Proglacial river dataset from the Akuliarusiarsuup Kuua River northern tributary, Southwest Greenland, 2008 - 2010, version 1.0

Pressing scientific questions concerning the Greenland ice sheet's climatic sensitivity, hydrology, and contributions to current and future sea level rise require hydrological datasets to resolve. While direct observations of ice sheet meltwater losses can be obtained in terrestrial rivers draining the ice sheet and from lake levels, few such datasets exist. We present a new dataset of meltwater river discharge for the vicinity of Kangerlussuaq, Southwest Greenland. The dataset contains measurements of river stage and discharge for three sites along the Akuliarusiarsuup Kuua (Watson) River's northern tributary, with 30 minute temporal resolution between June 2008 and August 2010. Additional data of water temperature, air pressure, and lake water depth and temperature are also provided. Discharge data were measured at sites with near-ideal properties for such data collection. Regardless, high water bedload and turbulent flow introduce considerable uncertainty. These were constrained and quantified using statistical techniques, thereby providing a high quality dataset from this important site. The greatest data uncertainties are associated with streambed elevation change and measurements. Large portions of stream channels deepened according to statistical tests, but poor precision of streambed depth measurements also added uncertainty. Quality checked data are freely available for scientific use as supplementary online material.

Synthesis dataset of physical and ecosystem properties from pan-arctic wetland sites using peat core analysis

Permafrost dynamics play an important role in high-latitude peatland carbon balance and are key to understanding the future response of soil carbon stocks. Permafrost aggradation can control the magnitude of the carbon feedback in peatlands through effects on peat properties. We compiled peatland plant macrofossil records for the northern permafrost zone (515 cores from 280 sites) and classified samples by vegetation type and environmental class (fen, bog, tundra and boreal permafrost, thawed permafrost). We examined differences in peat properties (bulk density, carbon (C), nitrogen (N) and organic matter content, C/N ratio) and C accumulation rates among vegetation types and environmental classes.

A new indexing method for high dimensional dataset

Indexing high dimensional datasets has attracted extensive attention from many researchers in the last decade. Since R-tree type of index structures are known as suffering curse of dimensionality problems, Pyramid-tree type of index structures, which are based on the B-tree, have been proposed to break the curse of dimensionality. However, for high dimensional data, the number of pyramids is often insufficient to discriminate data points when the number of dimensions is high. Its effectiveness degrades dramatically with the increase of dimensionality. In this paper, we focus on one particular issue of curse of dimensionality; that is, the surface of a hypercube in a high dimensional space approaches 100% of the total hypercube volume when the number of dimensions approaches infinite. We propose a new indexing method based on the surface of dimensionality. We prove that the Pyramid tree technology is a special case of our method. The results of our experiments demonstrate clear priority of our novel method.

Benchmarking the n-tuple classifier with statlog dataset

The n-tuple recognition method was tested on 11 large real-world data sets and its performance compared to 23 other classification algorithms. On 7 of these, the results show no systematic performance gap between the n-tuple method and the others. Evidence was found to support a possible explanation for why the n-tuple method yields poor results for certain datasets. Preliminary empirical results of a study of the confidence interval (the difference between the two highest scores) are also reported. These suggest a counter-intuitive correlation between the confidence interval distribution and the overall classification performance of the system.

Absorptive capacity and the benefits from global reservoirs of knowledge:evidence from a linked China-OECD dataset

This paper investigates the role of absorptive capacity in the diffusion of global technology with sector and firm heterogeneity. We construct the FDI-intensity weighted global R&D stock for each industry and link it to Chinese firm-level panel data relating to 53,981 firms over the period 2001-2005. Non-parametric frontier analysis is employed to explore how absorptive capacity affects technical change and catch-up in the presence of global knowledge spillovers. We find that R&D activities and training at individual firms serve as an effective source of absorptive capability. The contribution of absorptive capacity varies according to the type of FDI and the extent of openness.

Cost economies, efficiency and productivity growth in the Chinese banking industry:evidence from a quarterly panel dataset

This article examines cost economies, productivity growth and cost efficiency of the Chinese banks using a unique panel dataset that identifies banks' four outputs and four input prices over the period of 1995-2001. By assessing the appropriateness of model specification, and making use of alternative methodologies in evaluating the performance of banks, we find that the joint-stock commercial banks outperform state-owned commercial banks in productivity growth and cost efficiency. Under the variable cost assumption, Chinese banks display economies of scale, with state-owned commercial banks enjoying cost advantages over the joint-stock commercial banks. Consequently, our results highlight the ownership advantage of these two types of banks and generally support the ongoing banking reform and transformation that is currently taking place in China.

Visualisation of quality information for geospatial and remote sensing data:providing the GIS community with the decision support tools for geospatial dataset quality evaluation

The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. The research presented here therefore focused on defining and developing a GEO label – a decision support mechanism to assist data users in efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for use. This thesis thus presents six phases of research and development conducted to: (a) identify the informational aspects upon which users rely when assessing geospatial dataset quality and trustworthiness; (2) elicit initial user views on the GEO label role in supporting dataset comparison and selection; (3) evaluate prototype label visualisations; (4) develop a Web service to support GEO label generation; (5) develop a prototype GEO label-based dataset discovery and intercomparison decision support tool; and (6) evaluate the prototype tool in a controlled human-subject study. The results of the studies revealed, and subsequently confirmed, eight geospatial data informational aspects that were considered important by users when evaluating geospatial dataset quality and trustworthiness, namely: producer information, producer comments, lineage information, compliance with standards, quantitative quality information, user feedback, expert reviews, and citations information. Following an iterative user-centred design (UCD) approach, it was established that the GEO label should visually summarise availability and allow interrogation of these key informational aspects. A Web service was developed to support generation of dynamic GEO label representations and integrated into a number of real-world GIS applications. The service was also utilised in the development of the GEO LINC tool – a GEO label-based dataset discovery and intercomparison decision support tool. The results of the final evaluation study indicated that (a) the GEO label effectively communicates the availability of dataset quality and trustworthiness information and (b) GEO LINC successfully facilitates ‘at a glance’ dataset intercomparison and fitness for purpose-based dataset selection.

Circumarctic wetland dataset based on ENVISAT ASAR Global Monitoring Mode with links to geotiff image and NetCDF files (2005-01 to 2011-12)

A circumpolar representative and consistent wetland map is required for a range of applications ranging from upscaling of carbon fluxes and pools to climate modelling and wildlife habitat assessment. Currently available data sets lack sufficient accuracy and/or thematic detail in many regions of the Arctic. Synthetic aperture radar (SAR) data from satellites have already been shown to be suitable for wetland mapping. Envisat Advanced SAR (ASAR) provides global medium-resolution data which are examined with particular focus on spatial wetness patterns in this study. It was found that winter minimum backscatter values as well as their differences to summer minimum values reflect vegetation physiognomy units of certain wetness regimes. Low winter backscatter values are mostly found in areas vegetated by plant communities typically for wet regions in the tundra biome, due to low roughness and low volume scattering caused by the predominant vegetation. Summer to winter difference backscatter values, which in contrast to the winter values depend almost solely on soil moisture content, show expected higher values for wet regions. While the approach using difference values would seem more reasonable in order to delineate wetness patterns considering its direct link to soil moisture, it was found that a classification of winter minimum backscatter values is more applicable in tundra regions due to its better separability into wetness classes. Previous approaches for wetland detection have investigated the impact of liquid water in the soil on backscatter conditions. In this study the absence of liquid water is utilized. Owing to a lack of comparable regional to circumpolar data with respect to thematic detail, a potential wetland map cannot directly be validated; however, one might claim the validity of such a product by comparison with vegetation maps, which hold some information on the wetness status of certain classes. It was shown that the Envisat ASAR-derived classes are related to wetland classes of conventional vegetation maps, indicating its applicability; 30% of the land area north of the treeline was identified as wetland while conventional maps recorded 1-7%.

Magnetic susceptibility dataset from the Danian Contessa Highway section, Gubbio, Italy

We studied a high-resolution multiproxy data set, including magnetic susceptibility (MS), CaCO3 content, and stable isotopes (d18O and d13C), from the stratigraphic interval covering the uppermost Maastrichtian and the lower Danian, represented by the pelagic limestones of the Scaglia Rossa Formation continuously exposed in the classic sections of the Bottaccione Gorge and the Contessa Highway near Gubbio, Italy. Variations in all the proxy series are periodic and reflect astronomically forced climate changes (i.e., Milankovitch cycles). In particular, the MS proxy reflects variations in the terrigenous dust input in this pelagic, deep-marine environment. We speculate that the dust is mainly eolian in origin and that the availability and transport of dust are influenced by variations in the vegetation cover on the Maastrichtian-Paleocene African or Asian zone, which were respectively located at tropical to subtropical latitudes to the south or far to the east of the western Tethyan Umbria-Marche Basin, and were characterized by monsoonal circulation. The dynamics of monsoonal circulation are known to be strongly dependent on precession-driven and obliquity-driven changes in insolation. We propose that a threshold mechanism in the vegetation coverage may explain eccentricity-related periodicities in the terrigenous eolian dust input. Other mechanisms, both oceanic and terrestrial, that depend on the precession amplitude modulated by eccentricity, can be evoked together with the variation of dust influx in the western Tethys to explain the detected eccentricity periodicity in the d13C record. Our interpretations of the d18O and MS records suggest a warming event ~400 k.y. prior to the Cretaceous-Paleogene (K-Pg) boundary, and a period of climatic and environmental instability in the earliest Danian. Based on these multiproxy phase relationships, we propose an astronomical tuning for these sections; this leads us to an estimate of the timing and duration of several late Maastrichtian and Danian biostratigraphic and magnetostratigraphic events.

Circumpolar dataset of Soil Organic Carbon north of treeline derived from ENVISAT ASAR GM, link to GeoTIFF

A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ~120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.

ROCADA: Romanian daily gridded climatic dataset (1961-2013) V1.0

Daily records of nine meteorological variables covering the interval 1961-2013 were used in order to create a state-of-the-art homogenized climatic dataset over Romania at a spatial resolution of 0.1°. All meteorological stations with full data records, as well as stations with up to 30 % missing data, were used for the following variables: air pressure (150 stations); minimum, maximum, and average air temperature (150 stations); soil temperature (127 stations); precipitation (188 stations); sunshine hours (135 stations); cloud cover (104 stations); relative humidity (150 stations). For each parameter, the data series were first homogenized with the software MASH (Multiple Analysis of Series for Homogenization); then, the data series were gridded by means of the software MISH (Meteorological Interpolation based on Surface Homogenized Data).

Mesoscale ocean eddy dataset in the Lofoten Basin from Satellite Altimetry

The Lofoten Basin is the most eddy rich region in the Norwegian Sea. In this paper, the characteristics of these eddies are investigated from a comprehensive database of nearly two decades of satellite altimeter data (1995-2013) together with Argo profiling floats and surface drifter data. An automated method identified 1695/1666 individual anticyclonic/cyclonic eddies in the Lofoten Basin from more than 10,000 altimeter-based eddy observations. The eddies are found to be predominantly generated and residing locally. The spatial distributions of lifetime, occurrence, generation sites, size, intensity, and drift of the eddies are studied in detail. The anticyclonic eddies in the Lofoten Basin are the most long-lived eddies (>60 days), especially in the western part of the basin. We reveal two hotspots of eddy occurrence on either side of the Lofoten Basin. Furthermore, we infer a cyclonic drift of eddies in the western Lofoten Basin. Barotropic energy conversion rates reveals energy transfer from the slope current to the eddies during winter. An automated colocation of surface drifters trapped inside the altimeter-based eddies are used to corroborate the orbital speed of the anticyclonic and cyclonic eddies. Moreover, the vertical structure of the altimeter-based eddies is examined using colocated Argo profiling float profiles. Combination of altimetry, Argo floats, and surface drifter data is therefore considered to be a promising observation-based approach for further studies of the role of eddies in transport of heat and biomass from the slope current to the Lofoten Basin.

Boys2Men, an age estimation dataset with applications to detect enfants in pornography content

[EN]The aim of this paper is the detection of non adults in images.