Living long-term with acquired brain injury in Ireland: towards a counter discourse

Irish literature on Acquired Brain Injury (ABI) is very scant and is mainly deficits and/or needs based. The focus is generally on how to manage the short term needs of the younger population with ABI. The starting position of my thesis is that people living long-term with ABI are important participants in developing knowledge about this social phenomenon, living with ABI while accepting that their brain injury does not determine them. Six mature adults with ABI and their six significant others participated in this longitudinal study. Using a narrative approach in interviews, over twenty months, five repeat individual interviews with each of the twelve participants was held. From this I gained an understanding of their lived experiences, their life-world and their experiences of our local public ABI/disability services, systems and discourse. Along with this new empirical data, theoretical developments from occupational therapy, occupational science, sociology, and disability studies were also used within a meta-narrative informed by critical theory and critical realism to develop a synthesis of this study. Social analysis of their narratives co-constructed with me, allowed me generate nuanced insights into tendencies and social processes that impacted and continues to impact on their everyday-everynight living. I discuss in some depth here, the relational attitudinal, structural, occupational and environmental supports, barriers or discrimination that they face(d) in their search for social participation and community inclusion. Personal recognition of the disabled participants by their family, friends and/or local community, was generally enhanced after much suffering, social supports, slow recovery, and with some form of meaningful occupational engagement. This engagement was generally linked with pre-injury interests or habits, while Time itself became both a major aid and a need. The present local ABI discourse seldom includes advocacy and inclusion in everyday/every night local events, yet most participants sought both peer-support or collective recognition, and social/community inclusion to help develop their own counter-discourse to the dominant ABI discourse. This thesis aims to give a broad social explanation on aspects of their social becoming, 'self-sameness' and social participation, and the status of the disabled participants wanting to live 'the slow life'. Tensions and dialectical issues involved in moving from the category of a person in coma, to person with a disability, to being a citizen should not demote the need for special services. While individualized short-term neuro-rehabilitation is necessary, it is not sufficient. Along with the participants, this researcher asks that community health and/or social care planners and service-providers rethink how ABI is understood and represented, and how people with ABI are included in their local communities

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.

Global and local perceptual style, field-independence, and central coherence: an attempt at concept validation

Historically, the concepts of field-independence, closure flexibility, and weak central coherence have been used to denote a locally, rather globally, dominated perceptual style. To date, there has been little attempt to clarify the relationship between these constructs, or to examine the convergent validity of the various tasks purported to measure them. To address this, we administered 14 tasks that have been used to study visual perceptual styles to a group of 90 neuro-typical adults. The data were subjected to exploratory factor analysis. We found evidence for the existence of a narrowly defined weak central coherence (field-independence) factor that received loadings from only a few of the tasks used to operationalise this concept. This factor can most aptly be described as representing the ability to dis-embed a simple stimulus from a more complex array. The results suggest that future studies of perceptual styles should include tasks whose theoretical validity is empirically verified, as such validity cannot be established merely on the basis of a priori task analysis. Moreover, the use of multiple indices is required to capture the latent dimensions of perceptual styles reliably.