Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

Size-partitioned phytoplankton carbon concentrations retrieved from ocean color data, links to data in netCDF format

Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield - 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

Biogeochemical data from terrestrial and aquatic ecosystems in a periglacial catchment, West Greenland

Global warming is expected to be most pronounced in the Arctic where permafrost thaw and release of old carbon may provide an important feedback mechanism to the climate system. To better understand and predict climate effects and feedbacks on the cycling of elements within and between ecosystems in northern latitude landscapes, a thorough understanding of the processes related to transport and cycling of elements is required. A fundamental requirement to reach a better process understanding is to have access to high-quality empirical data on chemical concentrations and biotic properties for a wide range of ecosystem domains and functional units (abiotic and biotic pools). The aim of this study is therefore to make one of the most extensive field data sets from a periglacial catchment readily available that can be used both to describe present-day periglacial processes and to improve predictions of the future. Here we present the sampling and analytical methods, field and laboratory equipment and the resulting biogeochemical data from a state-of-the-art whole-ecosystem investigation of the terrestrial and aquatic parts of a lake catchment in the Kangerlussuaq region, West Greenland. This data set allows for the calculation of whole-ecosystem mass balance budgets for a long list of elements, including carbon, nutrients and major and trace metals.

Inventory of SINOPS project data sets

During the SINOPS project, an optimal state of the art simulation of the marine silicon cycle is attempted employing a biogeochemical ocean general circulation model (BOGCM) through three particular time steps relevant for global (paleo-) climate. In order to tune the model optimally, results of the simulations are compared to a comprehensive data set of 'real' observations. SINOPS' scientific data management ensures that data structure becomes homogeneous throughout the project. Practical work routine comprises systematic progress from data acquisition, through preparation, processing, quality check and archiving, up to the presentation of data to the scientific community. Meta-information and analytical data are mapped by an n-dimensional catalogue in order to itemize the analytical value and to serve as an unambiguous identifier. In practice, data management is carried out by means of the online-accessible information system PANGAEA, which offers a tool set comprising a data warehouse, Graphical Information System (GIS), 2-D plot, cross-section plot, etc. and whose multidimensional data model promotes scientific data mining. Besides scientific and technical aspects, this alliance between scientific project team and data management crew serves to integrate the participants and allows them to gain mutual respect and appreciation.

Building Information Modelling in UK Construction Projects: A State of the Art Review

This paper aims to present a state-of-the-art review of the scope and practical implications of the Building Information Modelling (BIM) platform in the UK construction practice. Theoretical developments suggest that BIM is an integration of both product and process innovation, not just a disparate set of software tools. BIM provides effective collaboration, visual representation and data management, which enable the smooth flow of information throughout the project’s lifecycle. The most frequently reported benefits are related to Capital Cost (capex) and Operational costs (opex) and time savings. Key challenges, however, focus on the interoperability of software, capital installation costs, in-house experience, client preference and cultural issues within design teams and within the organisation. The paper concludes with a critical commentary on the changing roles and a process required to implement BIM in UK construction projects, and suggests areas for further research.

CODEX: mapping co-created data for speculative geographies

This paper discusses a series of artworks named CODEX produced by the authors as part of a collaborative research project between the Centre for Research in Education, Art and Media (CREAM), University of Westminster, and the Oxford Internet Institute. Taking the form of experimental maps, large-scale installations and prints, we show how big data can be employed to reflect upon social phenomena through the formulation of critical, aesthetic and speculative geographies.

Dislocated Data Palm (in Two Parts)

Portikus presents the work of late British conceptual artist John Latham (1921-2006) and a new work by artist and researcher Neal White. By facilitating a dialogue between these two practices, the show decodes Latham’s expansive and hugely complex oeuvre and the conceptual legacy of art in relation to the ‘event’ as a structural entity.

Sweat Lodges in Iron Age Iberian Peninsula: New Data, Typologies and Interpretations

Three questions on the study of NO Iberian Peninsula sweat lodges are posed. First, the new sauna of Monte Ornedo (Cantabria), the review of the one of Armea (Ourense), and the Cantabrian pedra formosa type are discussed. Second, the known types of sweat lodges are reconsidered underlining the differences between the Cantabrian and the Douro - Minho groups as these differences contribute to a better assessment of the saunas located out of those territories, such as those of Monte Ornedo or Ulaca. Third, a richer record demands a more specific terminology, a larger use of archaeometric analysis and the application of landscape archaeology or art history methodologies. In this way the range of interpretation of the sweat lodges is opened, as an example an essay is proposed that digs on some already known proposals and suggests that the saunas are material metaphors of wombs whose rationale derives from ideologies and ritual practices of Indo-European tradition.

A state-of-the-art review and feasibility analysis of high altitude wind power in Northern Ireland

In many countries wind energy has become an indispensable part of the electricity generation mix. The opportunity for ground based wind turbine systems are becoming more and more constrained due to limitations on turbine hub heights, blade lengths and location restrictions linked to environmental and permitting issues including special areas of conservation and social acceptance due to the visual and noise impacts. In the last decade there have been numerous proposals to harness high altitude winds, such as tethered kites, airfoils and dirigible based rotors. These technologies are designed to operate above the neutral atmospheric boundary layer of 1,300 m, which are subject to more powerful and persistent winds thus generating much higher electricity capacities. This paper presents an in-depth review of the state-of-the-art of high altitude wind power, evaluates the technical and economic viability of deploying high altitude wind power as a resource in Northern Ireland and identifies the optimal locations through considering wind data and geographical constraints. The key findings show that the total viable area over Northern Ireland for high altitude wind harnessing devices is 5109.6 km2, with an average wind power density of 1,998 W/m2 over a 20-year span, at a fixed altitude of 3,000 m. An initial budget for a 2MW pumping kite device indicated a total cost £1,751,402 thus proving to be economically viable with other conventional wind-harnessing devices.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.

Investigating the AGN-starburst connection in a nearby Seyfert galaxy with ALMA and multiwavelength data

The astrophysical context in which this thesis project lies concerns the comprehension of the mutual interaction between the accretion onto a Super Massive Black Hole (SMBH) and the Star Formation (SF), that take place in the host galaxy. This is one of the key topic of the modern extragalactic astrophysical research. Indeed, it is widely accepted that to understand the physics of a galaxy, the contribution of a possible central AGN must be taken into account. The aim of this thesis is the study of the physical processes of the nearby Seyfert galaxy NGC 34. This source was selected because of the wide collection of multiwavelength data available in the literature. In addition, recently, it has been observed with the Atacama Large Submillimeter/Millimeter Array (ALMA) in Band 9. This project is divided in two main parts: first of all, we reduced and analyzed the ALMA data, obtaining the continuum and CO(6-5) maps; then, we looked for a coherent explaination of NGC 34 physical characteristics. In particular, we focused on the ISM physics, in order to understand its properties in terms of density, chemical composition and dominant radiation field (SF or accretion). This work has been done through the analysis of the spectral distribution of several CO transitions as a function of the transition number (CO SLED), obtained joining the CO(6-5) line with other transitions available in the literature. More precisely, the observed CO SLED has been compared with ISM models, including Photo-Dissociation Regions (PDRs) and X-ray-Dominated Regions (XDRs). These models have been obtained through the state-of-the-art photoionization code CLOUDY. Along with the observed CO SLED, we have taken into account other physical properties of NGC 34, such as the Star Formation Rate (SFR), the gas mass and the X-ray luminosity.

The art of building trust via e-communication channels: Post-acquisition integration as a special context

This study discusses the importance of establishing trust in post-acquisition integration context and how the use of e-channels facilitates or inhibits this process. The objective of this study is to analyze how the use of electronic communication channels influences the post-acquisition integration process in terms of trust establishment and overall integration efficiency, developing a framework as a result. Three sub-objectives are introduced: to find out the building blocks of trust in M&A’s, to analyse how the use of e-channels influence the process of trust establishment in post-acquisition integration context, and to define the consequences trust and use of e-channels have for the process. The theoretical background of the study includes literature and theories relating to trust establishment in post-acquisition integration context and how the use of e-channels influences the process of trust development on a general level. The empirical research is conducted as a single case study, based on key informant interviews. The interview data was collected between October 2015 and January 2016. Altogether nine interviews were realised; six with representatives from the acquiring firm and three with target firm members. Thematic analysis was selected as the main method for analysing and processing the qualitative data. This study finds that trust has an essential role in post-acquisition integration context, facilitating the integration process in various different ways. Hence, identifying the different building blocks of trust is important in order for members of the organisations to be better able establish and maintain trust. In today’s international business, the role of electronic communication channels has also increased in importance significantly and it was confirmed that these pose both challenges and possibilities for the development of interpersonal trust. One of the most important underlying factors influencing the trust levels via e-communication channels is the level of user’s comfort in using the different e-channels. Without sufficient and meaningful training, the communication conducted via these channels in inhibited in a number of ways. Hence, understanding the defining characteristics of e-communication together with the risks and opportunities related to the use of these can have far-reaching consequences for the post-acquisition integration process as a whole. The framework based on the findings and existing theory introduces the most central factors influencing the trust establishment together with the positive and negative consequences these have for the integration process. Moreover, organizational level consistency and the existence of shared guidelines on appropriate selection of communication channels according to the nature of the task at hand are seen as important

Two years survival rate of Class II ART restorations in primary molars using two ways to avoid saliva contamination

AIM To compare the survival rates of Class II Atraumatic Restorative Treatment (ART) restorations placed in primary molars using cotton rolls or rubber dam as isolation methods. METHODS A total of 232 children, 6-7 years old, both genders, were selected having one primary molar with proximal dentine lesion. The children were randomly assigned into two groups: control group with Class II ART restoration made using cotton rolls and experimental group using rubber dam. The restorations were evaluated by eight calibrated evaluators (Kappa > 0.8) after 6, 12, 18 and 24 months. RESULTS A total of 48 (20.7%) children were considered dropout, after 24 months. The cumulative survival rate after 6, 12, 18 and 24 months was 61.4%, 39.0%, 29.1% and 18.0%, respectively for the control group, and 64.1%, 55.1%, 40.1% and 32.1%, respectively for the rubber dam group. The log rank test for censored data showed no statistical significant difference between the groups (P = 0.07). The univariate Cox Regression showed no statistical significant difference after adjusting for independent variables (P > 0.05). CONCLUSION Both groups had similar survival rates, and after 2 years, the use of rubber dam does not increase the success of Class II ART restorations significantly.

An Exploration of the Data Collection Methods Utilised with Children, Teenagers and Young People (CTYPs)

Background: The impact of cancer upon children, teenagers and young people can be profound. Research has been undertaken to explore the impacts upon children, teenagers and young people with cancer, but little is known about how researchers can ‘best’ engage with this group to explore their experiences. This review paper provides an overview of the utility of data collection methods employed when undertaking research with children, teenagers and young people. A systematic review of relevant databases was undertaken utilising the search terms ‘young people’, ‘young adult’, ‘adolescent’ and ‘data collection methods’. The full-text of the papers that were deemed eligible from the title and abstract were accessed and following discussion within the research team, thirty papers were included. Findings: Due to the heterogeneity in terms of the scope of the papers identified the following data collections methods were included in the results section. Three of the papers identified provided an overview of data collection methods utilised with this population and the remaining twenty seven papers covered the following data collection methods: Digital technologies; art based research; comparing the use of ‘paper and pencil’ research with web-based technologies, the use of games; the use of a specific communication tool; questionnaires and interviews; focus groups and telephone interviews/questionnaires. The strengths and limitations of the range of data collection methods included are discussed drawing upon such issues as of the appropriateness of particular methods for particular age groups, or the most appropriate method to employ when exploring a particularly sensitive topic area. Conclusions: There are a number of data collection methods utilised to undertaken research with children, teenagers and young adults. This review provides a summary of the current available evidence and an overview of the strengths and limitations of data collection methods employed.

Health and mood among HIV‐positive outpatients attending an ART Clinic of a University Hospital

To evaluate how individuals at different stages of infection with HIV perceive their health status and its association with mood states. With the introduction of Highly Active Antiretroviral Therapy in 1996, the quality of life of people living with HIV has improved. However, the literature emphasises the negative effects of the disease on the mental health of individuals suffering from this condition and the high incidence of depression among infected individuals. Although people diagnosed and living with HIV are overwhelmed by emotions, we found that various emotional manifestations are understudied within this group of patients. A cross-sectional study was conducted in an outpatient unit of a University Hospital (antiretroviral therapy clinic), with a consecutive sample composed of 152 patients. Data were collected through a questionnaire used to assess the sociodemographic and clinical characteristics, the Short Form (36) Health Survey, and the Profile of Mood States scale. The health status negatively affects the role at the emotional and mental health dimensions. The participants showing a worse health condition than in the previous year had higher levels of tension/anxiety, depression/dejection, fatigue/inertia and confusion/bewilderment. The stage of disease and the profile of mood state emerged as independent phenomena. The results of this study indicate that nurses worldwide should be aware of the emotional aspects (negative emotions strongly impact health) related to the subjective perception of a worsening health status, regardless of the stage of the disease.