Global Human Settlement Analysis for Disaster Risk Reduction

The Global Human Settlement Layer (GHSL) is supported by the European Commission, Joint Research Center (JRC) in the frame of his institutional research activities. Scope of GHSL is developing, testing and applying the technologies and analysis methods integrated in the JRC Global Human Settlement analysis platform for applications in support to global disaster risk reduction initiatives (DRR) and regional analysis in the frame of the European Cohesion policy. GHSL analysis platform uses geo-spatial data, primarily remotely sensed and population. GHSL also cooperates with the Group on Earth Observation on SB-04-Global Urban Observation and Information, and various international partners andWorld Bank and United Nations agencies. Some preliminary results integrating global human settlement information extracted from Landsat data records of the last 40 years and population data are presented.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

Visual collection of built up information from high resolution satellite imagery

The document summarizes the steps, procedures, information infrastructure used for collecting built up information from satellite imagery. The document is intended as a reference for visual interpreters. The document also summarizes the lessons learned by photo-interpreters for imagery covering Europe.JRC.G.2-Global security and crisis managemen