A new spatial database and software layer supporting the JRC image information query (IQ) system

The database is one of the core components of the image information query (IQ) system: all the information involved in the system is stored inside the database. The database is a searchable archive for the data, the processes, and the satellite imagery processing. With the new database structure it is possible to keep track of every image processing executed inside the system, of all parameters involved to obtain a certain result, and of every input and output involved in the processing. Moreover, the database contains a replica of the metadata of the CID Portal's satellite imagery, with additional information useful for the team’s image processing needs. The database structure is automatically generated and supported by a Python software layer which is also starting the processing on the Linux cluster.JRC.G.2-Global security and crisis managemen

A Global Human Settlement Layer from optical high resolution imagery - Concept and first results

A general framework for processing of high and very-high resolution imagery for creating a Global Human Settlement Layer (GHSL) is presented together with a discussion on the results of the first operational test of the production workflow. The test involved the mapping of 24.3 millions of square kilometres of the Earth surface spread over four continents, corresponding to an estimated population of 1.3 billion of people in 2010. The resolution of the input image data ranges from 0.5 to 10 meters, collected by a heterogeneous set of platforms including satellite SPOT (2 and 5), CBERS-2B, RapidEye (2 and 4), WorldView (1 and 2), GeoEye-1, QuickBird-2, Ikonos-2, and airborne sensors. Several imaging modes were tested including panchromatic, multispectral and pan-sharpened images. A new fully automatic image information extraction, generalization and mosaic workflow is presented that is based on multiscale textural and morphological image features extraction. New image feature compression and optimization are introduced, together with new learning and classification techniques allowing for the processing of HR/VHR image data using low-resolution thematic layers as reference. A new systematic approach for quality control and validation allowing global spatial and thematic consistency checking is proposed and applied. The quality of the results are discussed by sensor, by band, by resolution, and eco-regions. Critical points, lessons learned and next steps are highlighted.JRC.G.2-Global security and crisis managemen

EOS workshop

The Joint Research Centre (JRC) of the European Commission has set up the Big Data Analytics Platform to enable the JRC projects to process and analyse big data, extracting knowledge and insights in support of EU policy making. Since 2016, EOS is the main storage component of the platform. In 2020, the total gross capacity of this instance has reached 19 PiB. The Big Data Analytics Platform is actively used by more than 40 JRC projects, covering a wide range of data analysis activities. To support the growing needs for data storage and processing capacity, the platform has been extended over the last year. Eight new FSTs have been added, for a space increase of 3.5 PiB. In addition, to increase the security of the platform, the team started to migrate the EOS nodes in a segregated VLAN. The presentation will give an overview about the Big Data Analytics Platform and its EOS storage back-end, presenting the current status, experiences made and the issues identified

A new map of the European settlements by automatic classification of 2.5m resolution SPOT data

This paper describes the methodology and the results of a comprehensive automatic image classification task aiming to map the European settlements using 2.5m-resolution input data. The processing approach is consistent with the Global Human Settlement Layer (GHSL) [1]; certain adjustments were driven by the specific input data characteristics and the specific application needs. In the study discussed here, a total of 2,275 SPOT-5 3-band pan-sharpened images were processed. The main output is a seamless 10m-resolution raster mosaic. Each pixel value expresses the proportion of the pixel area covered by buildings. Complementary information about the open spaces between buildings and the proportion of vegetation is also produced at the same spatial resolution.JRC.G.2-Global security and crisis managemen

A Global Human Settlement Layer From Optical HR/VHR RS Data: Concept and First Results

A general framework for processing high and veryhigh resolution image data in support to a Global Human Settlement Layer (GHSL) is presented together with a discussion on the results of the first operational test of the production workflow. The test involved the mapping of 24.3 millions of square kilometres of the Earth surface spread in four continents, corresponding to an estimated population of 1.3 billions of people in 2010. The resolution of the input image data ranges from 0.5 to 10 meters, collected by a heterogeneous set of platforms including satellite SPOT (2 and 5), CBERS 2B, RapidEye (2 and 4), WorldView (1 and 2), GeoEye 1, QuickBird 2, Ikonos 2, and airborne sensors. Several imaging mode were tested including panchromatic, multispectral and pan-sharpened images. A new fully automatic image information extraction, generalization and mosaic workflow is presented that is based on multiscale textural and morphological image features extraction. New image feature compression and optimization are introduced, together with new earning and classification techniques allowing for the processing of HR/VHR image data using low-resolution thematic layers as reference. A new systematic approach for quality control and validation allowing global spatial and thematic consistency checking is proposed and applied. The quality of the results are discussed by sensor, by band, by resolution, and eco-regions. Critical points, lessons learned and next steps are highlighted.JRC.G.2-Global security and crisis managemen