Remote Sensing Of Suspended Sediment

A remote sensing near infrared suspended sediment algorithm is developed from first principles and applied to Compact Airborne Spectrographic Imagery (CASI) data flown over the Humber Estuary. Laboratory measurements were used as the basis for the algorithm development, with the resulting spectra indicating that the ideal wavelength for a suspended sediment algorithm is the near infrared. The resulting algorithm took the form of a waveband ratio which was subsequently validated with a semi-analytical water optics model based on the absorption/scattering properties of the optically active constituents. The model was then used to derive a global water-leaving radiance algorithm, which is independent of the sediment type. The algorithm was applied to the CASI data collected during August and September 1993, and the resulting SPM maps were compared with contemporaneous in-situ measurements. The in-situ measurements include calculations of the diffuse attenuation coefficient (Kd), which was correlated with the SPM concentration. Further developments to the algorithm through the use of an atmospheric correction are outlined.Plymouth Marine Laborator

Complement Factor H Related Proteins and their Biological Role During Bacterial Infection

Neisseria meningitidis is a major cause of meningitis and sepsis worldwide despite available polysaccharide and protein vaccines. Individuals with rare defects in the terminal complement pathway are susceptible to meningococcal disease but further genetic factors that contribute to disease susceptibility are less well understood. A genome wide association study has linked polymorphisms in the Complement Factor H (CFH) locus with meningococcal disease in the general population. CFH is a negative regulator of the alternative complement pathway whereas CFH-related proteins (CFHR), encoded in the CFH locus, act as antagonists of CFH. Investigations of the biological role of the CFHRs have been hampered by lack of reagents, therefore a panel of specific monoclonal antibody reagents to CFHR2-5 were generated and characterised. Previously, N. meningitidis has been shown to bind CFH via a surface exposed lipoprotein, factor H binding protein (fHbp), at high affinity. This study demonstrates that CFHR3 binds to the bacterial surface in a fHbp dependent-manner. Furthermore, CFHR3 competes with CFH for binding to fHbp. Bound CFHR3 increases susceptibility of N. meningitidis to complement-mediated lysis which was dependent on the sequence of the fHbp variant. The ability of N. meningitidis to evade the host immune system is likely to be determined by the relative levels of CFH and CFHR3 on the bacterial surface, providing a molecular mechanism for how variation in cfhr3 may predispose individuals to meningococcal disease. Furthermore this work demonstrates that Neisseria cinerea, which colonises the respiratory mucosa, expresses fHbp and binds CFH at similar affinities as meningococcal fHbp promoting bacterial survival in serum. The recently developed meningococcal vaccine, Bexsero®, includes fHbp as an antigen and antibodies elicited by Bexsero® are bactericidal against N. cinerea suggesting that the introduction of this vaccine could affect nasopharyngeal carriage of N. cinerea

Detection of potentially gas flaring related pollution on vegetation cover and its health using remotely sensed data in the Niger delta, Nigeria

Detection of potentially gas flaring-related pollution on vegetation cover using remotely sensed data at 11 flaring sites in Rivers State, Nigeria is the emphasis of this research. 21 Landsat 7 Enhanced Thematic Mapper Plus (ETM ), and 4 Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI-TIRS) data dated from 21/04/2000 to 05/02/2022 with  3  cloud cover were used. Normalized Differential Vegetation Index (NDVI) was retrieved from corrected Landsat 7 bands (1-4), and Landsat 8 bands (2-5). Corrected thermal band was used for the computation of Land Surface Temperature (LST). Change in NDVI (δNDVI450-60)m and LST ( δLST60-450m) were computed. NDVI values at 60 m from the stack show that as the year increases, NDVI values around the stack reduces to almost zero. Linear regression analysis was considered for (δ NDVI450-60)mN against ( δNDVI450-60)mE, (δNDVI450-60)mN against (δNDVI450-60)mS, and (δNDVI450-60)mN against (δNDVI450-60)mW. Only (δNDVI450-60)mN against (δNDVI450-60)mW give statistically significant results at 99 % confidence level (p-value  0.0016). (δNDVI450-60)mN,E,S,W against (δLST60-450)mN,E,S,W were considered and results show positive correlation but statistically insignificant. Based on the results of this research, it can be concluded that flaring-related pollution can be detected on vegetation cover using Landsat 7 and Landsat 8 data in the Niger Delta

MERIS phytoplankton time series products from the SW Iberian Peninsula (Sagres) using seasonal-trend decomposition based on loess

The European Space Agency has acquired 10 years of data on the temporal and spatial distribution of phytoplankton biomass from the MEdium Resolution Imaging Spectrometer (MERIS) sensor for ocean color. The phytoplankton biomass was estimated with the MERIS product Algal Pigment Index 1 (API 1). Seasonal-Trend decomposition of time series based on Loess (STL) identified the temporal variability of the dynamical features in the MERIS products for water leaving reflectance ((w)()) and API 1. The advantages of STL is that it can identify seasonal components changing over time, it is responsive to nonlinear trends, and it is robust in the presence of outliers. One of the novelties in this study is the development and the implementation of an automatic procedure, stl.fit(), that searches the best data modeling by varying the values of the smoothing parameters, and by selecting the model with the lowest error measure. This procedure was applied to 10 years of monthly time series from Sagres in the Southwestern Iberian Peninsula at three Stations, 2, 10 and 18 km from the shore. Decomposing the MERIS products into seasonal, trend and irregular components with stl.fit(), the (w)() indicated dominance of the seasonal and irregular components while API 1 was mainly dominated by the seasonal component, with an increasing effect from inshore to offshore. A comparison of the seasonal components between the (w)() and the API 1 product, showed that the variations decrease along this time period due to the changes in phytoplankton functional types. Furthermore, inter-annual seasonal variation for API 1 showed the influence of upwelling events and in which month of the year these occur at each of the three Sagres stations. The stl.fit() is a good tool for any remote sensing study of time series, particularly those addressing inter-annual variations. This procedure will be made available in R software

An assessment of high touch object cleaning thoroughness using a fluorescent marker in two Australian hospitals

An Unassigned Group, An Unassigned DepartmentFull Tex

Identifying four phytoplankton functional types from space: An ecological approach

Deriving maps of phytoplankton taxa based on remote sensing data using bio-optical properties of phytoplankton alone is challenging. A more holistic approach was developed using artificial neural networks, incorporating ecological and geographical knowledge together with ocean color, bio-optical characteristics, and remotely sensed physical parameters. Results show that the combined remote sensing approach could discriminate four major phytoplankton functional types (diatoms, dinoflagellates, coccolithophores, and silicoflagellates) with an accuracy of more than 70%. Models indicate that the most important information for phytoplankton functional type discrimination is spatio-temporal information and sea surface temperature. This approach can supply data for large-scale maps of predicted phytoplankton functional types, and an example is shown

Living up to the hype of hyperspectral aquatic remote sensing: science, resources and outlook

Intensifying pressure on global aquatic resources and services due to population growth and climate change is inspiring new surveying technologies to provide science-based information in support of management and policy strategies. One area of rapid development is hyperspectral remote sensing: imaging across the full spectrum of visible and infrared light. Hyperspectral imagery contains more environmentally meaningful information than panchromatic or multispectral imagery and is poised to provide new applications relevant to society, including assessments of aquatic biodiversity, habitats, water quality, and natural and anthropogenic hazards. To aid in these advances, we provide resources relevant to hyperspectral remote sensing in terms of providing the latest reviews, databases, and software available for practitioners in the field. We highlight recent advances in sensor design, modes of deployment, and image analysis techniques that are becoming more widely available to environmental researchers and resource managers alike. Systems recently deployed on space- and airborne platforms are presented, as well as future missions and advances in unoccupied aerial systems (UAS) and autonomous in-water survey methods. These systems will greatly enhance the ability to collect interdisciplinary observations on-demand and in previously inaccessible environments. Looking forward, advances in sensor miniaturization are discussed alongside the incorporation of citizen science, moving toward open and FAIR (findable, accessible, interoperable, and reusable) data. Advances in machine learning and cloud computing allow for exploitation of the full electromagnetic spectrum, and better bridging across the larger scientific community that also includes biogeochemical modelers and climate scientists. These advances will place sophisticated remote sensing capabilities into the hands of individual users and provide on-demand imagery tailored to research and management requirements, as well as provide critical input to marine and climate forecasting systems. The next decade of hyperspectral aquatic remote sensing is on the cusp of revolutionizing the way we assess and monitor aquatic environments and detect changes relevant to global communities

Report on IOCCG Workshop Phytoplankton Composition from Space: towards a validation\ud strategy for satellite algorithms

The IOCCG-supported workshop “Phytoplankton Composition from Space: towards a validation strategy for satellite algorithms” was organized as a follow-up to the Phytoplankton Functional Types from Space splinter session, held at the International Ocean Colour Science Meeting (Germany, 2013). The specific goals of the workshop were to: 1. Provide a summary of the status of activities from relevant IOCCG working groups, the 2nd PFT intercomparison working group, PFT validation data sets and other research developments. 2. Provide a PFT validation strategy that considers the different applications of PFT products: and seeks community consensus on datasets and analysis protocols. 3. Discuss possibilities for sustaining ongoing PFT algorithm validation and intercomparison activities. The workshop included 15 talks, breakout sessions and plenary discussions. Talks covered community algorithm intercomparison activity updates, review of established and novel methods for PFT validation, validation activities for specific applications and space-agency requirements for PFT products and validation. These were followed by general discussions on (a) major recommendations for global intercomparison initiative in respect to validation, intercomparison and user’s guide; (b) developing a community consensus on which data sets for validation are optimal and which measurement and analysis protocols should be followed to support sustained validation of PFT products considering different applications; (c) the status of different validation data bases and measurement protocols for different PFT applications, and (d) engagement of the various user communities for PFT algorithms in developing PFT product specifications. From these discussions, two breakout groups provided in depth discussion and recommendations on (1) validation of current algorithms and (2) work plan to prepare for validation of future missions. Breakout group 1 provided an action list for progressing the current international community validation and intercomparison activity. Breakout group 2 provided the following recommendations towards developing a future validation strategy for satellite PFT products: 1. Establish a number of validation sites that maintain measurements of a key set of variables. 2. This set of variables should include: • Phytoplankton pigments from HPLC, phycobilins from spectrofluorometry • Phytoplankton cell counts and ID, volume / carbon estimation and imaging (e.g. from flow cytometry, FlowCam, FlowCytobot type technologies) • Inherent optical properties (e.g. absorption, backscattering, VSF) • Hyperspectral radiometry (both above and in-water) • Particle size distribution • Size-fractionated measurements of pigments and absorption • Genetic / -omics data 3. Undertake an intercomparison of methods / instruments over several years at a few sites to understand our capabilities to fully characterize the phytoplankton community. 4. Organise workshops to address the following topics: • Techniques for particle analysis, characterization and classification • Engagement with modellers and understanding end-user requirements • Data storage and management, standards for data contributors, data challenges In conclusion, the workshop was assessed to have fulfilled its goals. A follow-on meeting will be organized during the International Ocean Colour Science Meeting 2015 in San Francisco. Specific follow-on actions are listed at the end of the report

Satellite remote sensing of surface winds, waves, and currents: Where are we now?

This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields