Offshore oil seepage visible from space : a Synthetic Aperture Radar (SAR) based automatic detection, mapping and quantification system

Offshore oil seepage is believed to be the largest source of marine oil, yet very few of their locations and seepage fluxes have been discovered and reported. Natural oil seep sites are important as they serve as potential energy sources and because they are hosts to a very varied marine ecosystem. These seeps can also be associated with gas hydrates and methane emissions and hence, locating natural oil seeps can provide locations where the sources of greenhouse gases could be studied and quantified. A quantification of the amount of crude oil released from natural oil seeps is important as it can be used to set a background against which the excess anthropogenic sources of marine oil can be checked. This will provide an estimate of the 'contamination' of marine waters from anthropogenic sources. Until the onset of remote sensing techniques, field measurements and techniques like hydroacoustic measurements or piston core analysis were used to obtain knowledge about the geological settings of the seeps. The remote sensing techniques either involved manual or semi-automatic image analysis. An automatic algorithm that could quantitatively and qualitatively estimate the locations of oil seeps around the world would reduce the time and costs involved by a considerable margin. Synthetic Aperture Radar (SAR) sensors provide an illumination and weather independent source of ocean images that can be used to detect offshore oil seeps. Oil slicks on the ocean surface dampen the small wind driven waves present on the ocean surface and appear darker against the brighter ocean surface. They can, hence, be detected in SAR image. With the launch of the latest Sentinel-1 satellite aimed at providing free SAR data, an algorithm that detects oil slicks and estimates seep location is very beneficial. The global data coverage and the reduction of processing times for the large amounts of SAR data would be unmatchable. The aim of this thesis was to create such an algorithm that could automatically detect oil slicks in SAR images, map the location of the estimated oil seeps and quantify their seepage fluxes. The thesis consists of three studies that are compiled into one of more manuscripts that are published, accepted for publication or ready for submission. The first study of this thesis involves the creation of the Automatic Seep Location Estimator (ASLE) which detects oil slicks in marine SAR images and estimates offshore oil seepage sites. This, the first fully automatic oil seep location estimation algorithm, has been implemented in the programming language Python and has been tested and validated on ENVISAT images of the Black Sea. The second study reported in this thesis focuses on the optimisation of the created ASLE and comparison of the ASLE with other existing algorithms. It also describes the efficiency of the ASLE with respect to other existing algorithms and the results show that the ASLE can successfully detect seeps of active seepages. The third study aimed to provide the status of the offshore seepage in the southern Gulf of Mexico estimated from the ASLE using SAR images from ENVISAT and RADARSAT-1. The ASLE was used to detect natural oil slicks from SAR images and estimate the locations of feeding seeps. The estimated seep locations and the slicks contributing to these estimations were then analysed to quantify their seepage fluxes and rates. The three case studies illustrate that an automatic offshore seepage detection and estimation system such as the Automatic Seep Location Estimator (ASLE) is very beneficial in order to locate global oil seeps and estimate global seepage fluxes. It provides a technique to detect offshore seeps and their seepage fluxes in a fast and highly efficient manner by using Synthetic Aperture Radar images. This allows global accessibility of offshore oil seepage sites. The availability of large amounts of historic SAR datasets, the presence of 5 active SAR satellites and the latest launch of the European Space Agency satellite Sentinel-1, which provides free data, shows that there is no shortage in the availability of SAR data. The result of the work done in this thesis provides a means to utilise this large SAR dataset for the purpose of offshore oil seepage detection and offshore seepage related geophysical applications. The created system will be an important tool in the future not just to estimate offshore seepage in local seas but in global oceans that are otherwise challenging for field analysis

Degradation of Methylene Blue Using Microplasma Discharge – A Relative Study with Photodegradation

Large-scale production and application of synthetic dyes have become a matter of concern as it is a major factor responsible for environmental pollution. Most dyeing effluents are discharged into water bodies and lands without being treated, which ultimately pollutes the groundwater making it unfit for consumption. The present study explains the degradation of one of such synthetic dyes Methylene blue (MB), using non-thermal Microplasma treatment. The aqueous solution of MB was treated with an array of air microplasma discharge at atmospheric pressure. Different concentrations (10 ppm, 20 ppm) of MB solution were treated for various treatment time and chemical parameters like pH, electrical conductivity, total dissolved solids and salinity was measured. The degradation percentage reached 100% in 15 min of treatment for 10 ppm MB solution, and 20 min of treatment for 20 ppm MB solution indicated by the color change from blue to a clear solution. The reactive oxygen species (ROS) and reactive nitrogen species (RNS) formed during the microplasma treatment are responsible for MB degradation. Same volume of MB solution was irradiated by direct sunlight for photodegradation and was found to degrade the solution of 10 ppm by 96% and 20 ppm by 93% in 10 hours of treatment. Experimental results indicated that microplasma treatment was effective for dye degradation, without the need for pretreatment process or chemicals

Marine Ölaustritte vom Weltraum aus gesehen : ein automatische System zur Detektierung, Kartierung und Quantifizierung, basierend auf Radar mit Synthetischer Apertur (SAR)

Offshore oil seepage is believed to be the largest source of marine oil, yet very few of their locations and seepage fluxes have been discovered and reported. Natural oil seep sites are important as they serve as potential energy sources and because they are hosts to a very varied marine ecosystem. These seeps can also be associated with gas hydrates and methane emissions and hence, locating natural oil seeps can provide locations where the sources of greenhouse gases could be studied and quantified. A quantification of the amount of crude oil released from natural oil seeps is important as it can be used to set a background against which the excess anthropogenic sources of marine oil can be checked. This will provide an estimate of the 'contamination' of marine waters from anthropogenic sources. Until the onset of remote sensing techniques, field measurements and techniques like hydroacoustic measurements or piston core analysis were used to obtain knowledge about the geological settings of the seeps. The remote sensing techniques either involved manual or semi-automatic image analysis. An automatic algorithm that could quantitatively and qualitatively estimate the locations of oil seeps around the world would reduce the time and costs involved by a considerable margin. Synthetic Aperture Radar (SAR) sensors provide an illumination and weather independent source of ocean images that can be used to detect offshore oil seeps. Oil slicks on the ocean surface dampen the small wind driven waves present on the ocean surface and appear darker against the brighter ocean surface. They can, hence, be detected in SAR image. With the launch of the latest Sentinel-1 satellite aimed at providing free SAR data, an algorithm that detects oil slicks and estimates seep location is very beneficial. The global data coverage and the reduction of processing times for the large amounts of SAR data would be unmatchable. The aim of this thesis was to create such an algorithm that could automatically detect oil slicks in SAR images, map the location of the estimated oil seeps and quantify their seepage fluxes. The thesis consists of three studies that are compiled into one of more manuscripts that are published, accepted for publication or ready for submission. The first study of this thesis involves the creation of the Automatic Seep Location Estimator (ASLE) which detects oil slicks in marine SAR images and estimates offshore oil seepage sites. This, the first fully automatic oil seep location estimation algorithm, has been implemented in the programming language Python and has been tested and validated on ENVISAT images of the Black Sea. The second study reported in this thesis focuses on the optimisation of the created ASLE and comparison of the ASLE with other existing algorithms. It also describes the efficiency of the ASLE with respect to other existing algorithms and the results show that the ASLE can successfully detect seeps of active seepages. The third study aimed to provide the status of the offshore seepage in the southern Gulf of Mexico estimated from the ASLE using SAR images from ENVISAT and RADARSAT-1. The ASLE was used to detect natural oil slicks from SAR images and estimate the locations of feeding seeps. The estimated seep locations and the slicks contributing to these estimations were then analysed to quantify their seepage fluxes and rates. The three case studies illustrate that an automatic offshore seepage detection and estimation system such as the Automatic Seep Location Estimator (ASLE) is very beneficial in order to locate global oil seeps and estimate global seepage fluxes. It provides a technique to detect offshore seeps and their seepage fluxes in a fast and highly efficient manner by using Synthetic Aperture Radar images. This allows global accessibility of offshore oil seepage sites. The availability of large amounts of historic SAR datasets, the presence of 5 active SAR satellites and the latest launch of the European Space Agency satellite Sentinel-1, which provides free data, shows that there is no shortage in the availability of SAR data. The result of the work done in this thesis provides a means to utilise this large SAR dataset for the purpose of offshore oil seepage detection and offshore seepage related geophysical applications. The created system will be an important tool in the future not just to estimate offshore seepage in local seas but in global oceans that are otherwise challenging for field analysis

The Haiti 2010 Earthquake: A 3D deformation analysis

On January 12,2010 at 2153 GMT, a magnitude 7.0 earthquake struck the region of Haiti with its hypo center at a distance of25 km from the capital city of Port-au-Prince. This disaster killed about 316,000, injured 300,000 and displaced another 1.3 million people in and around Port-au-Prince. The earthquake is believed to have occurred along the Enriquillo-Plantain Garden fault zone, which is one of the two main strike-slip faults inferred to accommodate about 7-10 mm/yr relative motion between the Caribbean and the North American Plates. In order to analyse the deformation caused by the earthquake, TerraSAR-X and ALOS-PALSAR data, was processed using Differential Interferometry and Incoherent cross-correlation methods. 3D inversion was then performed on the incoherent cross-correlation results to get the deformation in three dimensions

Haiti 2010 Earthquake: A 3D Deformation Analysis

On January 12, 2010 at 2153 GMT, a magnitude 7.0 earthquake struck the region of Haiti with its hypocenter at a distance of 25 km from the capital city of Port-au-Prince. This disaster killed about 316,000, injured 300,000 and displaced another 1.3 million people around Port-au-Prince. The earthquake occurred along the Enriquillo- Plantain Garden fault zone, which is one of the two main strike-slip faults inferred to accommodate about 7-10 mm yr-1 relative motion between the Caribbean and the North American Plates. In order to analyse the deformation caused by the earthquake, TerraSAR-X and ALOS-PALSAR data, was processed using Differential Interferometry and Incoherent cross-correlation methods

Aliasing of the Indian Ocean externally-forced warming spatial pattern by internal climate variability

International audienceCoupled Model Intercomparison Project (CMIP5) models project an inhomogeneous anthropogenic surface warming of the Indian Ocean by the end of the 21st century, with strongest warming in the Arabian Sea and Western equatorial Indian Ocean. Previous studies have warned that this “Indian Ocean Dipole (IOD)-like” warming pattern could yield more Arabian Sea cyclones, more extreme IOD events and decrease monsoonal rains. Here we show that CMIP5 models also produce an “IOD-like” pattern over the 1871–2016 period, in broad agreement with observations. Single-models ensemble simulations however indicate a strong aliasing of the warming pattern “signal” by the internal climate variability “noise” over that period. While the average Indian Ocean warming emerges around 1950 in CMIP5 and observations, regional contrasts are more difficult to detect. The only detectable signal by 2016 in CMIP5 is a stronger Arabian Sea than Bay of Bengal warming in > 80% of the models, which is not detected in HadSST3 observations. Conversely, observations already detect a stronger Northern than Southern Indian ocean warming, while this signal only emerges by ~ 2060 in > 80% of the models. Subsampling observations to only retain the most accurate values however indicate that this observed signal most likely results from sampling issues in the Southern hemisphere. In light of this large aliasing by internal climate variability and observational uncertainties, the broad agreement between CMIP5 and observations over 1871–2016 may be largely coincidental. Overall, these results call for extreme caution when interpreting spatial patterns of anthropogenic surface warming

Discovering Inclusivity in Remote Sensing: Leaving No One Behind

Innovative and beneficial science stems from diverse teams and authorships that are inclusive of many perspectives. In this paper, we explore the status of inclusivity in remote sensing academic publishing, using an audit of peer-reviewed journal editorial board composition. Our findings demonstrate diversity deficiency in gender and country of residence, limiting the majority of editors to men residing in four countries. We also examine the many challenges underrepresented communities within our field face, such as implicit bias, harsher reviews, and fewer citations. We assert that in the field of remote sensing, the gatekeepers are not representative of the global society and this lack of representation restricts what research is valued and published, and ultimately who becomes successful. We present an action plan to help make the field of remote sensing more diverse and inclusive and urge every individual to consider their role as editor, author, reviewer, or reader. We believe that each of us have a choice to continue to align with a journal/institution/society that is representative of the dynamic state of our field and its people, ensuring that no one is left behind while discovering all the fascinating possibilities in remote sensing.</jats:p

Insights on the astringency of non alcoholic beverages: fruit, vegetable & planation based perspective

Sensory parameters of food and beverages secured much importance with mounting changes in diet preferences. The taste and flavour of these food groups are largely affected by astringency which in turn influence the sensory experience. Derived from Latin, astringency deals with the sensation of extreme dryness, roughness or puckering involving the secretions of salivary glands. Accountable astringent clusters majorly revolving around the presence of tannins in food trailed by the incidence of salts of multivalent cations like Al, Zn, Cr etc, and dehydrating agents like mineral acids, alcohol etc. To augment the sensory feeling and to broaden the marketing possibilities related to beverages, it is important to accomplish techniques to reduce or control the development of these sensations. De-astringency practices performed in foods can be broadly catalogued into thermal and non-thermal treatments. While the former majorly included hot water, steam and microwave treatment, the latter concentrated mainly on innovative techniques like high hydrostatic pressure, pulsed electric field, thermo-sonication, ultrasonication etc. The effectiveness of these procedures is largely dependent on the mechanisms associated with the development of astringency feelings in foods. Understanding the mechanism underlying astringency sensation is still in a nascent stage and needs more exploration to state the explicit reason behind the process. This review chiefly covers the explanation of astringency, the mechanism involved and the different de-astringency techniques as per the prevailing astringency models

Challenges faced by state and society in providing care to homeless mentally Ill Patients: Know the unknown project

Background: Homeless mentally ill (HMI) patients pose a major problem in our society. There are no specific, focused studies to understand the complex needs and the challenges faced by state and society in providing care of HMI patients in India. Objectives: This study was planned to understand the challenges faced by state and society in providing care to HMI. Materials and Methods: We performed a retrospective chart review of “HMI” patients from January 1, 2002, to December 31, 2015, who were admitted to the Department of Psychiatry at National Institute of Mental Health and Neuro Sciences, Bengaluru, India. Pathway to care and reintegration outcome characteristics were analyzed using descriptive statistics. Results: In our study, among 78 HMI patients admitted, police 32 (41%), public 32 (41%), and nongovernmental organizations (NGOs) 14 (18%) were the first contacts who found HMI patients. In the 15 weeks of mean duration of inpatient care, 40 (51.3%) were reintegrated into the family through a multidisciplinary approach. However public, NGO, Clinicians had multiple challenges in admission, treatment services, rehabilitation, and aftercare of HMI patients. Conclusion: Holistic care and services for HMI patients are challenging and have multiple hurdles with the existing infrastructure in India. Better care might be possible with collaborative, multidisciplinary approach with NGOs, Rehabilitation centers, local police, judiciary, and psychiatric facilities. Mental Health Care Act 2017 has addressed above few challenges making admission procedure simpler, administering free treatment, involving police officers in the identification of HMI, admission to hospital, tracing HMI, and reintegration with the family