The results of a paleomagnetic study along the fore arc of southern Peru (15–18°S) and northern Chile (18–19°S) are reported from middle to late Miocene ignimbrites (7 sites), late Oligocene to early Miocene ignimbrites (72 sites), Paleogene sediments (20 sites), and Mesozoic and Paleocene volcanics and intrusions (31 sites). Comparison of locality‐mean directions with expected paleomagnetic directions indicates vertical axis rotations ranging from 5.2 ± 11.3° clockwise to 55.6 ± 7.0° counterclockwise. Spatially, the magnitude of counterclockwise rotations increases northward from ∼0° within the Chilean fore arc south of 18°30′S to >45° north of 16°30′S. In southern Peru, paleomagnetic rotations recorded in Paleogene red beds decrease from late Eocene to late Oligocene, whereas Miocene ignimbrites display no evidence of rotation. These new results confirm that the rotations recorded in the fore arc of southern Peru were acquired at least before ∼15 Ma, and probably before 25 Ma, and thus prior to the late Neogene shortening of the sub‐Andes. The onset of major Andean shortening in the Eastern Cordillera during the latest Eocene–earliest Oligocene is interpreted to have triggered the bending of the Peruvian fore arc. The region of the Peruvian fore arc with the largest rotations appears to be the fore‐arc counterpart of the Abancay deflection, a remarkable NE‐SW offset in the axis of the Eastern Cordillera induced by a major regional preorogenic structure. We underline that the Abancay deflection should be seen as the northwestern boundary, and therefore as a key element, of the Bolivian Orocline.

One of the seven potentially active andesite stratovolcanoes in southern Peru, Misti (5822 m), located I 7 km northeast and 3.5 km above Arequipa, represents a major threat to the population (-900,000 inhabitants). Our recent geophysical and geochemical research comprises an extensive self-potential (SP) data set, an audio-magnetotelluric (AM1) profile across the volcano and CO 2 concentrations in the soil along a radial profile. The SP survey is the first of its kind in providing a complete mapping of a large andesitic stratovolcano 20 km in diameter. The SP mapping enables us to analyze the SP signature associated with a subduction-related active volcano. The general SP pattern of Misti is similar to that of most volcanoes with a hydrogeologic zone in the lower flanks and a hydrothermal zone in the upper central area. A quasi-systematic relationship exists between SP and elevation. Zones with constant SP/altitude gradients (Ce) are observed in both hydrogeologic (negative Ce) and hydrothermal (positive Ce) zones. Transition zones between the different Ce zones, which form a , concentric pattern around the summit, have been interpreted in terms of lateral heterogeneities in the lithology. The highest amplitudes of SP anomalies seem to coincide with highly resistive zones. The hydrothermal system 6 km in diameter, which extends over an area much larger than the summit caldera, may be constrained by an older, concealed collapse caldera. A sealed zone has apparently developed through alteration in the hydrothermal system, blocking the migration of CO 2 upward. Significant CO 2 emanations are thus observed on the lower flanks but are absent above the hydrothermal zone.

Environmental monitoring is a topic of increasing interest, especially concerning the matter of natural hazards prediction. Regarding volcanic unrest, effective methodologies along with innovative and operational tools are needed to monitor, mitigate and prevent risks related to volcanic hazards. In general, the current approaches for volcanoes monitoring are mainly based on the manual analysis of various parameters, including gas leaps, deformations measurements and seismic signals analysis. However, due to the large amount of data acquired by in situ sensors for long term monitoring, manual inspection is no longer a viable option. As in many Big Data situations, classic Machine Learning approaches are now considered to automatize the analysis of years of recorded signals, thereby enabling monitoring at a larger scale. This paper focuses on integrated and operational tools dedicated to the automatic analysis of volcano-seismic signals. Namely we review (i) tools for the optimal representation of volcano-seismic signals (feature space) and the available methods for volcano-seismic events (ii) detection and (iii) classification. We then propose an architecture for the automatic classification of volcano-seismic events. Our prediction system is tested on 6 years of recordings containing 109434 volcano-seismic events acquired from Ubinas volcano (the most active volcano in Perú). Our new proposed model is build using supervised machine learning algorithms (Support Vector Machine) and reaches 92.2% of correct classification over six classes. This prediction model is then used to fully analyze the 6 years of recorded signals.

We use interferometric synthetic aperture radar (InSAR) and local seismic data to investigate the cause of earthquake sequences near Sabancaya volcano in southern Peru from 2002 to 2014, with a particular focus on events leading up to the August 2014 phreatic eruption. InSAR‐observed deformation associated with earthquake swarms in late 2002, February 2013, and July 2013 is modeled by fault slip, with no need for magmatic sources to explain the deformation. The majority of the seismicity is an expression of the regional tectonic system, which is characterized by E‐W trending normal faults, but a link to the magmatic system is possible. The Mw 5.9 earthquake on 17 July 2013 occurred on a previously unmapped normal fault that continued to deform in the months following the earthquake. An increase in long period and hybrid seismicity and changes in fumarolic emissions in 2013–2014 culminating in the August 2014 eruption indicates the involvement of both tectonic and magmatic systems.

Thermal Remote Sensing for Volcano Monitoring volcanological community. The results presented clearly demonstrate how the open access of satellite thermal data and the sharing of derived products allow a better understanding of ongoing volcanic phenomena, and therefore constitute an essential requirement for the assessment of volcanic hazards.