Some effects of vehicle and industrially generated emissions on the environment

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Autonomous Systems for the Environmental Characterization of Lagoons

This chapter reviews the state of the art in robotics and autonomous systems (RAS) for monitoring the environmental characteristics of lagoons, as well as potential future uses of such technologies that could contribute to enhancing current monitoring programmes. Particular emphasis will be given to unmanned aerial vehicles (UAVs), autonomous under water vehicles (AUVs), remotely operated underwater vehicles (ROVs) and (semi-)autonomous boats. Recent technological advances in UAVs, AUVs and ROVs have demonstrated that high-resolution data (e.g. 0.4 cm imagery resolution) can be gathered when bespoke sensors are incorporated within these platforms. This in turn enables the accurate quantification of key metrics within lagoon environments, such as coral morphometries. For example, coral height and width can now be estimated remotely with errors below 12.6 and 14.7 cm, respectively. The chapter will explore how the use of such technologies in combination could improve the understanding of lagoon environments through increased knowledge of the spatial and temporal variations of parameters of interest. Within this context, both advantages and limitations of the proposed approaches will be highlighted and described from operational, logistical, and regulatory considerations. The chapter will be based on recent peer-reviewed research outputs obtained by the authors

Using 1st derivative reflectance signatures within a remote sensing framework to identify macroalgae in marine environments

Macroalgae blooms (MABs) are a global natural hazard that are likely to increase in occurrence with climate change and increased agricultural runoff. MABs can cause major issues for indigenous species, fish farms, nuclear power stations, and tourism activities. This project focuses on the impacts of MABs on the operations of a British nuclear power station. However, the outputs and findings are also of relevance to other coastal operators with similar problems. Through the provision of an early-warning detection system for MABs, it should be possible to minimize the damaging effects and possibly avoid them altogether. Current methods based on satellite imagery cannot be used to detect low-density mobile vegetation at various water depths. This work is the first step towards providing a system that can warn a coastal operator 6–8 h prior to a marine ingress event. A fundamental component of such a warning system is the spectral reflectance properties of the problematic macroalgae species. This is necessary to optimize the detection capability for the problematic macroalgae in the marine environment. We measured the reflectance signatures of eight species of macroalgae that we sampled in the vicinity of the power station. Only wavelengths below 900 nm (700 nm for similarity percentage (SIMPER)) were analyzed, building on current methodologies. We then derived 1st derivative spectra of these eight sampled species. A multifaceted univariate and multivariate approach was used to visualize the spectral reflectance, and an analysis of similarities (ANOSIM) provided a species-level discrimination rate of 85% for all possible pairwise comparisons. A SIMPER analysis was used to detect wavebands that consistently contributed to the simultaneous discrimination of all eight sampled macroalgae species to both a group level (535–570 nm), and to a species level (570–590 nm). Sampling locations were confirmed using a fixed-wing unmanned aerial vehicle (UAV), with the collected imagery being used to produce a single orthographic image via standard photogrammetric processes. The waveband found to contribute consistently to group-level discrimination has previously been found to be associated with photosynthetic pigmentation, whereas the species-level discriminatory waveband did not share this association. This suggests that the photosynthetic pigments were not spectrally diverse enough to successfully distinguish all eight species. We suggest that future work should investigate a Charge-Coupled Device (CCD)-based sensor using the wavebands highlighted above. This should facilitate the development of a regional-scale early-warning MAB detection system using UAVs, and help inform optimum sensor filter selection.

Protection motivation theory: a proposed theoretical extension and moving beyond rationality-the case of flooding

Despite the significant financial and non-financial costs of household flooding, and the availability of products that can reduce the risk or impact of flooding, relatively few consumers choose to adopt these products. To help explain this, we combine the existing theoretical literature with evidence from 20 one-to-one discussions and three workshops with key stakeholders, as well as five round tables, to draw practical evidence of actual responses to flood risk. This analysis leads us to propose an extension to Protection Motivation Theory (PMT), which more accurately captures the decision-making process of consumers by highlighting the role of 'ownership appraisal'. We then assess the extent to which behavioral biases impact on this revised framework. By highlighting the interaction with an augmented model of PMT and behavioral biases, the paper sheds light on potential reasons behind the fact that consumers are unlikely to adopt property-level flood resilience measures and identifies strategies to increase flood protection. The Augmented PMT suggests that policymakers might focus on increasing the Ownership Appraisal element, both directly and by targeting the creation of more supportive social norms. The work presented here opens up a wide range of areas for future research in the field

A remote sensing based integrated approach to quantify the impact of fluvial and pluvial flooding in an urban catchment

Pluvial (surface water) flooding is often the cause of significant flood damage in urban areas. However, pluvial flooding is often overlooked in catchments which are historically known for fluvial floods. In this study, we present a conceptual remote sensing based integrated approach to enhance current practice in the estimation of flood extent and damage and characterise the spatial distribution of pluvial and fluvial flooding. Cockermouth, a town which is highly prone to flooding, was selected as a study site. The flood event caused by named storm Desmond in 2015 (5-6/12/2015) was selected for this study. A high resolution digital elevation model (DEM) was produced from a composite digital surface model (DSM) and a digital terrain model (DTM) obtained from the Environment Agency. Using this DEM, a 2D flood model was developed in HEC-RAS (v5) 2D for the study site. Simulations were carried out with and without pluvial flooding. Calibrated models were then used to compare the fluvial and combined (pluvial and fluvial) flood damage areas for different land use types. The number of residential properties affected by both fluvial and combined flooding was compared using a combination of modelled results and data collected from Unmanned Aircraft Systems (UAS). As far as the authors are aware, this is the first time that remote sensing data, hydrological modelling and flood damage data at a property level have been combined to differentiate between the extent of flooding and damage caused by fluvial and pluvial flooding in the same event. Results show that the contribution of pluvial flooding should not be ignored, even in a catchment where fluvial flooding is the major cause of the flood damages. Although the additional flood depths caused by the pluvial contribution were lower than the fluvial flood depths, the affected area is still significant. Pluvial flooding increased the overall number of affected properties by 25%. In addition, it increased the flood depths in a number of properties that were identified as being affected by fluvial flooding, in some cases by more than 50%. These findings show the importance of taking pluvial flooding into consideration in flood management practices. Further, most of the data used in this study was obtained via remote sensing methods, including UAS. This demonstrates the merit of developing a remote sensing based framework to enhance current practices in the estimation of both flood extent and damage

Towards more effective strategies to reduce property level flood risk: standardising the use of Unmanned Aerial Vehicles

Effective flood risk management strategies require a detailed understanding of the source, extent and impact of flooding. Unmanned Aerial Vehicles (UAVs) enable detailed and accurate data collection that can be used to determine flood source, extent, impact and the presence of property level flood resistance measures. This paper draws on the practical experience of the authors including the use of UAVs during flood events. We highlight the potential uses of UAVs in flood risk management activities and the associated challenges. The impact of a flooding event will also be dependent on how well an area is prepared in terms of community and property level resistance and resilience measures. We have looked at potential reasons why there is not a greater uptake of property level resistance and resilience measures. It is clear that a standardised approach is required if UAVs are to fulfil their potential within flood risk management activities. We have identified five pillars of standardisation that underpin an overarching, purpose-driven, cost-effective systems-based approach to the use of UAVs in flood risk management. These are as follows: (P1) deployment, data collection and flight-related regulatory requirements; (P2) data processing, data merging and outputs; (P3) the introduction and use of innovative approaches and technological integration; (P4) use of outputs for public engagement and (P5) policy development and governance. We consider that the proposed approach will maximise cost-effective information gathering, standardise the way processed outcomes are generated and provide the basis for comparable and robust flood risk information that is based on a single coherent methodolog

The use of unmanned aerial vehicles to estimate direct tangible losses to residential properties from flood events: A case study of Cockermouth following the Desmond storm

Damage caused by flood events is expected to increase in the coming decades driven by increased land use pressures and climate change impacts. The insurance sector needs accurate and efficient loss adjustment methodologies for flood events. These can include remote sensing approaches that enable the rapid estimation of (i) damage caused to property as well as (ii) the number of affected properties. Approaches based on traditional remote sensing methods have limitations associated with low-cloud cover presence, oblique viewing angles, and the resolution of the geomatic products obtained. Unmanned aerial vehicles (UAVs) are emerging as a potential tool for post-event assessment and provide a means of overcoming the limitations listed above. This paper presents a UAV-based loss-adjustment framework for the estimation of direct tangible losses to residential properties affected by flooding. For that purpose, features indicating damage to property were mapped from UAV imagery collected after the Desmond storm (5 and 6 December 2015) over Cockermouth (Cumbria, UK). Results showed that the proposed framework provided an accuracy of 84% in the detection of direct tangible losses compared with on-the-ground household-by-household assessment approaches. Results also demonstrated the importance of pluvial and, from eye witness reports, lateral flow flooding, with a total of 168 properties identified as flooded falling outside the fluvial flood extent. The direct tangible losses associated with these additional properties amounted to as high as £3.6 million. The damage-reducing benefits of resistance measures were also calculated and amounted to around £4 million. Differences in direct tangible losses estimated using the proposed UAV approach and the more classic loss-adjustment methods relying on the fluvial flood extent was around £1 million—the UAV approach providing the higher estimate. Overall, the study showed that the proposed UAV approach could make a significant contribution to improving the estimation of the costs associated with urban flooding, and responses to flooding events, at national and international levels

Appraising longitudinal trends in the strategic risks cited by risk managers in the international water utility sector, 2005-2015

We report dynamic changes in the priorities for strategic risks faced by international water utilities over a 10 year period, as cited by managers responsible for managing them. A content analysis of interviews with three cohorts of risk managers in the water sector was undertaken. Interviews probed the focus risk managers' were giving to strategic risks within utilities, as well as specific questions on risk analysis tools (2005); risk management cultures (2011) and the integration of risk management with corporate decision-making (2015). The coding frequency of strategic (business, enterprise, corporate) risk terms from 18 structured interviews (2005) and 28 semi-structured interviews (12 in 2011; 16 in 2015) was used to appraise changes in the perceived importance of strategic risks within the sector. The aggregated coding frequency across the study period, and changes in the frequency of strategic risks cited at three interview periods identified infrastructure assets as the most significant risk over the period and suggests an emergence of extrinsic risk over time. Extended interviews with three utility risk managers (2016) from the UK, Canada and the US were then used to contextualise the findings. This research supports the ongoing focus on infrastructure resilience and the increasing prevalence of extrinsic risk within the water sector, as reported by the insurance sector and by water research organisations. The extended interviews provided insight into how strategic risks are now driving the implementation agenda within utilities, and into how utilities can secure tangible business value from proactive risk governance. Strategic external risks affecting the sector are on the rise, involve more players and are less controllable from within a utility's own organisational boundaries. Proportionate risk management processes and structures provide oversight and assurance, whilst allowing a focus on the tangible business value that comes from managing strategic risks well

Guidelines for the Use of Unmanned Aerial Systems in Flood Emergency Response

There is increasing interest in using Unmanned Aircraft Systems (UAS) in flood risk management activities including in response to flood events. However, there is little evidence that they are used in a structured and strategic manner to best effect. An effective response to flooding is essential if lives are to be saved and suffering alleviated. This study evaluates how UAS can be used in the preparation for and response to flood emergencies and develops guidelines for their deployment before, during and after a flood event. A comprehensive literature review and interviews, with people with practical experience of flood risk management, compared the current organizational and operational structures for flood emergency response in both England and India, and developed a deployment analysis matrix of existing UAS applications. An online survey was carried out in England to assess how the technology could be further developed to meet flood emergency response needs. The deployment analysis matrix has the potential to be translated into an Indian context and other countries. Those organizations responsible for overseeing flood risk management activities including the response to flooding events will have to keep abreast of the rapid technological advances in UAS if they are to be used to best effect

Towards a transferable UAV-based framework for river hydromorphological characterization

The multiple protocols that have been developed to characterize river hydromorphology, partly in response to legislative drivers such as the European Union Water Framework Directive (EU WFD), make the comparison of results obtained in different countries challenging. Recent studies have analyzed the comparability of existing methods, with remote sensing based approaches being proposed as a potential means of harmonizing hydromorphological characterization protocols. However, the resolution achieved by remote sensing products may not be sufficient to assess some of the key hydromorphological features that are required to allow an accurate characterization. Methodologies based on high resolution aerial photography taken from Unmanned Aerial Vehicles (UAVs) have been proposed by several authors as potential approaches to overcome these limitations. Here, we explore the applicability of an existing UAV based framework for hydromorphological characterization to three different fluvial settings representing some of the distinct ecoregions defined by the WFD geographical intercalibration groups (GIGs). The framework is based on the automated recognition of hydromorphological features via tested and validated Artificial Neural Networks (ANNs). Results show that the framework is transferable to the Central-Baltic and Mediterranean GIGs with accuracies in feature identification above 70%. Accuracies of 50% are achieved when the framework is implemented in the Very Large Rivers GIG. The framework successfully identified vegetation, deep water, shallow water, riffles, side bars and shadows for the majority of the reaches. However, further algorithm development is required to ensure a wider range of features (e.g., chutes, structures and erosion) are accurately identified. This study also highlights the need to develop an objective and fit for purpose hydromorphological characterization framework to be adopted within all EU member states to facilitate comparison of results