Recent shift from forest to savanna burning in the Amazon Basin observed by satellite

The numbers of fires detected on forest, savanna and transition lands during the 2002-10 biomass burning seasons in Amazonia are shown using fire count data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). The ratio of forest fires to savanna fires has varied substantially over the study period, with a maximum ratio of 0.65:1 in 2005 and a minimum ratio of 0.27:1 in 2009, with the four lowest years occurring in 2007-10. The burning during the droughts of 2007 and 2010 is attributed to a higher number of savanna fires relative to the drought of 2005. A decrease in the regional mean single scattering albedo of biomass burning aerosols, consistent with the shift from forest to savanna burning, is also shown. During the severe drought of 2010, forest fire detections were lower in many areas compared with 2005, even though the drought was more severe in 2010. This result suggests that improved fire management practices, including stricter burning regulations as well as lower deforestation burning, may have reduced forest fires in 2010 relative to 2005 in some areas of the Amazon Basin.

Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning to Optimization of Broad-Band Reflector Antennas Satellite

This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.

Overview of semi-sinusoidal stellar variability with the CoRoT satellite

Context. To date, the CoRoT space mission has produced more than 124 471 light curves. Classifying these curves in terms of unambiguous variab ility behavior is mandatory for obtaining an unbi ased statistical view on th eir controlling root-causes. Aims. The present study provides an overview of semi-sinusoidal light curves observed by the CoRoT exo-field CCDs. Methods. We selected a sample of 4206 light curves presenting well-defined semi-si nusoidal signatures. Th e variability periods were computed based on Lomb-Scargle periodograms, harmonic fits, and visual inspection. Results. Color–period diagrams for the present sample show the trend of an increase of the variability periods as long as the stars evolve. This evolutionary behavior is also noticed when comparing the period distribution in the Galactic center and anti-center directions. These aspect s indicate a compatibility with stellar rotation, although more inform ation is needed to confirm their root- causes. Considering this possi bility, we identified a subset of th ree Sun-like candidates by their photometric peri od. Finally, the variability period versus color diagr am behavior was found to be highly depe ndent on the reddening correction.

Identifying clouds over the Pierre Auger Observatory using infrared satellite data

We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ∼2.4 km by ∼5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.