Data Of Different Origin Research Articles

Localized Smart Interpretation - a data driven semi-automatic geological modelling method

Localised Smart interpretation (LSI) is a method that infers a statistical model, which describes a relation between the knowledge of a geologist (as quantified by geological interpretation) and the available information (such as geophysical data, well log data, etc.) that a geologist uses when he/she interprets. This model is then used to perform semi-automatic geological interpretation wherever the same kinds of attributes, as used for the initial interpretation, are available. The statistical model is inferred using a combination of a regularized least squares method and cross validation. In this study, we demonstrate the applicability of the method to predict the depth to a low resistivity subsurface layer, based on interpretations from a geological expert, using a 19-layered resistivity model obtained from inversion of airborne electromagnetic (SkyTEM) data. This study shows that LSI is capable of making prediction with great accuracy. The method is fast and is able to handle large amounts of data of different origin, which suggest that the method may become a very useful approach to assist in geological modelling, based on increasingly large amounts of data of different nature.

Using surveillance and monitoring data of different origins in a Salmonella source attribution model: a European Union example with challenges and proposed solutions.

Microbial subtyping approaches are commonly used for source attribution of human salmonellosis. Such methods require data on Salmonella in animals and humans, outbreaks, infection abroad and amounts of food available for consumption. A source attribution model was applied to 24 European countries, requiring special data management to produce a standardized dataset. Salmonellosis data on animals and humans were obtained from datasets provided by the European Food Safety Authority. The amount of food available for consumption was calculated based on production and trade data. Limitations included different types of underreporting, non-participation in prevalence studies, and non-availability of trade data. Cases without travel information were assumed to be domestic; non-subtyped human or animal records were re-identified according to proportions observed in reference datasets; missing trade information was estimated based on previous years. The resulting dataset included data on 24 serovars in humans, broilers, laying hens, pigs and turkeys in 24 countries.

An open source package for the IBA data format IDF

Ion Beam Analysis (IBA) codes and laboratories implement various formats to store the spectral data and to describe the experimental conditions and simulation or fit parameters. These various data formats are isolated applications and generally incompatible – they are unable to “talk” to each other. The need for a universal IBA data format (IDF) has been recognised for many years to allow easy transfer of data and simulation parameters between codes, as well as between experimentalists and data analysts. A new standard data format, IDF, which is transparent, universal, and includes the most common features desired by both experimentalists who collect and archive data and by users who analyse the data was previously presented. However, its actual implementation has been left to each individual software developer, and the sheer size of the full IDF definition has prevented widespread implementation, with only a few codes using the IDF. Open source software was now developed to implement the IDF, and made available to the community in http://idf.schemas.itn.pt/ both as source code and as a DLL that every code and lab can use to, finally, make data of different origins “talk” to each other. We report the main features of the open source IDF package developed.

LONGWOOD - integrating woodland history and ecology in a geodatabase through an interdisciplinary approach.

Forests in Europe have been shaped considerably by human activities during most of the Holocene. Changes in forest structure, distribution of tree species and forest biodiversity are partly driven by management history, and many current forest types result from former management. The interdisciplinary project "Long-term woodland dynamics in Central Europe: from estimations to a realistic model" (LONGWOOD) aims to reconstruct long-term dynamics of woodland cover, structure and management in the eastern Czech Republic (Moravia, ca. 27,000 km2), compare the historical and present state of forests, and analyze general patterns of changes and stability of woodlands as well as the role of humans in these processes. In the LONGWOOD project, palaeoecological, archaeological, historical and ecological sources of information on woodland cover, species composition, and human activities (management, settlement density) over the past 7500 years are collected and integrated in the form of a geodatabase. Combining data of different origin, scale, degree of spatial precision and detail into a single geodatabase is a challenging task. The level of detail, information content, and spatio-temporal distribution of data varies between layers as well as individual records according to the nature of the data source and the data itself. The limited and incomplete sources of information until ca. 1100 AD provide a coarser view on forest history while the historical period (especially the past ca. 250 years) is covered by large amounts of precisely located ecological and historical data enabling detailed spatial and temporal analyses. Data on forest structure, history and management will be related to environmental factors (soil type, climate, elevation and other topographic variables derived from DEM) and social historical data (settlement distribution, population density, landuse). A spatio-temporal forest landscape model will be built to assess the forest changes and the main drivers of change.

The International Bathymetric Chart of the Southern Ocean (IBCSO) Version 1.0—A new bathymetric compilation covering circum‐Antarctic waters

AbstractThe International Bathymetric Chart of the Southern Ocean (IBCSO) Version 1.0 is a new digital bathymetric model (DBM) portraying the seafloor of the circum‐Antarctic waters south of 60°S. IBCSO is a regional mapping project of the General Bathymetric Chart of the Oceans (GEBCO). The IBCSO Version 1.0 DBM has been compiled from all available bathymetric data collectively gathered by more than 30 institutions from 15 countries. These data include multibeam and single‐beam echo soundings, digitized depths from nautical charts, regional bathymetric gridded compilations, and predicted bathymetry. Specific gridding techniques were applied to compile the DBM from the bathymetric data of different origin, spatial distribution, resolution, and quality. The IBCSO Version 1.0 DBM has a resolution of 500 × 500 m, based on a polar stereographic projection, and is publicly available together with a digital chart for printing from the project website (www.ibcso.org) and at http://dx.doi.org/10.1594/PANGAEA.805736.

Advances in remote sensing of hydraulic roughness

Riparian vegetation plays a crucial role in affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. Systematic detection, identification and assessment of flow resistance factors using conventional field sampling is often unfeasible as these techniques are time-consuming and expensive. As in many other environmental monitoring problems, remote sensing may provide unprecedented mapping capabilities. In this article we present an overview focusing on the different methods that can be used to remotely derive floodplain hydraulic roughness. The overview is based on an extensive literature review on recent estimation techniques of riparian roughness using remote sensing data from different platforms. The outlined methods of floodplain roughness parameterization include: (1) classification-derived hydraulic roughness maps and (2) estimation of vegetation hydrodynamic properties. Possible directions for a multiscale analysis of riparian flow resistance are also described in a short section by focusing on the potential of data assimilation methods for the estimation of floodplain roughness. The literature reveals that many valuable remote-sensing techniques have been developed for riparian corridor parameterization. Methodologies based on the fusion of multispectral/temporal imagery with data of different origin, such as light detection and ranging (LiDAR) and radar/microwave, appear to be powerful tools for characterizing riparian ecosystems for hydraulic purposes.

Deep Electromagnetic Studies from Land, Sea, and Space: Progress Status in the Past 10 Years

This review paper summarizes advances in deep electromagnetic studies of the Earth in the past decade. The paper reports progress in data interpretation, with special emphasis on three-dimensional and quasi one-dimensional developments, and results. The results obtained from data of different origin—geomagnetic observatories, long-period magnetotelluric experiments, submarines cables, and from low-Earth orbiting geomagnetic satellite missions—are described. Both frequency-domain and time-domain approaches are addressed. Perspectives for the future are also discussed.

Incipient crystallization of sparingly soluble salts on membrane surfaces: The case of dead-end filtration with no agitation

This paper aims at contributing to development of reliable criteria for determining the onset of scaling on desalination membranes. A novel approach is proposed to investigate incipient crystallization on membranes through modeling and RO filtration experiments. The evolution of membrane surface concentration of rejected ionic species (e.g. Ca 2+, CO 3 2−) is theoretically determined, and coupled with a detailed kinetic model for nucleation and growth of particles on the membrane. Model results contribute to our understanding of this problem and are in general accord with experimental data on membrane surface crystal density and mean size. Experimental data and model results show that incipient crystallization on RO membrane surfaces, when the bulk supersaturation ratio is maintained near its critical value (S ~ 1), is controlled by fluid permeation, and that the “induction time” may be insignificant under typical RO conditions. This work also suggests that the ability to determine the onset of crystallization on membranes is dependent on the combined sensitivity and adequate spatial resolution of the experimental technique employed, which explains the significant uncertainty associated with the reported in literature “induction period” data of different origin. Directions for future research are discussed.

The OPLS methodology for analysis of multi‐block batch process data

AbstractWith increasing availability of different process analysers multiple data sources are commonly available and this will impose new challenges and enable new types of investigations. The ability to separate joint, complementary and redundant information in multiple block data will be of increasing importance. In this study data from a batch mini plant were collected and O2PLS was implemented to facilitate a combined analysis of spectroscopic and process data. This enables assessment of both the joint and complementary variations in the respective data sets. The different types of variation that were separated were then modelled together to evaluate their individual correlation to a time response. By combining data of different origin an uncomplicated summary of the variation was accomplished and a deeper understanding of process interactions was gained. The analysis of separated variation with a response variable proved useful for verifying the supposed correlation between the joint variation and time. Copyright © 2007 John Wiley & Sons, Ltd.

A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling

During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise.In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical–empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections.The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave.

A contribution to data combination in ill-posed downward continuation problems

The spaceborne gravity field missions CHAMP, GRACE and GOCE, to be realized in the coming years, will improve our knowledge of the Earth's gravity field in the short, medium and long wavelength parts. Nevertheless, it is necessary to supplement this gravity field information with available terrestrial data. While the combination of data of different origin is comparably well-understood in well-posed problems there are some open questions in combining satellite derived and terrestrial data sets in the case of improperly posed problems. In this investigation, the future satellite missions are shortly characterized. The downward continuation process and its regularization based on Tikhonov's regularization method is reviewed. The test strategies to detect the contributions of satellite derived and terrestrial gravity field information applied in this investigation are summarized. A detailed simulation based on a GRACE-type SST mission scenario and additional terrestrial data with the task to derive parameters of a gravity field representation by local base functions is performed. The investigation tries to tackle a clarification of various questions related to the data combination by numerical tests.

Global modelling study (GSM TIP) of the ionospheric effects of excited <i>N<sub>2</sub></i>, convection and heat fluxes by comparison with EISCAT and satellite data for 31 July 1990

Abstract. Near-earth plasma parameters were calculated using a global numerical self-consistent and time-dependent model of the thermosphere, ionosphere and protonosphere (GSM TIP). The model results are compared with experimental data of different origin, mainly EISCAT measurements and simultaneous satellite data (Ne and ion composition). Model runs with varying inputs of auroral FAC distributions, temperature of vibrationally excited nitrogen and photoelectron energy escape fluxes are used to make adjustments to the observations. The satellite data are obtained onboard Active and its subsatellite Magion-2 when they passed nearby the EISCAT station around 0325 and 1540 UT on 31 July 1990 at a height of about 2000 and 2200 km, respectively. A strong geomagnetic disturbance was observed two days before the period under study. Numerical calculations were performed with consideration of vibrationally excited nitrogen molecules for high solar-activity conditions. The results show good agreement between the incoherent-scatter radar measurements (Ne, Te, Ti) and model calculations, taking into account the excited molecular nitrogen reaction rates. The comparison of model results of the thermospheric neutral wind shows finally a good agreement with the HWM93 empirical wind model.

Simultaneous decomposition of several spectra into the constituent Gaussian peaks

A computer program is proposed for the decomposition of spectra into their constituent Gaussian peaks. A new feature of this program is the possibility of operating on different spectra from two or more components of variable concentration at the same time, by optimising the wavelengths of the maxima and the halfbandwidths of all the spectra while the height of each peak is optimized in each single spectrum. This distinct treatment is possible due to the fact that the Gaussian functions are linear with respect to the heights and non-linear with respect to the remaining parameters. A linear and non-linear least-squares analysis, respectively, is therefore possible. Besides its intrinsic utility in handling spectral data of different origin this procedure proves more useful than the single spectrum decomposition both in increasing the reliability of the parameters and in improving the convergence properties of the procedure.

Future coal supply for the world energy balance. Third IIASA Conference on Energy Resources, 1977

During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise.In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical–empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections.The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave.

Geodetic constants and the motion of the Moon

The author discusses the set of constants required to describe the external gravitational field of the Earth : a set of form factors and two scale factors. Some problems in relating the external field as derived from the motions of satellites to the quantities observed at the surface are mentioned. The fondamental parameters cannot be derived from the data without a knowledge of other astronomical constants, and it is shown how a general adjustment of data of different origins can be made. The results enable suggestions to be made about the way in which new conventional values of these parameters should be chosen.