AOD adaptive prediction method based on GNSS PWV

Aerosol optical depth (AOD) is a basic parameter of total aerosol content, which plays an important role in the study of atmospheric air quality. In order to explore the impact of different types of AOD on air quality, this paper proposes two adaptive AOD prediction methods based on GNSS PWV. The pr...

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Autores principales:	ZHAO Qingzhi, SU Jing, YANG Pengfei, YAO Yibin
Formato:	article
Lenguaje:	ZH
Publicado:	Surveying and Mapping Press 2021
Materias:	gnss pwv aod prediction model Mathematical geography. Cartography GA1-1776
Acceso en línea:	https://doaj.org/article/70dc111a41e1455dba747e7d828338e3
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id	oai:doaj.org-article:70dc111a41e1455dba747e7d828338e3
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spelling	oai:doaj.org-article:70dc111a41e1455dba747e7d828338e32021-11-12T02:25:59ZAOD adaptive prediction method based on GNSS PWV1001-159510.11947/j.AGCS.2021.20210052https://doaj.org/article/70dc111a41e1455dba747e7d828338e32021-10-01T00:00:00Zhttp://xb.sinomaps.com/article/2021/1001-1595/2021-10-1279.htmhttps://doaj.org/toc/1001-1595Aerosol optical depth (AOD) is a basic parameter of total aerosol content, which plays an important role in the study of atmospheric air quality. In order to explore the impact of different types of AOD on air quality, this paper proposes two adaptive AOD prediction methods based on GNSS PWV. The proposed method considers the temporal autocorrelation of AOD between adjacent epochs, and the model coefficients can be updated adaptively. One method is to model the 550 nm AOD directly based on GNSS PWV, which is called TAF (total AOD forecast) model. Another AOD modeling method takes into account the sensitivity of five different types of AOD to PWV, referred to it simply as FTAF(five type based AOD forecast) model. The model first establishes the functional relationship between PWV and five types of AOD. Secondly, according to the relationship between 550 nm AOD and five types of AOD, the weight of different types of AOD in 550 nm AOD was determined. Finally, PWV is used to predict five types of AOD, and the final 550 nm AOD is obtained by weighted average. 16 GNSS stations in Beijing, Tianjin, Hebei region are selected to verify the accuracy of the proposed model. The results show that the two 550 nm AOD prediction models have high accuracy, and the FTAF model is better than the TAF model. The AOD prediction model proposed in this paper can effectively apply the tropospheric parameters retrieved from GNSS to remote sensing monitoring of atmospheric environment, which provides a new idea for the study of atmospheric environmental quality.ZHAO QingzhiSU JingYANG PengfeiYAO YibinSurveying and Mapping Pressarticlegnsspwvaodprediction modelMathematical geography. CartographyGA1-1776ZHActa Geodaetica et Cartographica Sinica, Vol 50, Iss 10, Pp 1279-1289 (2021)
institution	DOAJ
collection	DOAJ
language	ZH
topic	gnss pwv aod prediction model Mathematical geography. Cartography GA1-1776
spellingShingle	gnss pwv aod prediction model Mathematical geography. Cartography GA1-1776 ZHAO Qingzhi SU Jing YANG Pengfei YAO Yibin AOD adaptive prediction method based on GNSS PWV
description	Aerosol optical depth (AOD) is a basic parameter of total aerosol content, which plays an important role in the study of atmospheric air quality. In order to explore the impact of different types of AOD on air quality, this paper proposes two adaptive AOD prediction methods based on GNSS PWV. The proposed method considers the temporal autocorrelation of AOD between adjacent epochs, and the model coefficients can be updated adaptively. One method is to model the 550 nm AOD directly based on GNSS PWV, which is called TAF (total AOD forecast) model. Another AOD modeling method takes into account the sensitivity of five different types of AOD to PWV, referred to it simply as FTAF(five type based AOD forecast) model. The model first establishes the functional relationship between PWV and five types of AOD. Secondly, according to the relationship between 550 nm AOD and five types of AOD, the weight of different types of AOD in 550 nm AOD was determined. Finally, PWV is used to predict five types of AOD, and the final 550 nm AOD is obtained by weighted average. 16 GNSS stations in Beijing, Tianjin, Hebei region are selected to verify the accuracy of the proposed model. The results show that the two 550 nm AOD prediction models have high accuracy, and the FTAF model is better than the TAF model. The AOD prediction model proposed in this paper can effectively apply the tropospheric parameters retrieved from GNSS to remote sensing monitoring of atmospheric environment, which provides a new idea for the study of atmospheric environmental quality.
format	article
author	ZHAO Qingzhi SU Jing YANG Pengfei YAO Yibin
author_facet	ZHAO Qingzhi SU Jing YANG Pengfei YAO Yibin
author_sort	ZHAO Qingzhi
title	AOD adaptive prediction method based on GNSS PWV
title_short	AOD adaptive prediction method based on GNSS PWV
title_full	AOD adaptive prediction method based on GNSS PWV
title_fullStr	AOD adaptive prediction method based on GNSS PWV
title_full_unstemmed	AOD adaptive prediction method based on GNSS PWV
title_sort	aod adaptive prediction method based on gnss pwv
publisher	Surveying and Mapping Press
publishDate	2021
url	https://doaj.org/article/70dc111a41e1455dba747e7d828338e3
work_keys_str_mv	AT zhaoqingzhi aodadaptivepredictionmethodbasedongnsspwv AT sujing aodadaptivepredictionmethodbasedongnsspwv AT yangpengfei aodadaptivepredictionmethodbasedongnsspwv AT yaoyibin aodadaptivepredictionmethodbasedongnsspwv
_version_	1718431296212959232

AOD adaptive prediction method based on GNSS PWV

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