Deriving the Dynamical Masses of Ultra-Luminous X-ray Sources with OSIRIS

Ultra Luminous X-ray Sources (ULXs) are extragalactic X-ray point sources with LX ∼ 1039 − 1041 erg s−1 discovered in the 80s with the Einstein satellite and confirmed as black hole X-ray binaries during the last decade. The nature of the compact object is highly controversial. They could be super-Eddington stellar-mass black holes or intermediate mass black holes. Deriving dynamical masses of the brightest ULXs, which can be done with OSIRIS, is the only way to find out the nature of the compact object.

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.

Proposal of a New Parameter for the Weathering Characterization of Carbonate Flysch-Like Rock Masses: The Potential Degradation Index (PDI)

The susceptibility of clay bearing rocks to weathering (erosion and/or differential degradation) is known to influence the stability of heterogeneous slopes. However, not all of these rocks show the same behaviour, as there are considerable differences in the speed and type of weathering observed. As such, it is very important to establish relationships between behaviour quantified in a laboratory environment with that observed in the field. The slake durability test is the laboratory test most commonly used to evaluate the relationship between slaking behaviour and rock durability. However, it has a number of disadvantages; it does not account for changes in shape and size in fragments retained in the 2 mm sieve, nor does its most commonly used index (Id2) accurately reflect weathering behaviour observed in the field. The main aim of this paper is to propose a simple methodology for characterizing the weathering behaviour of carbonate lithologies that outcrop in heterogeneous rock masses (such as Flysch slopes), for use by practitioners. To this end, the Potential Degradation Index (PDI) is proposed. This is calculated using the fragment size distribution curves taken from material retained in the drum after each cycle of the slake durability test. The number of slaking cycles has also been increased to five. Through laboratory testing of 117 samples of carbonate rocks, extracted from strata in selected slopes, 6 different rock types were established based on their slaking behaviour, and corresponding to the different weathering behaviours observed in the field.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.