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A WCS-based approach to integrate satellite imagery data in wildfire simulation

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Detalhes bibliográficos
Resumo:This paper describes the integration of multi-dimensional data from satellite sensors in a Civil Protection application that simulates fire spread. The approach uses standard Web Coverage Services from OGC to fetch and process land cover and recently burned areas, available in the form of satellite imagery data previously captured by the MODIS sensor, to automatically generate renovated fuel maps. The proposed architecture is based on rasdaman, a domain-independent database management system (DBMS) that offers a suite of WCS services on top of the DBMS. In the current work we extended rasdaman with facilities to: (i) insert and retrieve multi-layer coverages from WCS, (ii) support new formats, such as HDF, adequate for satellite imagery and multi-layer files, and (iii) support Coordinate Reference Systems. We also demonstrate that it is feasible to use MODIS datasets to automatically compute valuable and regularly updated fuel maps, used as input of fire spread simulations. The results also show that in spite of using inexpensive general and low resolution (500m) MODIS maps, we obtained quite acceptable results when compared with the static ones, which are tailored and higher resolution (80m).
Autores principais:Esteves, António
Outros Autores:Pina, António Manuel Silva
Assunto:OGC standards Satellite datasets MODIS sensor Wildfire simulation WCS
Ano:2012
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:This paper describes the integration of multi-dimensional data from satellite sensors in a Civil Protection application that simulates fire spread. The approach uses standard Web Coverage Services from OGC to fetch and process land cover and recently burned areas, available in the form of satellite imagery data previously captured by the MODIS sensor, to automatically generate renovated fuel maps. The proposed architecture is based on rasdaman, a domain-independent database management system (DBMS) that offers a suite of WCS services on top of the DBMS. In the current work we extended rasdaman with facilities to: (i) insert and retrieve multi-layer coverages from WCS, (ii) support new formats, such as HDF, adequate for satellite imagery and multi-layer files, and (iii) support Coordinate Reference Systems. We also demonstrate that it is feasible to use MODIS datasets to automatically compute valuable and regularly updated fuel maps, used as input of fire spread simulations. The results also show that in spite of using inexpensive general and low resolution (500m) MODIS maps, we obtained quite acceptable results when compared with the static ones, which are tailored and higher resolution (80m).