Jean Moulin University Lyon 3

About: Jean Moulin University Lyon 3 is a education organization based out in Lyon, Rhône-Alpes, France. It is known for research contribution in the topics: Computer science & Geology. The organization has 343 authors who have published 572 publications receiving 3175 citations.

Determining paleostresses with ‘incomplete’ data

Abstract: In Chapter 4 , we discussed various methods to reconstruct paleostresses from fault slip data and demonstrated their validity. Unfortunately, in some cases, natural conditions may preclude direct access to fault planes and the measurement of slip vectors. The question of the present chapter is what if no slip or only one slip component is recorded? We will see that modifications of the original method may bring satisfactory solutions to the problem, even when part of the information is missing in the input data. The chapter introduces these original methodologies, starting with semi-analytical forward modelling and progressing and moving to advanced geomechanical numerical modelling.

Reply on RC2

Abstract: Snow avalanches are the predominant hazards in winter in high elevation mountains. They cause damage to both humans and assets but cannot be accurately predicted. Until now, only local maps to estimate snow avalanche risk have been produced. Here we show how remote sensing can accurately inventory large avalanches every year at a basin scale using a 32-yr snow index derived from Landsat satellite archives. This Snow Avalanche Frequency Estimation (SAFE) built in an open-access Google Engine script maps snow hazard frequency and targets vulnerable areas in remote regions of Afghanistan, one of the most data-limited areas worldwide. SAFE correctly detected of the actual avalanches identified on Google Earth and in the field (Probability of Detection 0.77 and Positive Predictive Value 0.96). A total of 810,000 large avalanches occurred since 1990 within an area of 28,500 km2 with a mean frequency of 0.88 avalanches/km2yr−1, damaging villages and blocking roads and streams. Snow avalanche frequency did not significantly change with time, but a northeast shift of these hazards was evident. SAFE is the first robust model that can be used worldwide and is capable of filling data voids on snow avalanche impacts in inaccessible regions.

Pilotage stratégique de la taxe carbone par les entreprises : les enjeux de la performance globale

Abstract: Cette recherche s’interesse a l’opinion des individus, concernant le pilotage strategique de la taxe carbone par les entreprises, en fonction des facteurs de justice sociale. Pour cela elle applique une technique empruntee aux sciences cognitives. Elle aboutit a deux clusters. Le premier regroupe des individus qui jugent acceptable la combinaison des trois choix de gestion de la taxe carbone suivants : augmentation des prix, investissements « low carbon » et absence de delocalisation, conformement aux justices distributive et retributive. Les membres du second cluster quant a eux, jugent acceptable tout choix de gestion de la taxe carbone qui autorise le maintien des prix selon la justice reparatrice. Ces resultats sont a considerer dans la definition des strategies RSE et dans la recherche d’un equilibre des differentes composantes de la performance globale.