A geospatial web portal for sharing and analyzing greenhouse gas data derived from satellite remote sensing images

Hao LIN, Bailang YU, Zuoqi CHEN, Yingjie HU, Yan HUANG, Jianping WU, Bin WU, Rong GE

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Front. Earth Sci. ›› 2013, Vol. 7 ›› Issue (3) : 295-309. DOI: 10.1007/s11707-013-0365-z
RESEARCH ARTICLE
RESEARCH ARTICLE

A geospatial web portal for sharing and analyzing greenhouse gas data derived from satellite remote sensing images

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Abstract

Greenhouse gas data collected by different institutions throughout the world have significant scientific values for global climate change studies. Due to the diversity of data formats and different specifications of data access interfaces, most of those data should be first downloaded onto a local machine before they can be used. To overcome this limitation, we present a geospatial web portal for sharing and analyzing greenhouse gas data derived from remote sensing images. As a proof-of-concept, a prototype has also been designed and implemented. The workflow of the web portal contains four processes: data access, data analysis, results visualization, and results output. A large volume of greenhouse gas data have been collected, described, and indexed in the portal, and a variety of data analysis services, such as calculating the temporal variation of regionally averaged column CO2 values and analyzing the latitudinal variations of globally averaged column CO2 values, are integrated into this portal. With the integrated geospatial data and services, researchers can collect and analyze greenhouse gas data online, and can preview and download the analysis results directly from the web portal. The geospatial web portal has been implemented as a web application, and we also used a study case to illustrate this framework.

Keywords

greenhouse gas data / geospatial web portal / online spatial analysis

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Hao LIN, Bailang YU, Zuoqi CHEN, Yingjie HU, Yan HUANG, Jianping WU, Bin WU, Rong GE. A geospatial web portal for sharing and analyzing greenhouse gas data derived from satellite remote sensing images. Front Earth Sci, 2013, 7(3): 295‒309 https://doi.org/10.1007/s11707-013-0365-z

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Acknowledgements

This work is supported by the National Basic Research Program of China (Grant No. 2010CB951603) and the National Natural Science Foundation of China (Grant No. 41001270). The authors thank five anonymous reviewers for their constructive comments and suggestions.

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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