INPE Spatial Data Infrastructure for Big Spatiotemporal Data Sets Karine Reis Ferreira (INPE-Brazil)
INPE (Brazil) and Big Data I work at INPE (Brazilian National Institute for Space Research). Main gate of INPE in São José dos Campos city. INPE has 13 facilities in Brazil.
INPE (Brazil) and Big Data INPE has many projects that produce and need to deal with big spatiotemporal data sets. PRODES Brazilian Amazon forest monitoring: Deforestation and land change detection based on Earth observation images and time series analyses. time Fire monitoring application: daily fire sports detection using satellite data, for Brazil and South America. Precipitation grids. 220 Landsat scenes to cover the Amazon
What are we doing related to Big Data? We are developing a new Spatial Data Infrastructure (SDI) for deal with these big amount of spatiotemporal data sets.
What are we doing related to Big Data? We are developing a new Spatial Data Infrastructure (SDI) for deal with these big amount of spatiotemporal data sets. Spatial Data Infrastructure is a framework of spatial data, metadata, users and software tools that are interactively connected in order to use spatial data in an efficient and flexible way.
What are we doing related to Big Data? We are developing a new Spatial Data Infrastructure (SDI) for deal with these big amount of spatiotemporal data sets. Key idea: Develop a SDI able to process these data sets in the server side; in a way that users can analyse big spatiotemporal data sets without needing to download them. Remote visualization and analysis Software goes where the data is! Big data sets
INPE SDI for Big Spatiotemporal Data ü Organizing and putting these data sets together in a single SDI ü Using a new technology to store and process big EO satellite images: SciDB Array Database. PRODES, DETER, Fires,... TerraClass Amazonia e Cerrado CanaSat, Cafe, etc... MODIS, LandSat, etc... OBT Vector Data EO Satellite Image Data SciDB + R
INPE SDI for Big Spatiotemporal Data ü Building metadata for these data sets: ISO 19115, INDE, Linded Data + RDF + Semantic Web concepts. / RDF files PRODES, DETER, Fires,... TerraClass Amazonia e Cerrado CanaSat, Cafe, etc... MODIS, LandSat, etc... OBT Vector Data EO Satellite Image Data SciDB + R
INPE SDI for Big Spatiotemporal Data ü Building metadata for these data sets: ISO 19115, INDE, Linded Data + RDF + Semantic Web concepts. Cooperation with our colleague Devika (India) / RDF files PRODES, DETER, Fires,... TerraClass Amazonia e Cerrado CanaSat, Cafe, etc... MODIS, LandSat, etc... OBT Vector Data EO Satellite Image Data SciDB + R
INPE SDI for Big Spatiotemporal Data ü Building a discovery module able to search our metadata Discovery module - able to search both metadata / RDF files PRODES, DETER, Fires,... TerraClass Amazonia e Cerrado CanaSat, Cafe, etc... MODIS, LandSat, etc... OBT Vector Data EO Satellite Image Data SciDB + R
INPE SDI for Big Spatiotemporal Data ü Building web services modules for data, metadata and processing Web server of data: WMS, WFS, WCS,.. GeoServer Web server of metadata: Catalog Web Service GeoNetwork / INDE Discovery module - able to search both metadata Web services: metadata, WMS, WCS, processing / RDF files PRODES, DETER, Fires,... TerraClass Amazonia e Cerrado CanaSat, Cafe, etc... MODIS, LandSat, etc... OBT Vector Data EO Satellite Image Data SciDB + R
TerraLib 5.0 / TerraView 5.0 Coverage Series / Raster Web server of data: WMS, WFS, WCS,.. GeoServer Web server of metadata: Catalog Web Service GeoNetwork / INDE Discovery module - able to search both metadata Web services: metadata, WMS, WCS, processing / RDF files PRODES, DETER, Fires,... TerraClass Amazonia e Cerrado CanaSat, Cafe, etc... MODIS, LandSat, etc... OBT Vector Data EO Satellite Image Data SciDB + R
Final remarks ü In this training workshop, I had the opportunity to know a lot of work related to our work at INPE, exchange ideas and think about future cooperations: Cloud-based Geospatial Data analysis and services (CNIC-CAS) Linking the Earth Observation Open Data for Global Change Study (RADI-CAS)...
XIE XIE! karine@dpi.inpe.br THANK TO CODATA AND CHINESE ACADEMY OF SCIENCES (CAS) FOR THIS OPPORTUNITY!