The Global Conflict Risk Index (GCRI): Regression model, data ingestion, processing and output methods

The GCRI is a quantitative conflict risk model, developed by the JRC and based solely on open source data, providing quantitative input to the EU early warning framework, one input to the EU Conflict Early Warning System (EWS), developed by the European External Action Service (EEAS) in close partnership with the European Commission to enhance the EU's conflict prevention capacities. The GCRI distinguishes between three types of violent conflict a state may experience: civil war over national power, subnational conflicts over secession, autonomy, or resources, and conflicts in the international sphere. While the latter are not currently modelled by GCRI, for the first two the index quantifies the probability and the intensity respectively of national and subnational conflicts occurring in the next one to four years. Relying on historical data and a statistical model that includes political, socio-economic, environmental and security variables, it assesses the level and likelihood of future conflicts The GCRI is composed of two statistical models: the regression model and the composite model. Both models are based on twenty-four individual variables. This report presents the work done between February 2017 and September 2017, specifically focused on improving the documentation on the regression model. The present report describes on the one hand the regression model, including the input data and the model itself. On the other hand, it presents the statistical significance test and the matrix of confusion that have been performed, in order to get a highly detailed analysis of the performances of the model. The results of these analyses are presented in chapter 4 and 5. This report is part of a series of documentations produced in 2017 aiming at improving the GCRI models with greater transparency and robustness. This work contributes to enhancing the GCRI performance.JRC.E.1-Disaster Risk 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

L’utilisation de la méthode quantitative et des bases de données pour appréhender les questions de défense et de sécurité internationale

International audienc

Les restrictions à la pratique de l’activité physique: adéquation entre droit du confinement et santé publique

International audienc

Les restrictions à la pratique de l’activité physique: adéquation entre droit du confinement et santé publique

International audienc

Le numérique au service d’un idéal de non-violence

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La non violence: théorie, pratique et bases de données

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Les restrictions à la pratique de l’activité physique: adéquation entre droit du confinement et santé publique

International audienc

Short Term and Event Interdependence Matter: A Political Economy Continuous Model of Civil War

This paper builds on several existing empirical models that have been widely used in studying the causes of civil war and/or internal political instability. It begins by showing that some widespread models have been inadequate in both accurately modeling causal relations and time dependence among several kinds of events, and to take advantage of some highly disaggregated (daily) datasets. It does so thanks to graphical comparisons of several existing models and dataset arrangements, followed by an intuitive graphical representation of the proposed model. Then, mathematical tools are used to compare the latter to a particular Generalized Linear Model. It is shown how the proposed model can be implemented practically, and it is finally applied to the period 1962-1997 to study the impact of International Financial Institutions' Structural Adjustment Programs on the risk of civil war.

Innovations scientifiques et technologiques liées à la guerre et à la paix: les problèmes du découplage avec les innovations requises dans la pratique professionnelle

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