An automated and integrated framework for dust storm detection based on ogc web processing services
Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm...
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doaj-e7d08d226bed4c86b94be98810d86f742020-11-24T22:01:01ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342014-11-01XL-215115610.5194/isprsarchives-XL-2-151-2014An automated and integrated framework for dust storm detection based on ogc web processing servicesF. Xiao0G. Y. K. Shea1M. S. Wong2J. Campbell3Dept. of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong KongDept. of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong KongDept. of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong KongUS Naval Research Laboratory, Monterey, CA, USDust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading to improved ease of use and flexibility.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-2/151/2014/isprsarchives-XL-2-151-2014.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
F. Xiao G. Y. K. Shea M. S. Wong J. Campbell |
spellingShingle |
F. Xiao G. Y. K. Shea M. S. Wong J. Campbell An automated and integrated framework for dust storm detection based on ogc web processing services The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
F. Xiao G. Y. K. Shea M. S. Wong J. Campbell |
author_sort |
F. Xiao |
title |
An automated and integrated framework for dust storm detection based on ogc web processing services |
title_short |
An automated and integrated framework for dust storm detection based on ogc web processing services |
title_full |
An automated and integrated framework for dust storm detection based on ogc web processing services |
title_fullStr |
An automated and integrated framework for dust storm detection based on ogc web processing services |
title_full_unstemmed |
An automated and integrated framework for dust storm detection based on ogc web processing services |
title_sort |
automated and integrated framework for dust storm detection based on ogc web processing services |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2014-11-01 |
description |
Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in
global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The
complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing
platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop
an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO
data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an
automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by
Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting
and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on
OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART
model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and
HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on
Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including
horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and
displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the
applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model
integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly
automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental
authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading
to improved ease of use and flexibility. |
url |
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-2/151/2014/isprsarchives-XL-2-151-2014.pdf |
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