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.

Multi-wavelength switchable fibre ring laser based on polarisation selective tilted fibre gratings capable of strain and temperature sensing

Using three fibre gratings with excessively tilted structures in the cavity, we have experimentally demonstrated a multiwavelength switchable erbium-doped fibre ring laser system. The three tilted gratings act as in-fibre polariser and polarisation dependent loss filters to induce the polarisation hole burning effect in the cavity for the operation of the laser at single, double, triple and quadruple wavelengths. The laser system has demonstrated good stability under room temperature conditions and also achieved a high degree of polarization (~30dB), high optical signal to noise ratio (up to 63dB) and high side mode suppression (~50dB). The system has also been investigated for temperature and strain sensing by subjecting the seeding fibre Bragg gratings (FBG) to temperature and strain variations. Since the loss band of the polarisation dependent loss filter is broader than the bandwidth of the seeding FBG, the laser output shifts in wavelength with the applied temperature and strain. The fibre ring laser has shown good responses to the temperature and strain, providing sensitivities of approximately 11.7 pm/°C and 0.85pm/µe respectively.

Business sustainability through successful integration of marketing and operations

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Multi-wavelength switchable fibre ring laser based on polarisation selective tilted fibre gratings capable of strain and temperature sensing

Using three fibre gratings with excessively tilted structures in the cavity, we have experimentally demonstrated a multiwavelength switchable erbium-doped fibre ring laser system. The three tilted gratings act as in-fibre polariser and polarisation dependent loss filters to induce the polarisation hole burning effect in the cavity for the operation of the laser at single, double, triple and quadruple wavelengths. The laser system has demonstrated good stability under room temperature conditions and also achieved a high degree of polarization (~30dB), high optical signal to noise ratio (up to 63dB) and high side mode suppression (~50dB). The system has also been investigated for temperature and strain sensing by subjecting the seeding fibre Bragg gratings (FBG) to temperature and strain variations. Since the loss band of the polarisation dependent loss filter is broader than the bandwidth of the seeding FBG, the laser output shifts in wavelength with the applied temperature and strain. The fibre ring laser has shown good responses to the temperature and strain, providing sensitivities of approximately 11.7 pm/°C and 0.85pm/µe respectively.

Theory of hybrid computational and physical measurement-based integration of thermal and dimensional measurement

In dimensional metrology, often the largest source of uncertainty of measurement is thermal variation. Dimensional measurements are currently scaled linearly, using ambient temperature measurements and coefficients of thermal expansion, to ideal metrology conditions at 20˚C. This scaling is particularly difficult to implement with confidence in large volumes as the temperature is unlikely to be uniform, resulting in thermal gradients. A number of well-established computational methods are used in the design phase of product development for the prediction of thermal and gravitational effects, which could be used to a greater extent in metrology. This paper outlines the theory of how physical measurements of dimension and temperature can be combined more comprehensively throughout the product lifecycle, from design through to the manufacturing phase. The Hybrid Metrology concept is also introduced: an approach to metrology, which promises to improve product and equipment integrity in future manufacturing environments. The Hybrid Metrology System combines various state of the art physical dimensional and temperature measurement techniques with established computational methods to better predict thermal and gravitational effects.

Expanding the biomass resource:sustainable oil production via fast pyrolysis of low input high diversity biomass and the potential integration of thermochemical and biological conversion routes

Waste biomass is generated during the conservation management of semi-natural habitats, and represents an unused resource and potential bioenergy feedstock that does not compete with food production. Thermogravimetric analysis was used to characterise a representative range of biomass generated during conservation management in Wales. Of the biomass types assessed, those dominated by rush (Juncus effuses) and bracken (Pteridium aquilinum) exhibited the highest and lowest volatile compositions respectively and were selected for bench scale conversion via fast pyrolysis. Each biomass type was ensiled and a sub-sample of silage was washed and pressed. Demineralization of conservation biomass through washing and pressing was associated with higher oil yields following fast pyrolysis. The oil yields were within the published range established for the dedicated energy crops miscanthus and willow. In order to examine the potential a multiple output energy system was developed with gross power production estimates following valorisation of the press fluid, char and oil. If used in multi fuel industrial burners the char and oil alone would displace 3.9 × 105 tonnes per year of No. 2 light oil using Welsh biomass from conservation management. Bioenergy and product development using these feedstocks could simultaneously support biodiversity management and displace fossil fuels, thereby reducing GHG emissions. Gross power generation predictions show good potential.

Decision support based on genomics:integration of data-and knowledge-driven reasoning

The breadth and depth of available clinico-genomic information, present an enormous opportunity for improving our ability to study disease mechanisms and meet the individualised medicine needs. A difficulty occurs when the results are to be transferred 'from bench to bedside'. Diversity of methods is one of the causes, but the most critical one relates to our inability to share and jointly exploit data and tools. This paper presents a perspective on current state-of-the-art in the analysis of clinico-genomic data and its relevance to medical decision support. It is an attempt to investigate the issues related to data and knowledge integration. Copyright © 2010 Inderscience Enterprises Ltd.

A simple remote sensing based information system for monitoring sites of conservation importance

Monitoring is essential for conservation of sites, but capacity to undertake it in the field is often limited. Data collected by remote sensing has been identified as a partial solution to this problem, and is becoming a feasible option, since increasing quantities of satellite data in particular are becoming available to conservationists. When suitably classified, satellite imagery can be used to delineate land cover types such as forest, and to identify any changes over time. However, the conservation community lacks (a) a simple tool appropriate to the needs for monitoring change in all types of land cover (e.g. not just forest), and (b) an easily accessible information system which allows for simple land cover change analysis and data sharing to reduce duplication of effort. To meet these needs, we developed a web-based information system which allows users to assess land cover dynamics in and around protected areas (or other sites of conservation importance) from multi-temporal medium resolution satellite imagery. The system is based around an open access toolbox that pre-processes and classifies Landsat-type imagery, and then allows users to interactively verify the classification. These data are then open for others to utilize through the online information system. We first explain imagery processing and data accessibility features, and then demonstrate the toolbox and the value of user verification using a case study on Nakuru National Park, Kenya. Monitoring and detection of disturbances can support implementation of effective protection, assist the work of park managers and conservation scientists, and thus contribute to conservation planning, priority assessment and potentially to meeting monitoring needs for Aichi target 11.

A low-cost remote sensing system for agricultural applications

This research develops a low cost remote sensing system for use in agricultural applications. The important features of the system are that it monitors the near infrared and it incorporates position and attitude measuring equipment allowing for geo-rectified images to be produced without the use of ground control points. The equipment is designed to be hand held and hence requires no structural modification to the aircraft. The portable remote sensing system consists of an inertia measurement unit (IMU), which is accelerometer based, a low-cost GPS device and a small format false colour composite digital camera. The total cost of producing such a system is below GBP 3000, which is far cheaper than equivalent existing systems. The design of the portable remote sensing device has eliminated bore sight misalignment errors from the direct geo-referencing process. A new processing technique has been introduced for the data obtained from these low-cost devices, and it is found that using this technique the image can be matched (overlaid) onto Ordnance Survey Master Maps at an accuracy compatible with precision agriculture requirements. The direct geo-referencing has also been improved by introducing an algorithm capable of correcting oblique images directly. This algorithm alters the pixels value, hence it is advised that image analysis is performed before image georectification. The drawback of this research is that the low-cost GPS device experienced bad checksum errors, which resulted in missing data. The Wide Area Augmented System (WAAS) correction could not be employed because the satellites could not be locked onto whilst flying. The best GPS data were obtained from the Garmin eTrex (15 m kinematic and 2 m static) instruments which have a highsensitivity receiver with good lock on capability. The limitation of this GPS device is the inability to effectively receive the P-Code wavelength, which is needed to gain the best accuracy when undertaking differential GPS processing. Pairing the carrier phase L1 with the pseudorange C/A-Code received, in order to determine the image coordinates by the differential technique, is still under investigation. To improve the position accuracy, it is recommended that a GPS base station should be established near the survey area, instead of using a permanent GPS base station established by the Ordnance Survey.

Integration of a 3D hydrogel matrix within a hollow core photonic crystal fibre for DNA probe immobilization

In this paper, we demonstrate the integration of a 3D hydrogel matrix within a hollow core photonic crystal fibre (HC-PCF). In addition, we also show the fluorescence of Cy5-labelled DNA molecules immobilized within the hydrogel formed in two different types of HC-PCF. The 3D hydrogel matrix is designed to bind with the amino groups of biomolecules using an appropriate cross-linker, providing higher sensitivity and selectivity than the standard 2D coverage, enabling a greater number of probe molecules to be available per unit area. The HC-PCFs, on the other hand, can be designed to maximize the capture of fluorescence to improve sensitivity and provide longer interaction lengths. This could enable the development of fibre-based point-of-care and remote systems, where the enhanced sensitivity would relax the constraints placed on sources and detectors. In this paper, we will discuss the formation of such polyethylene glycol diacrylate (PEGDA) hydrogels within a HC-PCF, including their optical properties such as light propagation and auto-fluorescence.

Area summation of first- and second-order modulations of luminance

To extend our understanding of the early visual hierarchy, we investigated the long-range integration of first- and second-order signals in spatial vision. In our first experiment we performed a conventional area summation experiment where we varied the diameter of (a) luminance-modulated (LM) noise and (b) contrastmodulated (CM) noise. Results from the LM condition replicated previous findings with sine-wave gratings in the absence of noise, consistent with long-range integration of signal contrast over space. For CM, the summation function was much shallower than for LM suggesting, at first glance, that the signal integration process was spatially less extensive than for LM. However, an alternative possibility was that the high spatial frequency noise carrier for the CM signal was attenuated by peripheral retina (or cortex), thereby impeding our ability to observe area summation of CM in the conventional way. To test this, we developed the ''Swiss cheese'' stimulus of Meese and Summers (2007) in which signal area can be varied without changing the stimulus diameter, providing some protection against inhomogeneity of the retinal field. Using this technique and a two-component subthreshold summation paradigm we found that (a) CM is spatially integrated over at least five stimulus cycles (possibly more), (b) spatial integration follows square-law signal transduction for both LM and CM and (c) the summing device integrates over spatially-interdigitated LM and CM signals when they are co-oriented, but not when crossoriented. The spatial pooling mechanism that we have identified would be a good candidate component for amodule involved in representing visual textures, including their spatial extent.

Evaluation of remote sensing for the detection of landfill gas and leachate in an urban environment

The technique of remote sensing provides a unique view of the earth's surface and considerable areas can be surveyed in a short amount of time. The aim of this project was to evaluate whether remote sensing, particularly using the Airborne Thematic Mapper (ATM) with its wide spectral range, was capable of monitoring landfill sites within an urban environment with the aid of image processing and Geographical Information Systems (GIS) methods. The regions under study were in the West Midlands conurbation and consisted of a large area in what is locally known as the Black Country containing heavy industry intermingled with residential areas, and a large single active landfill in north Birmingham. When waste is collected in large volumes it decays and gives off pollutants. These pollutants, landfill gas and leachate (a liquid effluent), are known to be injurious to vegetation and can cause stress and death. Vegetation under stress can exhibit a physiological change, detectable by the remote sensing systems used. The chemical and biological reactions that create the pollutants are exothermic and the gas and leachate, if they leave the waste, can be warmer than their surroundings. Thermal imagery from the ATM (daylight and dawn) and thermal video were obtained and used to find thermal anomalies on the area under study. The results showed that vegetation stress is not a reliable indicator of landfill gas migration, as sites within an urban environment have a cover too complex for the effects to be identified. Gas emissions from two sites were successfully detected by all the thermal imagery with the thermal ATM being the best. Although the results were somewhat disappointing, recent technical advancements in the remote sensing systems used in this project would allow geo-registration of ATM imagery taken on different occasions and the elimination of the effects of solar insolation.

Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

The investigation of vegetation change using remote sensing to detect and monitor migration of landfill gas

Decomposition of domestic wastes in an anaerobic environment results in the production of landfill gas. Public concern about landfill disposal and particularly the production of landfill gas has been heightened over the past decade. This has been due in large to the increased quantities of gas being generated as a result of modern disposal techniques, and also to their increasing effect on modern urban developments. In order to avert diasters, effective means of preventing gas migration are required. This, in turn requires accurate detection and monitoring of gas in the subsurface. Point sampling techniques have many drawbacks, and accurate measurement of gas is difficult. Some of the disadvantages of these techniques could be overcome by assessing the impact of gas on biological systems. This research explores the effects of landfill gas on plants, and hence on the spectral response of vegetation canopies. Examination of the landfill gas/vegetation relationship is covered, both by review of the literature and statistical analysis of field data. The work showed that, although vegetation health was related to landfill gas, it was not possible to define a simple correlation. In the landfill environment, contribution from other variables, such as soil characteristics, frequently confused the relationship. Two sites are investigated in detail, the sites contrasting in terms of the data available, site conditions, and the degree of damage to vegetation. Gas migration at the Panshanger site was dominantly upwards, affecting crops being grown on the landfill cap. The injury was expressed as an overall decline in plant health. Discriminant analysis was used to account for the variations in plant health, and hence the differences in spectral response of the crop canopy, using a combination of soil and gas variables. Damage to both woodland and crops at the Ware site was severe, and could be easily related to the presence of gas. Air photographs, aerial video, and airborne thematic mapper data were used to identify damage to vegetation, and relate this to soil type. The utility of different sensors for this type of application is assessed, and possible improvements that could lead to more widespread use are identified. The situations in which remote sensing data could be combined with ground survey are identified. In addition, a possible methodology for integrating the two approaches is suggested.