copernicus Publications
2017-09-01
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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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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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1725211261910646784 |