Browsing by Author "Hallett, Stephen"

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    Adapting smartphone app used in water testing, for soil nutrient analysis
    (Elsevier, 2020-06-03) Golicz, Karolina; Hallett, Stephen; Sakrabani, Ruben; Ghosh, Joy
    Smartphone technology has now penetrated every aspect of modern life. At such high rates of access and utilization, there is today much potential for the development of smartphones as high-performing tools in a number of industries. Traditionally, smartphones have been used as e.g. point-of-care testing devices in developing countries; now a similar approach can be extended to agriculture. This paper assesses the viability of utilizing smartphones in soil analysis. An Android-based smartphone application, in conjunction with commercially available Quantofix® test strips, was employed to analyze 92 soil samples collected across Indonesia. The soils tested encompassed a wide range of different textures (with 13%, 60% and 25% of samples constituting sandy, loamy and clayey soils, respectively), soil organic matter contents (range: 0.8–19.7%) and nutrient concentrations (range for plant-available N: 0.1–137.4 mg kg−1 and P: 1.2 to 64.2 mg kg−1; on dry soil basis). The app utilizes the smartphone as a portable reflectometer, which relates the color of test strips to the concentration of particular nutrients present in the soil medium. Three mobile devices currently available on the market, representing low, mid- and high-end products, were used to test the application. The results obtained via the smartphone were compared against standard methods for determination of extractable nitrate-N and exchangeable phosphorus (Olsen-P) under laboratory conditions. The smartphone-mediated soil analysis was found to have a high degree of agreement with standard methods for nitrate-N determination (87% of samples with nitrate-N differed by less than 10 mg kg−1 from the standard method for the high-end smartphone) but not for phosphorus determination where chemical interferences to test strip colour development were noted. All three mobile devices were shown to be effective as portable reflectometers. However, color perception was found to differ amongst the devices, resulting in a consistent bias between the high-end phone and the remaining appliances. Whereas, it is essential to consider the inter-smartphone variability in readings and environmental factors such as temperature prior to the smartphone-mediated soil analysis, the smartphone-test strip combination might be employed as acceptable screening tool for soil nutrient concentration assessment to enhance crop outcomes, increasing yield, and preventing over-application of inputs, reducing consequent financial and environmental impact. Further enhancements can test the applicability of smartphone-mediated soil analysis in field conditions.
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    Advancing the development and application of decision support systems for sustainable brownfield redevelopment.
    (Cranfield University, 2023-12) Hammond, Ellis Bernard; Coulon, Frederic; Hallett, Stephen; Beriro, Darren
    The redevelopment of brownfield sites is a vital part of ensuring sustainable urban development but has a range of challenges, including contamination and/or geotechnical hazards, leading to risk and cost implications. Brownfield redevelopment involves multiple stakeholders, from land use planners, land developers, and specialist consultants, to local community groups, and neighbouring residents. Understanding complex data and information can be difficult for decision-makers, which is exacerbated when communicating development scenarios and options with others. To support stakeholders, digital tools are often used, including specialised Decision Support Systems (DSSs). This PhD research investigates and contributes to the advancement of brownfield redevelopment DSSs. Existing and emerging challenges are evaluated, identifying improvement opportunities through a critical review of literature and large-scale sector- wide stakeholder consultation. A novel WebGIS-based DSS was developed in collaboration with land use planning stakeholders, applying the DSS to an area of post- industrial land within the Liverpool city region, UK. The DSS was evaluated through user testing, where improvements were identified and implemented, and verified, using a combination of empirical and user-testing methods. Overall, the approach and application of this PhD research demonstrates modern user led DSS development for brownfield applications, overcoming many of the limitations of existing work. The use of the DSS to support early-stage planning and redevelopment of brownfield land is aligned with and informs, multiple current policies for sustainable development and the use of applied digital technologies in planning and land development.
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    The application of land evaluation technique in the north-east of Libya
    (Cranfield University, 2006-08-10T13:45:00Z) Nwer, Bashir Ahmad Bashir; Hallett, Stephen; Brewer, Timothy R.
    Land evaluation is a prerequisite to achieving optimum utilisation of available land resources for agricultural production. The principal purpose of land evaluation is to predict the potential and the limitations of land for changing use. Food security is one of the most important issues of agriculture policy in Libya. The country aims to obtain self‐sufficiency for its in agricultural products which contribute largely to the diet of most of the population. Therefore, eighty per cent of water transferred from aquifer‐sourced in the south of the country to the north, is planned for agriculture development. Cereal crops such wheat, barley, maize and sorghum are given the highest priority. There is, therefore, a pressing need to develop an optimal land evaluation method to identify in which part of a region these selected crops could e grown favourably. The model should be developed in accordance with the priorities of the Libyan Government in developing a practical and applicable land evaluation system that can be used by the average computer user. The FAO Framework was selected to conduct the land suitability assessment. This selection was based upon extensive and critical review of land evaluation methodologies and an evaluation of the objectives for and of the data available for study area. The FAO framework is a set of guidelines rather than a classification system, and model used builds upon this.
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    Cationic nutrients and the effects of termite mounds on soil - vegetation associations - associated data
    (Cranfield University, 2022-01-04 09:10) Hallett, Stephen; Baillie, Ian C.; Kaewfoo, Manop; Bunyavejchewin, Sarayudh; Davies, Stuart; Marod, Dokrak; Wiwatwittaya, Decha
    A series of datasets related to studies to determine the cationic nutrients and the effects of termite mounds on soil - vegetation associations in Dry Dipterocarp Forest in northern Thailand.
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    CEiA_07:08:2019.xlsx
    (Cranfield University, 2020-08-07 08:41) Golicz, Karolina; Hallett, Stephen; Sakrabani, Ruben; Ghosh, Joy
    Data collected during laboratory experiments, which took place at Cranfield University. The dataset provides raw data, which accompanies a scientific paper titled: 'Development of a smartphone-mediated screening tool for determining soil nutrient content analysis in Indonesia'.
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    Coastal management and adaptation: an integrated data-driven approach
    (2019-03) Rumson, Alexander G.; Hallett, Stephen; Brewer, Timothy R.
    Coastal regions are some of the most exposed to environmental hazards, yet the coast is the preferred settlement site for a high percentage of the global population, and most major global cities are located on or near the coast. This research adopts a predominantly anthropocentric approach to the analysis of coastal risk and resilience. This centres on the pervasive hazards of coastal flooding and erosion. Coastal management decision-making practices are shown to be reliant on access to current and accurate information. However, constraints have been imposed on information flows between scientists, policy makers and practitioners, due to a lack of awareness and utilisation of available data sources. This research seeks to tackle this issue in evaluating how innovations in the use of data and analytics can be applied to further the application of science within decision-making processes related to coastal risk adaptation. In achieving this aim a range of research methodologies have been employed and the progression of topics covered mark a shift from themes of risk to resilience. The work focuses on a case study region of East Anglia, UK, benefiting from the input of a partner organisation, responsible for the region’s coasts: Coastal Partnership East. An initial review revealed how data can be utilised effectively within coastal decision-making practices, highlighting scope for application of advanced Big Data techniques to the analysis of coastal datasets. The process of risk evaluation has been examined in detail, and the range of possibilities afforded by open source coastal datasets were revealed. Subsequently, open source coastal terrain and bathymetric, point cloud datasets were identified for 14 sites within the case study area. These were then utilised within a practical application of a geomorphological change detection (GCD) method. This revealed how analysis of high spatial and temporal resolution point cloud data can accurately reveal and quantify physical coastal impacts. Additionally, the research reveals how data innovations can facilitate adaptation through insurance; more specifically how the use of empirical evidence in pricing of coastal flood insurance can result in both communication and distribution of risk. The various strands of knowledge generated throughout this study reveal how an extensive range of data types, sources, and advanced forms of analysis, can together allow coastal resilience assessments to be founded on empirical evidence. This research serves to demonstrate how the application of advanced data-driven analytical processes can reduce levels of uncertainty and subjectivity inherent within current coastal environmental management practices. Adoption of methods presented within this research could further the possibilities for sustainable and resilient management of the incredibly valuable environmental resource which is the coast.
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    The contributions of C. F. Charter to tropical soil survey and classification
    (Elsevier, 2020-10-22) Borden, R. Wayne; Brammer, Hugh; Baillie, Ian C.; Hallett, Stephen
    Cecil Charter had taught botany and biology in China and Antigua for five years, when in 1931 he was engaged to conduct a soil survey of the sugarcane-growing areas of Antigua. This was followed by similar surveys elsewhere in the Caribbean. In 1944, he joined the West African Cacao Research Institute in the Gold Coast (now Ghana) to carry out soil investigations in the forest zones of West Africa. In 1949 he moved to organise the soil survey unit in the Gold Coast Department of Agriculture, and, in 1951, to found and direct the new Soil and Land Use Survey Department. He rapidly built up a highly professional unit that produced many practical and useful reports of high quality. He based the surveys on ecological principles, selecting river basins as mapping regions. In the initial absence of qualified soil scientists, he subdivided the soil survey process and trained school leavers as technicians for separate tasks. Teams of these technicians examined soils, vegetation and land use at regular intervals on regularly-spaced traverses cut across the topography. Charter’s contributions to soil science included his recognition of non-residual tropical soils formed in material brought to the surface by soil fauna and treefall. Also, he differentiated between highly acidic upland Oxysols in high-rainfall areas, which he considered unsuitable for cocoa cultivation, and less acidic Ochrosols, which were more suitable. Based on farmers’ experience and his ecological background, he differentiated between forest, thicket and savannah soils within these groups. He strongly advocated genetic and contextual classification of tropical soils.
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    DAFNI: a computational platform to support infrastructure systems research
    (Institution of Civil Engineers - ICE, 2023-03-20) Matthews, Brian; Hall, Jim; Batty, Michael; Hallett, Stephen
    Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing historical data to inform system operations or assessing the impacts of infrastructure on the environment. Models are more complex, at higher resolution and with larger coverage. Researchers also require a ‘multi-systems’ approach to explore interactions between systems, such as energy and water with urban development, and across scales, from buildings and streets to regions or nations. Consequently, researchers need enhanced computational resources to support cross-institutional collaboration and sharing at scale. The Data and Analytics Facility for National Infrastructure (DAFNI) is an emerging computational platform for infrastructure systems research. It provides high-throughput compute resources so larger data sets can be used, with a data repository to upload data and share these with collaborators. Users’ models can also be uploaded and executed using modern containerisation techniques, giving platform independence, scaling and sharing. Further, models can be combined into workflows, supporting multi-systems modelling and generating visualisations to present results. DAFNI forms a central resource accessible to all infrastructure systems researchers in the UK, supporting collaboration and providing a legacy, keeping data and models available beyond the lifetime of a project.
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    Data for 'The potential for using smartphones as portable soil nutrient analyzers on suburban farms in central East China' paper
    (Cranfield University, 2019-11-12 16:40) Golicz, Karolina; Sakrabani, Ruben; Hallett, Stephen; Pan, Genxing
    The data presented in the spreadsheet underpins 'The potential for using smartphones as portable soil nutrient analyzers on suburban farms in central East China' paper published in Scientific Reports. Each tab corresponds to particular figure and/or table presented in the paper.
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    Developing a water strategy for sustainable irrigated agriculture in Mediterranean island communities – Insights from Malta
    (Sage, 2019-04-07) Papadimitriou, Lamprini; Hallett, Stephen; Sakrabani, Ruben; Borg, Malcolm; Thompson, Andrew; Knox, Jerry W.
    The future sustainability of irrigated agriculture in Mediterranean island communities faces a raft of economic, environmental and socio-economic challenges. Many of these are inextricably linked to the extreme levels of water scarcity that exist in the region. With a focus on Malta, we developed a water strategy to identify the priorities for action to support decision makers, practitioners and the agrifood industry in achieving agricultural and water resources sustainability. The methodology involved a combination of evidence synthesis, to inform the development of a Drivers-Pressures-State-Impact-Response framework. These priorities were then used to define a set of key actions under three thematic pillars of sustainability (environment, economy and society). Our analysis confirmed that irrigated agriculture in Malta is not only impacted by environmental factors such as the challenging climate and geography of the region but also strongly influenced by a range of economic (tourism development, European Union accession) and societal (population growth, environmental regulation) drivers of change. The developed strategy is underpinned by priority actions relating to improved water and soil management. The reduction of water and energy footprints in crop production, the establishment of demonstration farms and the support of policies that promote ‘value adding’ activities are examples of key priority actions for the environmental, economic and societal pillar, respectively. Regarding the scale of intervention, the analysis distinguishes research as being important for supporting many of the economy-focused actions.
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    Development of in-field diagnositc tool for soil nutrient screening.
    (Cranfield University, 2020-06) Golicz, Karolina K.; Sakrabani, Ruben; Hallett, Stephen
    The use of external inputs in the form of inorganic fertilisers is rising across the world. Rapidly growing crops such as vegetables necessitate high fertiliser inputs, whilst remaining an attractive cash-crop option for farmers, especially smallholders in the developing countries. For vegetable farming to be sustainable, these inputs should be monitored so the crop nutrient use efficiency is high and the potential for under- and over-fertilisation is low. Therefore, there is a need for the development of low-cost tools that can bring site-specific soil information to farmers who do not ordinarily have access to such knowledge. In recent years, smartphone technology has given rise to a number of advanced apps that aim to improve agronomic production, especially in the Southern Hemisphere. The work in this thesis centres around method development and appraisal for the application of a smartphone-mediated diagnostic tool for use in soil nutrient screening. A smartphone application marketed as Akvo Caddisfly, used together with nutrient-sensitive test strips was repurposed for the analysis of soil samples. The app was used alongside selected test strip types and underwent rigorous laboratory testing to evaluate its suitability for soil analysis and to identify its strengths and weaknesses. The laboratory-based experiments allowed for the development of soil extraction, filtration and analysis methodologies, through the utilisation of variable soil samples obtained from Indonesia, an approach subsequently employed in field conditions in other study sites. The field-based experiments were undertaken in the People’s Republic of China, Ghana and Kenya, allowing for a critical appraisal of smartphone-mediated soil analysis as an effective tool for fertiliser recommendations in smallholder vegetable production. In China, where frequent over-fertilisation of crops is the chief cause of soil acidification and heavy metal pollution as well as eutrophication of waterbodies and high N₂O emissions, smartphone-mediated soil analysis was employed successfully in identifying over-fertilised plots. In contrast, in Sub-Saharan Africa, where soil Nitrogen content was low, smartphone-mediated soil analysis encouraged farmers to apply organic fertilisers to improve their yields. Referencing the metadata, which was collected during laboratory and field-based experiments, a framework for designing and evaluating future in-field soil test kits was created. The data consisted of a collation of quantitative analyses and qualitative observations and these were synthesised into a step-by-step process that can be used at the test kit evaluation stage to reduce the time and costs associated with their development. Finally, a range of statistical approaches were employed to investigate the level of agreement between the in-field method and the accepted laboratory standard methods employed in agricultural soil analysis. They were described in detail to encourage their wider application in method comparison studies across environmental science.
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    Effective use of metallic Z-pins for composites' through-thickness reinforcement
    (Elsevier, 2019-02-28) M'membe, Beene; Yasaee, Mehdi; Hallett, Stephen; Partridge, Ivana K.
    Z-pins offer effective through-thickness reinforcement for laminated composites. Various studies have however, shown that metal Z-pins are less effective at bridging Mode I delaminations than carbon-fibre composite Z-pins, due to poor interfacial bonding with the laminate. This is exacerbated by high thermal mismatch between the metallic Z-pins and the laminate. This study investigates inserting metallic Z-pins at angles offset from the laminate normal, to improve the Mode I bridging in composites. The effects on the apparent fracture toughness under pure and mixed Mode I/II loads using single pin specimens is investigated. Results show that, unlike orthogonally inserted metal Z-pins, inclined Z-pins exhibit high energy absorption throughout the mixed mode range. Double Cantilever Beam (DCB) tests show that the inclined metal Z-pins increase the Mode I apparent fracture toughness by a factor of 2 compared to traditional carbon fibre Z-pins. In End Loaded Split (ELS) tests, the Mode II apparent fracture toughness of inclined stainless steel Z-pins, although less than their uninclined equivalent, is greater than that of carbon fibre Z-pins.
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    Evidence-based stragegies to inform urban design decision-making: the case of pedestrian movement behaviour.
    (Cranfield University, 2022-04) Stanitsa, Avgousta; Hallett, Stephen; Jude, Simon
    Walking is an essential mode of transportation, and pedestrian movement is a major influencing parameter in city design. Due to the complexity of pedestrian behaviour, new insights concerning the significance of factors affecting walking are challenging to obtain without the use of technology. Furthermore, despite the impact of decision-making in the design of buildings and places, there is currently a limited understanding concerning how urban design decisions are best made. This research aims to “assess the adoption of, and opportunities deriving from, data-driven innovation techniques in the design of urban spaces, by the analysis of pedestrian movement patterns in urban environments, and to evaluate how the integration of evidence-based strategies can be established in supporting decision-making in relation to future urban designs”. The research focuses on two groups of stakeholders: Decision-makers in designing buildings and places and End-users undertaking walking activities within urban space. In addressing the aim, a range of research methodologies has been developed and trialled. The work centres on an extended case study concerning a retail high-street locale in London, UK. This study makes several contributions to the immediate field of urban design research. Firstly, the findings advance the research methods applied to study pedestrian movement in urban environments. Secondly, the results offer real impact in practice by demonstrating the value and importance of adopting data-driven innovation techniques in decision-making processes in urban design via the adoption of a quantitative data- driven, evidence-based methodological framework. Thirdly, the findings support decision-making by presenting a novel methodological framework to assess pedestrian routing in urban environments utilising the classification of pedestrian behaviours and spatial visibility interactions. Finally, this study raises awareness of the critical challenges and opportunities, priorities, and potential development areas for applying evidence- based strategies in informing building and urban design decisions. The research presents a series of recommendations for enhancing data-driven innovation techniques in urban design decision-making processes.
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    An evolution of statistical pipe failure models for drinking water networks: a targeted review
    (IWA, 2022-01-19) Barton, Neal A.; Hallett, Stephen; Jude, Simon R.; Tran, Trung Hieu
    The use of statistical models to predict pipe failures has become an important tool for proactive management of drinking water networks. This targeted review provides an overview of the evolution of existing statistical models, grouped into three categories: deterministic, probabilistic and machine learning. The main advantage of deterministic models is simplicity and relative minimal data requirement. Deterministic models predicting failure rates for the network or large groups of pipes performs well and are useful for shorter prediction intervals that describe the influences of seasonality. Probabilistic models can accommodate randomness and are useful for predicting time to failure, interarrival times and the probability of failure. Probability models are useful for individual pipe models. Generally, machine learning describes large complex data more accurately and can improve predictions for individual pipe failure models yet are complex and require expert knowledge. Non-parametric models are better suited to the non-linear relationships between pipe failure variables. Census data and socio-economic data requires further research. The complexity of choosing the most appropriate statistical model requires careful consideration of the type of variables, prediction interval, spatial level, response type and level of inference is required.
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    The impact of soils, weather and trees on water infrastructure failure.
    (Cranfield University, 2018-09) North, Matthew Robert; Farewell, Timothy; Hallett, Stephen
    The uninterrupted supply and reliable distribution of drinking water is fundamental in a modern society; however, water pipelines are subject to a range of operational and environmental factors which can lead to asset failure. For the privatised water-sector in the UK, utility companies are moving towards the deployment of statistical models for proactive asset management. For some companies, statistical models have facilitated the migration away from static annual burst targets, to targets which are dynamic and adjusted to observed environmental conditions. There is an increasing need for the development of accurate pipeline failure prediction models to support asset management and regulatory reporting. This thesis evaluates several quantitative measures to improve current methods of pipeline failure prediction. The aim of this thesis is to establish the impact of soils, weather and trees on water infrastructure failure and to develop a series of material-specific drinking water pipeline failure models for an entire distribution network. A quantitative assessment investigating the impact of data cleaning on the attained model error of a series of previously developed models was conducted. Material-specific variable selection and step-wise modelling approaches was used to construct a series of improved statistical models, which have an increased representation of the environmental factors leading to pipeline failure. A detailed national tree inventory was investigated for its use in enhancing pipeline failure predictions and for calculating failure rates of different pipe materials under varying soil shrink swell and tree density conditions. The value in creating separate winter and summer pipeline failure models was also evaluated, to increase representation of the highly seasonal nature of pipeline failure. Finally, a satellite approach was used to generate soil-related land surface deformation measurements across a regional area was investigated. The result is a series of enhanced statistical models for the prediction of water pipeline failure and a greater understanding into the environmental drivers leading to asset failure.
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    Improving soil and water management for agriculture: insights and innovation from Malta
    (Malta College of Arts, Science & Technology, 2017-11-30) Hallett, Stephen; Sakrabani, Ruben; Thompson, Andrew; Deeks, Lynda K.; Knox, Jerry W.
    Maltese soil resources are a precious and finite natural resource of great agricultural, environmental, and cultural value. They have been subject to human influence over a considerable time and, owing to prolonged intensive land use, have suffered from degradation by erosion, loss of organic matter, structural deterioration, and contamination from excess nitrates, agrochemicals, and salinity. Similarly, water resources (both quantity and quality) in Malta are also under severe stress owing to socio-economic development, over-abstraction for agricultural irrigation and from diffuse pollution. This paper briefly explores the key soil and water challenges facing farmers and the agricultural sector in Malta. Selected technology based and management innovations to improve resource use efficiency, sustain productivity, and support the agricultural sector are identified and discussed. The evidence forms part of FOWARIM ‘Fostering water-agriculture research and innovation in Malta’, an EC H2020-funded twinning project that is building research capacity, supporting knowledge exchange to practitioners, and providing evidence to inform policies for government and the agricultural sector in Malta.
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    Infrastructure and cities ontologies
    (Institution of Civil Engineers - ICE, 2023-06-01) Varga, Liz; McMillan, Lauren; Hallett, Stephen; Russell, Tom; Smith, Luke; Truckell, Ian; Postnikov, Andrey; Rodger, Sunil; Vizcaino, Noel; Perkins, Bethan; Matthews, Brian; Lomax, Nik
    The creation and use of ontologies has become increasingly relevant for complex systems in recent years. This is because of the growing number of use of cases that rely on real-world integration of disparate systems, the need for semantic congruence across boundaries and the expectations of users for conceptual clarity within evolving domains or systems of interest. These needs are evident in most spheres of research involving complex systems, but they are particularly apparent in infrastructure and cities where traditionally siloed and sectoral approaches have dominated, undermining the potential for integration to solve societal challenges such as net zero, resilience to climate change, equity and affordability. This paper reports on findings of a literature review on infrastructure and city ontologies and puts forward some hypotheses inferred from the literature findings. The hypotheses are discussed with reference to the literature and provide avenues for further research on (a) belief systems that underpin non-top-level ontologies and the potential for interference from them, (b) the need for a small number of top-level ontologies and translation mechanisms between them and (c) clarity on the role of standards and information systems in the adaptability and quality of data sets using ontologies. A gap is also identified in the extent that ontologies can support more complex automated coupling and data transformation when dealing with different scales.
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    Monitoring the response of roads and railways to seasonal soil movement with persistent scatterers interferometry over six UK sites
    (MDPI, 2017-09-04) North, Matthew; Farewell, Tim; Hallett, Stephen; Bertelle, Audrey
    Road and rail networks provide critical support for society, yet they can be degraded by seasonal soil movements. Currently, few transport network operators monitor small-scale soil movement, but understanding the conditions contributing to infrastructure failure can improve network resilience. Persistent Scatterers Interferometry (PSI) is a remote sensing technique offering the potential for near real-time ground movement monitoring over wide areas. This study tests the use of PSI for monitoring the response of major roads, minor roads, and railways to ground movement across six study sites in England, using Sentinel 1 data in VV polarisation in ascending orbit. Some soils are more stable than others—a national soil map was used to quantify the relationships between infrastructure movement and major soil groups. Vertical movement of transport infrastructure is a function of engineering design, soil properties, and traffic loading. Roads and railways built on soil groups prone to seasonal water-logging (Ground-water Gley soils, Surface-water Gley soils, Pelosols, and Brown soils) demonstrated seasonal subsidence and heave, associated with an increased risk of infrastructure degradation. Roads and railways over Podzolic soils demonstrated relative stability. Railways on Peat soils exhibited the most extreme continual subsidence of up to 7.5 mm year−1. Limitations of this study include the short observation period (~13 months, due to satellite data availability) and the regional scale of the soil map—mapping units contain multiple soil types with different ground movement potentials. Future use of a higher resolution soil map over a longer period will advance this research. Nevertheless, this study demonstrates the viability of PSI as a technique for measuring both seasonal soil-related ground movement and the associated impacts on road and rail infrastructure.
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    Natural vegetation cover changes in north-east Libya.
    (Cranfield University, 2019-07) Almesmari, Nagat M. G.; Hallett, Stephen; Simmons, Robert W.
    The vegetation cover in Al Jabal Al Akhdar has been subjected to human and natural pressures that have contributed to the deterioration and shrinking of the vegetated area. Therefore, the principle goal of this dissertation was to establish and evaluate the changes in the natural vegetation of the Al Jabal Al Akhdar region in the period following the 2011 Libyan uprising. The thesis is comprised of three main objectives; the first is to provide a quantitative assessment of changes in natural vegetation cover over a period from 2004-2016, and identify the consequent impact of human activity; the second is to investigate the impact of climate on the natural vegetation cover; and the third objective is to evaluate the ability of machine learning techniques to predict the natural vegetation cover types. GIS and remote sensing techniques and Landsat imagery, population MODIS NDVI and climate satellite-based data have been used to achieve these objectives, along with the ancillary data, across 53 sites in the study area. Six classified Landsat image scenes have been used for undertaking a post- classification comparison approach to detect the changes and the types of changes, by the use of image processing, GIS software and spreadsheet, and programme scripts used to detect LULC changes and determine human activities impact. The correlaction between the ANDVI and climate factors for each lanform, and the trends of climate factors and ANDVI for each sites in each landform have been undertaken using statistical analysis package and spreadsheet. Lastly the machine learning ‘J48’ algorithm, within the WEKA tool, was applied on ANDVI, climate data, and spatial characteristics for 53 sites and analysed statistically to test its ability to predict the natural vegetation type. The main research findings have confirmed that from 2004-2016, natural forest and rangelands decreased by 71,543 ha or 7.10% of the total area as a result of urbanisation and agricultural expansion. Human activities have had more impact than climate impact on LULC changes. The machine learning classifier decision tree ‘J48’ algorithm was also found to have the ability to classify and predict the natural vegetation cover type. Finally, an evaluation was undertaken of the current distribution of natural vegetation cover, and a forecast of future changes, utilising high-resolution imagery is recommended. A conclusion considers how developing action plans using tools such as those described to manage and protect the natural vegetation cover are highly recommended.
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    Novel procedures for testing of soil field test kits involving paper strips
    (Wiley, 2020-02-08) Golicz, Karolina; Hallett, Stephen; Sakrabani, Ruben
    The need for facilitation of access to soil information has never been greater. Growing human population, shrinking land and water resources, soil pollution, climate change and unequal distribution of agriculture-oriented technology impact negatively on global food security. There has been a long-standing interest in developing low-cost and easily accessible soil field kits to measure different properties of agricultural soils in order to improve their agronomic capacity. Test strips, in particular, have provided a favoured method of obtaining soil nutrient status information since the 1970s. Today there is renewed interest in using semi-qualitative colorimetric methods in soil assessment due to incorporation of modern technological solutions, such as smartphones, which could in turn increase the accuracy and precision of the existing methods. In this paper, we propose streamlined testing procedures based on experience gathered that may be conducted prior to a field kit development involving test strips. Results from laboratory and field experiments are presented, highlighting important factors which ought to be taken into account at the commencement of test-strip oriented studies.