Picophytoplankton and bacterioplankton in the Mississippi River plume and its adjacent waters

Picoplankton abundance and distribution in the Mississippi River plume and its adjacent waters were studied during two cruises in April (high discharge) and October (low discharge) 2000 using flow cytometry. Concentrations of photosynthetic picoplankton,Synechococcus and picoeukaryotes were low in the turbid plume water but high in the coastal waters—i.e., the green waters resulting from mixing of river and oceanic waters. In this region, three types ofSynechococcus, characterized by their phycoerythrin chromophore composition, were found:Synechococcus cells with a low phycourobilin to phycoerythrobilin ratio (PUB:PEB) occurred throughout the region and dominated the totalSymechococcus abundance during both seasons; high PUB:PEB cells, which are the dominant strains in the open or blue ocean, occurred only at the outer shelf stations; and PEB-onlySynechococcus were abundant in most of the surveyed area during april, but were not observed during October.Prochlorococcus cyanobacteria only occurred at the oceanic stations, but extended farther inshore in October compared to April. This was a consequence of the reduced discharge and plume size during October. Picophytoplankton were a less important component of total phytoplankton biomass in the turbid river water and more important in the oligotrophic Gulf water. Seasonally, the contribution of picophytoplankton to total phytoplankton biomass in the surveyed area was higher during low discharge in October than during high discharge in April, even though the spring 2000 river discharge was unusually low and might not present a typical high discharge scenario. The abundance of heterotrophic bacteria was weakly correlated to chlorophylla (chla) concentration, but better correlated to picophytoplankton biomass. A higher proportion of High DNA bacteria occurred in the river-impacted regions during both seasons, with the ratio of High DNA bacteria to Low DNA bacteria significantly higher in April.     

Non-Linear Gravitational Clustering Using the Zel'dovich Approximation

As an alternative to computationally expensive N-body simulations for gravitional clustering, the Zel'dovich approximation (ZA) was studied in 3D, 2D and 1D. Plots of the density contrast were compared against linear theory and the exact solution. The ZA was found to perform very well in the linear regime, better than linear theory, and to give a good approximation well into the non-linear regime. This revised version was published online in July 2006 with corrections to the Cover Date.     

EVKG: An interlinked and interoperable electric vehicle knowledge graph for smart transportation system

Over the past decade, the electric vehicle (EV) industry has experienced unprecedented growth and diversification, resulting in a complex ecosystem. To effectively manage this multifaceted field, we present an EV-centric knowledge graph (EVKG) as a comprehensive, cross-domain, extensible, and open geospatial knowledge management system. The EVKG encapsulates essential EV-related knowledge, including EV adoption, EV supply equipment, and electricity transmission network, to support decision-making related to EV technology development, infrastructure planning, and policy-making by providing timely and accurate information and analysis. To enrich and contextualize the EVKG, we integrate the developed EV-relevant ontology modules from existing well-known knowledge graphs and ontologies. This integration enables interoperability with other knowledge graphs in the Linked Data Open Cloud, enhancing the EVKG's value as a knowledge hub for EV decision-making. Using six competency questions, we demonstrate how the EVKG can be used to answer various types of EV-related questions, providing critical insights into the EV ecosystem. Our EVKG provides an efficient and effective approach for managing the complex and diverse EV industry. By consolidating critical EV-related knowledge into a single, easily accessible resource, the EVKG supports decision-makers in making informed choices about EV technology development, infrastructure planning, and policy-making. As a flexible and extensible platform, the EVKG is capable of accommodating a wide range of data sources, enabling it to evolve alongside the rapidly changing EV landscape.     

Accuracy assessment of digital elevation models by means of robust statistical methods

Measures for the accuracy assessment of Digital Elevation Models (DEMs) are discussed and characteristics of DEMs derived from laser scanning and automated photogrammetry are presented. Such DEMs are very dense and relatively accurate in open terrain. Built-up and wooded areas, however, need automated filtering and classification in order to generate terrain (bare earth) data when Digital Terrain Models (DTMs) have to be produced. Automated processing of the raw data is not always successful. Systematic errors and many outliers at both methods (laser scanning and digital photogrammetry) may therefore be present in the data sets. We discuss requirements for the reference data with respect to accuracy and propose robust statistical methods as accuracy measures. Their use is illustrated by application at four practical examples. It is concluded that measures such as median, normalized median absolute deviation, and sample quantiles should be used in the accuracy assessment of such DEMs. Furthermore, the question is discussed how large a sample size is needed in order to obtain sufficiently precise estimates of the new accuracy measures and relevant formulae are presented.     

Using DORIS measurements for modeling the vertical total electron content of the Earth’s ionosphere

The Doppler orbitography and radiopositioning integrated by satellite (DORIS) system was originally developed for precise orbit determination of low Earth orbiting (LEO) satellites. Beyond that, it is highly qualified for modeling the distribution of electrons within the Earth’s ionosphere. It measures with two frequencies in L-band with a relative frequency ratio close to 5. Since the terrestrial ground beacons are distributed quite homogeneously and several LEOs are equipped with modern receivers, a good applicability for global vertical total electron content (VTEC) modeling can be expected. This paper investigates the capability of DORIS dual-frequency phase observations for deriving VTEC and the contribution of these data to global VTEC modeling. The DORIS preprocessing is performed similar to commonly used global navigation satellite systems (GNSS) preprocessing. However, the absolute DORIS VTEC level is taken from global ionospheric maps (GIM) provided by the International GNSS Service (IGS) as the DORIS data contain no absolute information. DORIS-derived VTEC values show good consistency with IGS GIMs with a RMS between 2 and 3 total electron content units (TECU) depending on solar activity which can be reduced to less than 2 TECU when using only observations with elevation angles higher than \(50^\circ \) . The combination of DORIS VTEC with data from other space-geodetic measurement techniques improves the accuracy of global VTEC models significantly. If DORIS VTEC data is used to update IGS GIMs, an improvement of up to 12  % can be achieved. The accuracy directly beneath the DORIS satellites’ ground-tracks ranges between 1.5 and 3.5 TECU assuming a precision of 2.5 TECU for altimeter-derived VTEC values which have been used for validation purposes.     

Earth observations during space shuttle flight STS‐41: Discovery's mission to planet earth

Abstract

Multi‐temporal ERS‐1 SAR data acquired over a large agricultural region in West Bengal was used to classify kharif crops like rice, jute and sugarcane. Rice crop grown under lowland management practice showed a temporal characteristic. The dynamic range of backscatter was highest for this crop in temporal SAR data. This was used to classify rice using temporal SAR data. Such temporal character was not observed for the other study crops, which may be due to the difference in cultivation practice and crop calendar. Significant increase in backscatter from the ploughed fields was used to derive information on onset and duration of land preparations. Synergistic use of optical remote sensing data and SAR data increased the separability of rice crop from homesteads and permanent vegetation classes.