Mapping and analysis using multisource oceanic satellite data and google earth engine
Ocean satellite observation because of its large coverage area and high frequency observation become ever more important data and information source with global climate changing, ocean resources protecting and oceanic engineering projects implementing. Oceanic satellite data characteristically inclu...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2022-01-01
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| Series: | SHS Web of Conferences |
| Online Access: | https://www.shs-conferences.org/articles/shsconf/pdf/2022/15/shsconf_aeme2022_01023.pdf |
| _version_ | 1818009560500142080 |
|---|---|
| author | Kang Yan Wang Jun |
| author_facet | Kang Yan Wang Jun |
| author_sort | Kang Yan |
| collection | DOAJ |
| description | Ocean satellite observation because of its large coverage area and high frequency observation become ever more important data and information source with global climate changing, ocean resources protecting and oceanic engineering projects implementing. Oceanic satellite data characteristically include multi-physical parameters, are the product of multi-level processing and are multi-sourced data. Therefore, oceanic satellite data often have different manifestations making the understanding and use of these data challenging, and there is an urgent need for a flexible platform to share the data and merge different kinds of the data information. Here we use Google Earth Engine that make these data easily understandable and a fully synthesized and comprehensive visualization. Then the key techniques for creating 2D and 3D visualizations of oceanic satellite data using KML and Google Earth are detailed in this paper. As an example, multi-sourced satellite data including horizontal distribution and vertical profiles of Typhoon Morakot in August 2009 are combined on Google Earth with three-dimensional visualization. We have extended this research and developed a web service system based on an oceanic satellite visualization data model to dynamically display different types of the oceanic satellite data on Google Earth. |
| first_indexed | 2024-04-14T05:44:23Z |
| format | Article |
| id | doaj.art-e6fdeedd8b1e4b34b60a5c2149ffba1a |
| institution | Directory Open Access Journal |
| issn | 2261-2424 |
| language | English |
| last_indexed | 2024-04-14T05:44:23Z |
| publishDate | 2022-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | SHS Web of Conferences |
| spelling | doaj.art-e6fdeedd8b1e4b34b60a5c2149ffba1a2022-12-22T02:09:20ZengEDP SciencesSHS Web of Conferences2261-24242022-01-011450102310.1051/shsconf/202214501023shsconf_aeme2022_01023Mapping and analysis using multisource oceanic satellite data and google earth engineKang Yan0Wang Jun1Institute of Land and Urban-Rural Development, Zhejiang University of Finance and EconomicsCollege of Mechanical and Electrical Engineering, China Jiliang UniversityOcean satellite observation because of its large coverage area and high frequency observation become ever more important data and information source with global climate changing, ocean resources protecting and oceanic engineering projects implementing. Oceanic satellite data characteristically include multi-physical parameters, are the product of multi-level processing and are multi-sourced data. Therefore, oceanic satellite data often have different manifestations making the understanding and use of these data challenging, and there is an urgent need for a flexible platform to share the data and merge different kinds of the data information. Here we use Google Earth Engine that make these data easily understandable and a fully synthesized and comprehensive visualization. Then the key techniques for creating 2D and 3D visualizations of oceanic satellite data using KML and Google Earth are detailed in this paper. As an example, multi-sourced satellite data including horizontal distribution and vertical profiles of Typhoon Morakot in August 2009 are combined on Google Earth with three-dimensional visualization. We have extended this research and developed a web service system based on an oceanic satellite visualization data model to dynamically display different types of the oceanic satellite data on Google Earth.https://www.shs-conferences.org/articles/shsconf/pdf/2022/15/shsconf_aeme2022_01023.pdf |
| spellingShingle | Kang Yan Wang Jun Mapping and analysis using multisource oceanic satellite data and google earth engine SHS Web of Conferences |
| title | Mapping and analysis using multisource oceanic satellite data and google earth engine |
| title_full | Mapping and analysis using multisource oceanic satellite data and google earth engine |
| title_fullStr | Mapping and analysis using multisource oceanic satellite data and google earth engine |
| title_full_unstemmed | Mapping and analysis using multisource oceanic satellite data and google earth engine |
| title_short | Mapping and analysis using multisource oceanic satellite data and google earth engine |
| title_sort | mapping and analysis using multisource oceanic satellite data and google earth engine |
| url | https://www.shs-conferences.org/articles/shsconf/pdf/2022/15/shsconf_aeme2022_01023.pdf |
| work_keys_str_mv | AT kangyan mappingandanalysisusingmultisourceoceanicsatellitedataandgoogleearthengine AT wangjun mappingandanalysisusingmultisourceoceanicsatellitedataandgoogleearthengine |