Vertical crustal motion along the Mediterranean and Black Sea coast derived from ocean altimetry and tide gauge data

Tide gauge (TG) data along the northern Mediterranean and Black Sea coasts are compared to the sea-surface height (SSH) anomaly obtained from ocean altimetry (TOPEX/Poseidon and ERS-1/2) for a period of nine years (1993–2001). The TG measures the SSH relative to the ground whereas the altimetry does so with respect to the geocentric reference frame; therefore their difference would be in principle a vertical ground motion of the TG sites, though there are different error sources for this estimate as is discussed in the paper. In this study we estimate such vertical ground motion, for each TG site, from the slope of the SSH time series of the (non-seasonal) difference between the TG record and the altimetry measurement at a point closest to the TG. Where possible, these estimates are further compared with those derived from nearby continuous Global Positioning System (GPS) data series. These results on vertical ground motion along the Mediterranean and Black Sea coasts provide useful source data for studying, contrasting, and constraining tectonic models of the region. For example, in the eastern coast of the Adriatic Sea and in the western coast of Greece, a general subsidence is observed which may be related to the Adriatic lithosphere subducting beneath the Eurasian plate along the Dinarides fault.

A data driven study of relationships between relief and farmland abandonment in a Mediterranean region

The environmental, cultural and socio-economic causes and consequences of farmland abandonment are issues of increasing concern for researchers and policy makers. In previous studies, we proposed a new methodology for selecting the driving factors in farmland abandonment processes. Using Data Mining and GIS, it is possible to select those variables which are more significantly related to abandonment. The aim of this study is to investigate the application of the above mentioned methodology for finding relationships between relief and farmland abandonment in a Mediterranean region (SE Spain).We have taken into account up to 28 different variables in a single analysis, some of them commonly considered in land use change studies (slope, altitude, TWI, etc), but also other novel variables have been evaluated (sky view factor, terrain view factor, etc). The variable selection process provides results in line with the previous knowledge of the study area, describing some processes that are region specific (e.g. abandonment versus intensification of the agricultural activities). The European INSPIRE Directive (2007/2/EC) establishes that the digital elevation models for land surfaces should be available in all member countries, this means that the research described in this work can be extrapolated to any European country to determine whether these variables (slope, altitude, etc) are important in the process of abandonment.

Advances in camera trap data management tools: Towards collaborative development and integration with GIS

Camera traps have become a widely used technique for conducting biological inventories, generating a large number of database records of great interest. The main aim of this paper is to describe a new free and open source software (FOSS), developed to facilitate the management of camera-trapped data which originated from a protected Mediterranean area (SE Spain). In the last decade, some other useful alternatives have been proposed, but ours focuses especially on a collaborative undertaking and on the importance of spatial information underpinning common camera trap studies. This FOSS application, namely, “Camera Trap Manager” (CTM), has been designed to expedite the processing of pictures on the .NET platform. CTM has a very intuitive user interface, automatic extraction of some image metadata (date, time, moon phase, location, temperature, atmospheric pressure, among others), analytical (Geographical Information Systems, statistics, charts, among others), and reporting capabilities (ESRI Shapefiles, Microsoft Excel Spreadsheets, PDF reports, among others). Using this application, we have achieved a very simple management, fast analysis, and a significant reduction of costs. While we were able to classify an average of 55 pictures per hour manually, CTM has made it possible to process over 1000 photographs per hour, consequently retrieving a greater amount of data.

Organizing and Interpreting Unstructured Qualitative Data

In the last several years there has been an increase in the amount of qualitative research using in-depth interviews and comprehensive content analyses in sport psychology. However, no explicit method has been provided to deal with the large amount of unstructured data. This article provides common guidelines for organizing and interpreting unstructured data. Two main operations are suggested and discussed: first, coding meaningful text segments, or creating tags, and second, regrouping similar text segments,or creating categories. Furthermore, software programs for the microcomputer are presented as away to facilitate the organization and interpretation of qualitative data

Mass Surveillance of Personal Data by EU Member States and its Compatibility with EU Law. CEPS Liberty and Security in Europe No. 61, 6 November 2013

In the wake of the disclosures surrounding PRISM and other US surveillance programmes, this paper assesses the large-scale surveillance practices by a selection of EU member states: the UK, Sweden, France, Germany and the Netherlands. Given the large-scale nature of these practices, which represent a reconfiguration of traditional intelligence gathering, the paper contends that an analysis of European surveillance programmes cannot be reduced to a question of the balance between data protection versus national security, but has to be framed in terms of collective freedoms and democracy. It finds that four of the five EU member states selected for in-depth examination are engaging in some form of large-scale interception and surveillance of communication data, and identifies parallels and discrepancies between these programmes and the NSA-run operations. The paper argues that these programmes do not stand outside the realm of EU intervention but can be analysed from an EU law perspective via i) an understanding of national security in a democratic rule of law framework where fundamental human rights and judicial oversight constitute key norms; ii) the risks posed to the internal security of the Union as a whole as well as the privacy of EU citizens as data owners and iii) the potential spillover into the activities and responsibilities of EU agencies. The paper then presents a set of policy recommendations to the European Parliament.

Migration and Asylum Data for Policy-making in the European Union – The problem with numbers. CEPS Liberty and Security in Europe No. 89/March 2016

Among many other problems, the migration, humanitarian and policy crises in the European Union in 2015 and early 2016 have highlighted a pressing need for reliable, timely and comparable statistical data on migration, asylum and arrivals at national borders. In this fast-moving policy field, data production and the timeliness of dissemination have seen some improvements but the sources of data remain largely unchanged at national level. In this paper the author examines the reasons for some of the problems with the data for policy and for public discussion, and makes a set of recommendations that call for a complete and updated inventory of data sources and for an evaluation of the quality of data used for policy-making.

Navigation and meteorological data during campaign TARA_20090926Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20091019Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Transportation statistical data and information. Final report.

Transportation Department, Office of Transportation Systems Analysis and Information, Washington, D.C.

Eddy covariance and environmental data of boreal bogs plant species

In boreal bogs plant species are low in number, but they differ greatly in their growth forms and photosynthetic properties. We assessed how ecosystem carbon (C) sink dynamics were affected by seasonal variations in photosynthetic rate and leaf area of different species. Photosynthetic properties (light-response parameters), leaf area development and areal cover (abundance) of the species were used to quantify species-specific net and gross photosynthesis rates (PN and PG, respectively), which were summed to express ecosystem-level PN and PG. The ecosystem-level PG was compared with a gross primary production (GPP) estimate derived from eddy covariance measurements (EC). Species areal cover rather than differences in photosynthetic properties determined the species with the highest PG of both vascular plants and Sphagna. Species-specific contributions to the ecosystem PG varied over the growing season, which in turn determined the seasonal variation in ecosystem PG. The upscaled growing-season PG estimate, 230 g C/m**2, agreed well with the GPP estimated by the EC, 243 g C/m**2. Sphagna were superior to vascular plants in ecosystem-level PG throughout the growing season but had a lower PN. PN results indicated that areal cover of the species together with their differences in photosynthetic parameters shape the ecosystem-level C balance. Species with low areal cover but high photosynthetic efficiency appear to be potentially important for the ecosystem C sink. Results imply that functional diversity may increase the stability of C sink of boreal bogs.

Submodular Optimization and Data Processing

Thesis (Ph.D.)--University of Washington, 2016-06

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Combining data driven programming with component based software development:with applications in geovisualisation and dynamic data driven application systems

Software development methodologies are becoming increasingly abstract, progressing from low level assembly and implementation languages such as C and Ada, to component based approaches that can be used to assemble applications using technologies such as JavaBeans and the .NET framework. Meanwhile, model driven approaches emphasise the role of higher level models and notations, and embody a process of automatically deriving lower level representations and concrete software implementations. The relationship between data and software is also evolving. Modern data formats are becoming increasingly standardised, open and empowered in order to support a growing need to share data in both academia and industry. Many contemporary data formats, most notably those based on XML, are self-describing, able to specify valid data structure and content, and can also describe data manipulations and transformations. Furthermore, while applications of the past have made extensive use of data, the runtime behaviour of future applications may be driven by data, as demonstrated by the field of dynamic data driven application systems. The combination of empowered data formats and high level software development methodologies forms the basis of modern game development technologies, which drive software capabilities and runtime behaviour using empowered data formats describing game content. While low level libraries provide optimised runtime execution, content data is used to drive a wide variety of interactive and immersive experiences. This thesis describes the Fluid project, which combines component based software development and game development technologies in order to define novel component technologies for the description of data driven component based applications. The thesis makes explicit contributions to the fields of component based software development and visualisation of spatiotemporal scenes, and also describes potential implications for game development technologies. The thesis also proposes a number of developments in dynamic data driven application systems in order to further empower the role of data in this field.

Technological diversification and new innovators in European regions:evidence from patent data

This paper assesses the impact of regional technological diversification on the emergence of new innovators across EU regions. Integrating analyses from regional economics, economic geography and technological change literatures, we explore the role that the regional embeddedness of actors characterised by diverse technological competencies may have in fostering novel and sustained interactions leading to new technological combinations. In particular, we test whether greater technological diversification improve regional ‘combinatorial’ opportunities leading to the emergence of new innovators. The analysis is based on panel data obtained merging regional economic data from Eurostat and patent data from the CRIOS-PATSTAT database over the period 1997–2006, covering 178 regions across 10 EU Countries. Accounting for different measures of economic and innovative activity at the NUTS2 level, our findings suggest that the regional co-location of diverse technological competencies contributes to the entry of new innovators, thereby shaping technological change and industry dynamics. Thus, this paper brings to the fore a better understanding of the relationship between regional diversity and technological change.