Jones, M. I., Wittenmyer, R., Aguilera-Gomez, C., Soto, M. G., Torres, P., Trifonov, T., et al. (2021). Four Jovian planets around low-luminosity giant stars observed by the EXPRESS and PPPS. Astron. Astrophys., 646, A131.
Abstract: We report the discovery of planetary companions orbiting four low-luminosity giant stars with M-star between 1.04 and 1.39 M-circle dot. All four host stars have been independently observed by the EXoPlanets aRound Evolved StarS (EXPRESS) program and the Pan-Pacific Planet Search (PPPS). The companion signals were revealed by multi-epoch precision radial velocities obtained in nearly a decade. The planetary companions exhibit orbital periods between similar to 1.2 and 7.1 yr, minimum masses of m(p)sin i similar to 1.8-3.7 M-J, and eccentricities between 0.08 and 0.42. With these four new systems, we have detected planetary companions to 11 out of the 37 giant stars that are common targets in the EXPRESS and PPPS. After excluding four compact binaries from the common sample, we obtained a fraction of giant planets (m(p) greater than or similar to 1- 2 M-J) orbiting within 5 AU from their parent star of f = 33.3(-7.1)(+9.0)%. This fraction is slightly higher than but consistent at the 1 sigma level with previous results obtained by different radial velocity surveys. Finally, this value is substantially higher than the fraction predicted by planet formation models of gas giants around stars more massive than the Sun.
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Miranda, A., Mentler, R., Moletto-Lobos, I., Alfaro, G., Aliaga, L., Balbontin, D., et al. (2022). The Landscape Fire Scars Database: mapping historical burned area and fire severity in Chile. Earth Syst. Sci. Data, 14(8), 3599–3613.
Abstract: Achieving a local understanding of fire regimes requires high-resolution, systematic and dynamic databases. High-quality information can help to transform evidence into decision-making in the context of rapidly changing landscapes, particularly considering that geographical and temporal patterns of fire regimes and their trends vary locally over time. Global fire scar products at low spatial resolutions are available, but high-resolution wildfire data, especially for developing countries, are still lacking. Taking advantage of the Google Earth Engine (GEE) big-data analysis platform, we developed a flexible workflow to reconstruct individual burned areas and derive fire severity estimates for all reported fires. We tested our approach for historical wild-fires in Chile. The result is the Landscape Fire Scars Database, a detailed and dynamic database that reconstructs 8153 fires scars, representing 66.6% of the country's officially recorded fires between 1985 and 2018. For each fire event, the database contains the following information: (i) the Landsat mosaic of pre- and post-fire images; (ii) the fire scar in binary format; (iii) the remotely sensed estimated fire indexes (the normalized burned ratio, NBR, and the relative delta normalized burn ratio, RdNBR); and two vector files indicating (iv) the fire scar perimeter and (v) the fire scar severity reclassification, respectively. The Landscape Fire Scars Database for Chile and GEE script (JavaScript) are publicly available. The framework developed for the database can be applied anywhere in the world, with the only requirement being its adaptation to local factors such as data availability, fire regimes, land cover or land cover dynamics, vegetation recovery, and cloud cover. The Landscape Fire Scars Database for Chile is publicly available in https://doi.org/10.1594/PANGAEA.941127 (Miranda et al., 2022).
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