Diapositivas presentadas en el Encuentro Científico Internacional, ECI-2010, celebrado en Lima, Perú.

Ponencia informativa presentada en el XIII Encuentro Científico Internacional, (ECI 2010v), realizado del 5 al 8 de enero de 2010 en la ciudad de Lima.

An ionogram is a graph that shows the distance that a vertically transmitted wave, of a given frequency, travels before returning to the earth. The ionogram is shaped by making a trace of this distance, which is called virtual height, against the frequency of the transmitted wave. Along with the echoes of the ionosphere, ionograms usually contain a large amount of noise of different nature, that must be removed in order to extract useful information. In the present work, we propose to use a convolutional neural network model to improve the quality of the information obtained from digital ionograms, compared to that using image processing and machine learning techniques, in the generation of electronic density profiles. A data set of more than 900,000 ionograms from 5 ionospheric observation stations is available to use.

The heavy volume of data that GPS, ionosondes and magnetometers are continuously collecting is stored in the LISN server and managed using a set of rules that are intended to provide an efficiently way to manipulate the large data sets and also implement an adequate method to systematically transform all this information into knowledge. LISN integrates multiple data sources and should provide security, integrity and availability in a multi-user environment. Data from the remote stations arrives to the server continuously and is stored, processed and distributed. This data is easily available and in some cases freely accessible to the community promoting research and encouraging collaboration between users.

An ionogram is a graph of the time that a vertically transmitted wave takes to return to the earth as a function of frequency. Time is typically represented as virtual height, which is the time divided by the speed of light. The ionogram is shaped by making a trace of this height against the frequency of the transmitted wave. Along with the echoes of the ionosphere, ionograms usually contain a large amount of noise and interference of different nature that must be removed in order to extract useful information. In the present work, we propose a method based on convolutional neural networks to extract ionospheric echoes from digital ionograms. Extraction using the CNN model is compared with extraction using machine learning techniques. From the extracted traces, ionospheric parameters can be determined and electron density profile can be derived.

Diapositivas presentadas en el Encuentro Científico Internacional, ECI-2010, celebrado en Lima, Perú.

Presentation at the 2021 CEDAR Virtual Workshop, June 20-25.

Presentation at the 2020 CEDAR Virtual Meeting, June 22-26.

Diapositivas presentadas en el 2010 CEDAR Workshop, University of Colorado, Boulder, CO, 20-25 June 2010.

Poster presented at the 2021 CEDAR Virtual Workshop, June 20-25.

Special thanks to the CIELO (Cluster of Instruments for Equatorial & Low-Latitude Observations) staff at the Jicamarca Radio Observatory for their technical support, and to Joaquim Fortuny Ph.D. for his guidance in the implementation of this project. Also, We thank FONDECYT for the support to this project through the agreement N?-PIAP-2-P-434-14. The Jicamarca Radio Observatory is a facility of the Instituto Geofísico del Perú (IGP) operated with support from the NSF award AGS-1433968 through Cornell University.

Presentado en MST12 - 12th Workshop on Technical and Scientific Aspects of MST Radars, London, Ontario, Canada, 17-23 May 2009.

Resumen presentado en: URSI General Assembly, New Delhi, October 2005.

Poster presented at the 2023 CEDAR Workshop, San Diego, CA - USA, June 25 - 30

Este proyecto ha generado importantes contribuciones para fortalecer la gestión del riesgo de desastres en el Perú, especialmente en lo que respecta al monitoreo y evaluación de deslizamientos de tierra. La implementación del prototipo de radar GB-SAR, y su operación en zonas críticas como Cuenca y Tabernuy, brinda información detallada sobre los movimientos del terreno, lo que permite detectar áreas inestables y cuantificar los desplazamientos con precisión milimétrica. Estos datos son de gran utilidad para los tomadores de decisiones en la gestión de riesgos, ya que les permite identificar oportunamente las zonas más vulnerables y adoptar medidas preventivas adecuadas, tales como evacuaciones, reubicaciones o trabajos de estabilización. Asimismo, los estudios geodinámicos y geotécnicos realizados han revelado las características físicas y los problemas geológicos que ...

For the first time, equatorial plasma depletions (EPDs) have been imaged in the longitude-altitude plane using radiotomography. High-resolution (~10 km) reconstructions of electron density were derived from total electron content (TEC) measurements provided by a receiver array in Peru. TEC data were obtained from VHF/UHF signals transmitted by the C/NOFS CERTO beacon. EPDs generated pre-midnight were observed near dawn. On one night, the bubble densities were highly reduced, 100-1000 km wide, and embedded within a layerlike ionosphere. Three nights later, the EPDs exhibited similar features, but were embedded in a locally uplifted ionosphere. The C/NOFS in-situ instruments detected a dawn depletion where the reconstruction showed lifted EPDs, implying that the postmidnight electric fields raised sections of ionosphere to altitudes where embedded/reactivated fossil-EPDs were detected ...