Ionospheric error contribution to GNSS single-frequency navigation at the 2014 solar maximum

For single-frequency users of the global satellite navigation system (GNSS), one of the main error contributors is the ionospheric delay, which impacts the received signals. As is well-known, GPS and Galileo transmit global models to correct the ionospheric delay, while the international GNSS service (IGS) computes precise post-process global ionospheric maps (GIM) that are considered reference ionospheres. Moreover, accurate ionospheric maps have been recently introduced, which allow for the fast convergence of the real-time precise point position (PPP) globally. Therefore, testing of the ionospheric models is a key issue for code-based single-frequency users, which constitute the main user segment. Therefore, the testing proposed in this paper is straightforward and uses the PPP modeling applied to single- and dual-frequency code observations worldwide for 2014. The usage of PPP modeling allows us to quantify—for dual-frequency users—the degradation of the navigation solutions caused by noise and multipath with respect to the different ionospheric modeling solutions, and allows us, in turn, to obtain an independent assessment of the ionospheric models. Compared to the dual-frequency solutions, the GPS and Galileo ionospheric models present worse global performance, with horizontal root mean square (RMS) differences of 1.04 and 0.49 m and vertical RMS differences of 0.83 and 0.40 m, respectively. While very precise global ionospheric models can improve the dual-frequency solution globally, resulting in a horizontal RMS difference of 0.60 m and a vertical RMS difference of 0.74 m, they exhibit a strong dependence on the geographical location and ionospheric activity.     

Using geographically weighted regression kriging for crop yield mapping in West Africa

Geographical information systems support the application of statistical techniques to map spatially referenced crop data. To do this in the optimal way, errors and uncertainties have to be minimized that are often associated with operations on the data. This paper applies a spatial statistical approach to upscale crop yields from the field level toward the scale of Burkina Faso. Observed yields were related to the Normalized Difference Vegetation Index derived from SPOT-VEGETATION. The objective was to quantify the uncertainties at the subsequent steps. First, we applied a point pattern analysis to examine uncertainties due to the sampling network of field surveys in the country. Second, geographically weighted regression kriging (GWRK) was applied to upscale the yield observations and to quantify the corresponding uncertainty. The proposed method was demonstrated with the mapping of sorghum yields in Burkina Faso and results were compared with those from regression kriging (RK) and kriging with external drift using a local kriging neighborhood (KEDLN). The proposed method was validated with independent yield observations obtained from field surveys. We observed that the lower uncertainty range value increased by 39%, and the upper uncertainty range value decreased by 51%, when comparing GWRK with RK and KEDLN. Moreover, GWRK reduced the prediction error variance as compared to RK (20 vs. 31) and to KEDLN (20 vs. 39). We found that climate and topography had a major impact on the country’s sorghum yields. Further, the financial ability of farmers influenced the crop management and, thus, the sorghum crop yields. We concluded that GWRK effectively utilized information present in the covariate datasets and improved the accuracies of both the regional-scale mapping of sorghum yields and was able to quantify the associated uncertainty.     

Galactosynthesis predictions at high redshift

We predict the Tully–Fisher (TF) and surface-brightness–magnitude relations for disc galaxies at     and discuss the origin of these scaling relations and their scatter. We find that both halo dynamics and the star formation history play important roles, and we show that the variation of the TF relation with redshift can be a potentially powerful discriminator of galaxy-formation models. In particular, the TF relation at high redshift might be used to break parameter degeneracies among galactosynthesis models at     , as well as to constrain the redshift distribution of collapsing dark-matter haloes, the star formation history and baryon fraction in the disc and the distribution of halo spins.     

Baryonic conversion tree: the global assembly of stars and dark matter in galaxies from the Sloan Digital Sky Survey

Using the spectroscopic sample of the Sloan Digital Sky Survey Data Release 1 (SDSS DR1), we measure how gas was transformed into stars as a function of time and stellar mass: the baryonic conversion tree (BCT). There is a clear correlation between early star formation activity and present-day stellar mass: the more massive galaxies have formed approximately 80 per cent of their stars at   z > 1  , while for the less massive ones the value is only approximately 20 per cent. By comparing the BCT with the dark matter merger tree, we find indications that star formation efficiency at   z > 1  had to be approximately a factor of two higher than today (∼10 per cent) in galaxies with present-day stellar mass larger than  2 × 10¹¹ M_⊙  , if this early star formation occurred in the main progenitor. Therefore, the λ cold dark matter (LCDM) paradigm can accommodate a large number of red objects. On the other hand, in galaxies with present-day stellar mass less than  10¹¹ M_⊙  , efficient star formation seems to have been triggered at   z ∼ 0.2  . We show that there is a characteristic mass  ( M _*∼ 10¹⁰ M_⊙)  for feedback efficiency (or lack of star formation). For galaxies with masses lower than this, feedback (or star formation suppression) is very efficient while for higher masses it is not. The BCT, determined here for the first time, should be an important observable with which to confront theoretical models of galaxy formation.     

Size-fractionated phytoplankton biomass,primary production and respiration in the Nervión–Ibaizabal estuary: A comparison with other nearshore coastal and estuarine ecosystems from the Bay of Biscay

The seasonal pattern of size-fractionated phytoplankton biomass, primary production and respiration was investigated along the longitudinal axis of the Nervión–Ibaizabal estuary (Bay of Biscay) from April 2003 to September 2004. Environmental factors influencing phytoplankton dynamics were also studied. Chlorophyll a biomass showed a longitudinal pattern of increase from the outer Abra bay to the inner estuary. On a seasonal scale, in the intermediate and inner estuary phytoplankton biomass maxima were registered in summer, the warmest and driest season, whereas in the outer bay chlorophyll a peaks occurred in May 2004, but were delayed to August 2003, likely due to a very rainy spring. Data suggest that river flow exerts a marked influence on the timing of phytoplankton biomass maxima in this estuary, decreased river flows providing a lowering of turbidity and an increase in water residence time needed for chlorophyll a to build up. Nutrient concentrations were high enough not to limit phytoplankton growth throughout the annual cycle, except silicate and occasionally phosphate in the outer bay during summer. Silicate concentration correlated positively with river flow, whereas ammonium and phosphate maximum values were generally measured in the mid-estuary, suggesting the importance of allochthonous anthropogenic sources. In the intermediate and inner estuary phytoplankton biomass was generally dominated by >8 μm size-fraction (ca. 60%), but in August 2003 <8 μm size-fraction increased its contribution in the intermediate estuary. It is argued that the lower nutrient concentrations measured in August 2003 than in August 2004 could have played a role. This is the first study in which phytoplankton primary production rates have been measured along the longitudinal axis of the Nervión–Ibaizabal estuary. Throughout the annual cycle these rates ranged from 0.001 to 3.163 g C m^?3 d^?1 and were comparable to those measured in nearby small estuaries of the Basque coast and other larger estuaries on the Bay of Biscay. Surface plankton community respiration rate maxima were measured during the spring 2004 chlorophyll a peak in the Abra bay and in summer months at the mid and inner estuary, coinciding with chlorophyll a biomass and primary production maxima. In general, respiration rates showed a positive correlation with temperature. In order to compare results from the Nervión–Ibaizabal estuary with other nearshore coastal and estuarine ecosystems within the Bay of Biscay a review of existing information on phytoplankton biomass and primary production dynamics was performed.     

Numerical analysis of wave loads for coastal structure stability

The numerical model COBRAS-UC [Losada, I.J., Lara, J.L., Guanche,R., Gonzalez-Ondina, J.M. (2008). Numerical analysis of wave overtopping of rubble mound breakwaters. Coastal Engineering, Vol 55 (1), 47–62.] is used to carry out a two-dimensional analysis of wave induced loads on coastal structures. The model calculates pressure, forces and moments for two different cross-sections corresponding to a low-mound and a conventional rubble-mound breakwater with a crown-wall under regular and irregular incident wave conditions. Predicted results are compared with experimental information provided in Losada et al. [Losada, I.J., Lara, J.L., Guanche,R., Gonzalez-Ondina, J.M. (2008). Numerical analysis of wave overtopping of rubble mound breakwaters. Coastal Engineering, Vol 55 (1), 47–62.] and Lara et al. [Lara, J.L., Losada, I.J., Guanche, R. (2008). “Wave interaction with low mound breakwaters using a RANS model”. Ocean engineering (35), pp 1388–1400; doi:10.1016/j.oceaneng.2008.05.006.] on a 1:20 scale. Good agreement is found, and the differences between both typologies are explained in detail. Additionally, numerical results are also compared with several semi-empirical formulae recommended for design at both the 1:20 model scale and two prototype cross-sections. Results suggest that COBRAS-UC is able to provide realistic stability information that can be used to complete the approach based on currently existing methods and tools.     

Cascade multitemporal classification based on fuzzy Markov chains

This paper proposes a new fuzzy cascade multitemporal classification method based on Fuzzy Markov Chains. This method differs from prior fuzzy multitemporal approaches proposed thus far, as the method does not require the knowledge of the true class at an earlier date; instead it uses the attributes of the image object being classified at the earlier date. This method combines the fuzzy, non-temporal, classification of a geographical region at two points in time to provide a single unified result. A transformation law based on class transition possibilities projects the earlier classification onto the later date before combining both results. Performance analysis was conducted upon a sequence of three LANDSAT images from the central region of Brazil using a Genetic Algorithm to estimate transition possibilities. The analysis showed that the increase in performance is highly dependent on whether or not a significant correlation exists between the temporal data sets, as well as on the accuracy of the monotemporal classifier at the earlier date. While the monotemporal approach used in the experiments attained an average class accuracy of approximately 55%, the multitemporal scheme achieved between 65% and 95%. Similar results in terms of overall accuracy were also observed. Furthermore, compared to two alternative cascade multitemporal classification approaches, the proposed method consistently showed better results.