Title: LIMNADES Database Demonstration

Presenter: Adam Varley, University of Stirling, Scotland

Date: November 12, 2020 2pm UTC

Abstract  – This will be a hands-on Demonstration of the Revamped LIMNADES Database. The LIMNADES (Lake Bio-optical Measurements and Matchup Date for Remote Sensing) data repository was a concept formed during the GloboLakes research project, which ended in 2018. The database is still maintained at the University of Stirling and poised to become a preferred data repository for inland water quality Calibration/Validation data.  The purpose of the LIMNADES project is to provide a centralised database of ground bio-optical measurements of worldwide lakes through voluntary cooperation across the international scientific community.

LIMNADES is open to new ideas and developing data avenues, such as the collection of citizen science data, but it currently provides a repository for:

1. 1. 1. Inherent and apparent optical property datasets and associated water constituent measurements;
      2. In-situ water constituent measurements for satellite validation.

Speaker Bio – Dr. Varley is the LIMNADES Database Manager.  He has a general background in environmental sciences, with a first class undergraduate degree in environmental chemistry. During his thesis he was introduced to the field of environmental radioactivity that would unwittingly form the basis of my career. His subsequent PhD in environmental radioactivity changed my focus more towards the physical/computational sciences and remote detection of radioactive sources. The objective of his PhD was to develop methods to process gamma-ray spectrometry data to estimate the activity and buried depth of radioactive sources. The data processing element relied heavily on Machine Learning techniques. The developed method was used to characterise radioactive contamination at sites contaminated with 226Ra and 137Cs.  His current research is dedicated to developing and implemented detection system for the Environmental Radioactivity Lab here at Stirling. This involves using gamma-ray spectrometry units on a number of platforms such as carbourne and handheld systems.  Another research area  is the use large volume detectors to estimate the risk posed by plough-induced soil erosion at archaeological sites. This work is a component of the larger European project called the CLIMA (Cultural Landscape risk Identification, Management and Assessment) project, which aims to protect ancient monuments and subsurface archaeological  structures.   

Video

Title: What environmental factors influence the concentration of fecal indicator bacteria in groundwater? Insights from Uganda and Bangladesh 

Date: October 29, 2020  2pm UTC:

Abstract:

While 2.2 billion people do not have safely-managed water services, Sustainable Goal 6.1 

calls for universal access to safe water by 2030. Water Quality information is critical to guide 

decision on sources protection or treatment approaches. Insufficient human and financial 

resources in low-income countries make the monitoring of all water supplies nearly 

impossible. Understanding the primary factors that contribute to microbial water quality 

degradation could help identify risk-prone water supplies and may therefore be an 

alternative to systematic monitoring.  

 

This study combines satellite, census and hydrological data with 5013 secondary 

measurements of groundwater quality in Uganda and Bangladesh. We first developed a 

conceptual framework representing potential risk factors to microbial groundwater quality 

and their interactions. We considered factors associated with human activities (proximity to 

cities, population density, land cover, livestock density and domestic animals), climate and 

hydrogeology (temperature, precipitation, runoff, soil type, flooding and water table depth), 

non-anthropogenic sources of contamination (wildlife feces, environmental reservoirs of 

fecal indicator bacteria), as well as water and sanitation infrastructure. We collected 

satellite-derived geospatial datasets for seven of the thirteen risk factors listed in the 

conceptual framework: temperature, precipitation, runoff, population density, land cover, 

livestock density, and time to city.  We used binomial and logistic regression to quantify 

associations between these factors and concentrations of fecal indicator bacteria in 

groundwater. 

 

In Uganda, we found that microbial contamination was both more frequent and higher in 

areas with denser population (p<0.001; RC=1.28; OR=1.27), higher runoff (p<0.001; RC=1.22; 

OR=1.37), higher cropland coverage (p=0.05; RC=1.20; OR=1.47), shorter time to city 

(p<0.001; RC=0.69; OR=0.66), and lower forest coverage (p<0.001; RC=0.83, OR=0.70). 

Microbial contamination was also more likely in areas with higher precipitation (p<0.001; 

OR=1.14) and higher livestock density (p<0.001; OR=1.17). In Bangladesh, microbial 

contamination was both more frequent and higher in areas with higher livestock density 

(p<0.001; RC=1.46; p=0.05; OR=1.11), higher forest coverage (p<0.001; RC=1.28; OR=1.23), 

higher precipitation (p<0.001; RC=1.27; 0R=1.44) and lower cropland coverage (p<0.001; 

RC=0.75; OR=0.80). In addition, contamination levels were higher in areas with higher 

temperatures (p<0.001; RC= 2.14), lower artificial land cover (p<0.001, RC=0.82) and shorter 

time to city (p<0.001; RC=0.79). These results suggest that anthropogenic activities are a 

good indicator of microbial groundwater contamination in Uganda, but not as clearly in 

Bangladesh, where forest coverage and only some indicators of anthropogenic activities 

Title: A Virtual Geostationary Ocean Color Sensor to Analyze the Coastal Optical Variability

Presenter: Marco Bracaglia , CNR

Date: September 17, 2020 2pm UTC

Abstract: in the coastal environment the optical properties can vary on temporal scales that are shorter than the near-polar orbiting satellite temporal resolution (~1 image per day), which does not allow capturing most of the coastal optical variability. The objective of this work is to fill the gap between the near-polar orbiting and geostationary sensor temporal resolutions, as the latter sensors provide multiple images of the same basin during the same day. To do that, a Level 3 hyper-temporal analysis-ready Ocean Color (OC) dataset, named Virtual Geostationary Ocean Color Sensor (VGOCS), has been created. This dataset contains the observations acquired over the North Adriatic Sea by the currently functioning near-polar orbiting sensors, allowing approaching the geostationary sensor temporal resolution. The problem in using data from different sensors is that they are characterized by different uncertainty sources that can introduce artifacts between different satellite images. Hence, the sensors have different spatial and spectral resolutions, their calibration procedures can have different accuracies, and their Level 2 data can be retrieved using different processing chains. Such differences were reduced here by adjusting the satellite data with a multi-linear regression algorithm that exploits the Fiducial Reference Measurements data stream of the AERONET-OC water-leaving radiance acquired at the Acqua Alta Oceanographic Tower, located in the Gulf of Venice. This work aims to prove the suitability of VGOCS in analyzing the coastal optical variability, presenting the improvement brought by the adjustment on the quality of the satellite data, the VGOCS spatial and temporal coverage, and the inter-sensor differences. Hence, the adjustment will strongly increase the agreement between the satellite and in situ data and between data from different near-polar orbiting OC imagers; moreover, the adjustment will make available data traditionally masked in the standard processing chains, increasing the VGOCS spatial and temporal coverage, fundamental to analyze the coastal optical variability. Finally, the fulfillment by VGOCS of the three conditions for a hyper-temporal dataset will be demonstrated in this work.

Biography: Dr. Marco Bracaglia graduated in Physics on 27/05/2016 at the University of Rome Tor Vergata. He attended a Ph.D. course in Environmental Phenomena and Risks at the Parthenope University of Naples and the CNR-ISMAR of Rome Tor Vergata. He completed the Ph.D. with the dissertation of its thesis “A Virtual Geostationary Ocean Colour Sensor to observe short term variations in particulate matter in the coastal environment” on 21/05/2020.  He is currently a research fellow at the CNR-ISMAR in Rome Tor Vergata and technical manager of the Ocean Colour Thematic Assembly Center (OC-TAC) in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). His scientific interests are Ocean Color, remote sensing, bio-optical dynamics in optically complex waters, data processing, calibration and validation of Ocean Color satellite data.

Video      and      Chatlog

Title: Spectral enhancements with contra-bands: A case study of the OLI/Landsat 8 orange contra-band and its application for inland water remote sensing.

Presenter: Alexander Castagna, Department of Biology, Ghent University

Date: June 18, 2020, 2pm UTC

Title: Observing Coastal Ocean Processes from Space at Hourly Frequency with GLIMR:  NASA’s 5th Earth Venture Instrument

Presenter: Dr. Joe Salisbury, University of New Hampshire

Date: May 21, 2020, 2pm UTC

Abstract: GLIMR is hyperspectral radiometer that will be launched in geostationary orbit to study coastal ecosystems that are under pressure from population growth and changing climate.  Our primary science centers on two questions: 1) How do physical processes that vary at timescales from hours to days impact the rates and fluxes of materials within and between aquatic coastal ecosystems? and 2) How do fluxes and rates within and between aquatic coastal ecosystems affect the formation, magnitude and trajectory of harmful algal blooms (HABS) and impact ecosystem and human health? To help address these questions, GLIMR will collect 141 bands of data in the visible to near infra-red (350-1020nm) with ~hourly coverage in our primary region of interest, the Gulf of Mexico.  This high-density 4-dimensional data stream, (U, V, time, hyperspectral) will require creative new combinations of in-water data and advanced numerical methodologies in order to maximize the science value. We will present an overview of the science, instrument capabilities and data processing, as well as ideas on how advanced in-water assets and processing solutions could benefit the GLIMR mission.

Speaker Bio: Dr. Salisbury’s interests focus on the biogeochemistry and ecology of coastal regions, particularly those influenced by riverine processes. He is presently working on two strands of research. The first seeks to characterize distributions of carbon dioxide, air-sea carbon exchange, productivity and acid stress in freshwater-influenced coastal regions. The second strand involves the use of data from a variety of space-borne sensors to characterize net community productivity and carbon exchanges in coastal waters. For these projects his team uses a variety of remotely sensed data including ocean color, sea surface temperature and microwave radiometry. He is currently the principal investigator of a NASA satellite mission called the Geostationary Littoral Imaging and Monitoring Radiometer, scheduled to launch in 2026.  This sensor will use ocean color to study coastal ecosystems.  He is also co-PI of the NASA scoping study, Arctic-COLORS which seeks to implement a series of campaigns to the coastal Arctic to explore land to ocean interactions. Our UNH Coastal Carbon Group maintains several autonomous data collecting assets in the Gulf of Maine and is active in cruise campaigns throughout the western Atlantic.

Video  Chatlog Publications (coming soon!)

Title: Arctic COLORS : Arctic-COastal Land Ocean inteRactionS

Presenters: Dr. Peter Hernes, University of California-Davis

Date: May 8, 2020, 2pm UTC/10am EDT (New York)

Abstract: Arctic-COLORS is a proposed NASA field campaign that is expected to start in 3-6 years and investigates the impact of changing terrestrial fluxes of materials on near-coastal ocean biogeochemistry in the study region from the Yukon River to the Mackenzie River. In preparation for Arctic-COLORS, NASA is funding preliminary projects to collect data to characterize the current state of the coastal Arctic that will be invaluable for measuring change when Arctic-COLORS comes online, and to test fundamental ideas about the transfer of riverine materials to the coastal zone that will help to shape the Arctic-COLORS science plan. This talk will primarily focus on one of those pre-Arctic-COLORS projects, in which we set out to 1) measure current conditions primarily in the Yukon River delta but also collected samples on the north slope of Alaska, 2) characterize the transformation of riverine materials from the head of tides through the delta and out to salinity, and 3) refine and develop algorithms for local Arctic water quality parameters and concentrations from remote sensing, with the ultimate goal of using those algorithms for hindcasting with existing remote sensing data. In addition to a multitude of optical measurements, our dataset also includes dissolved and particulate organic carbon, lignin, chlorophyll, salinity mixing experiments, microbial and photochemical oxidations experiments, and eventually high resolution mass spectrometry data. Understanding how river materials are transformed will allow Arctic-COLORS to take full advantage of long term datasets from programs like the Arctic Great Rivers Observatory.

Speaker Bio: Peter Hernes uses biomarkers (primarily lignin) in conjunction with several other bulk measurements to characterize sources, processes, and fates of organic matter in rivers out to the coastal ocean. In particular, he is interested in how river chemistry maps back to land use, landscape sources and processes, and constant change. He received his masters and PhD in chemical oceanography at the University of Washington in Seattle and did postdoctoral work at the University of South Carolina in Columbia before landing at the University of California – Davis is 2002, where he is a Professor of Hydrology and Aqueous Geochemist.

Video (Webinar Starts at 23mins 30 secs into the recording) Chatlog

Title: Airborne drone-based monitoring of the water quality

Presenters: Dr. Liesbeth De Keukelaere and Mr. Robrecht Moelans, VITO

Date: March 26, 2020, 2pm UTC

Abstract:  Recent advances in Remotely Piloted Aircraft Systems (RPAS), or airborne drones, have created an additional monitoring platform that provides an opportunity to capture spatial, spectral and temporal information that could benefit a wide range of applications. This with a relative small investment, especially compared to the cost of manned airborne systems or satellite missions. However, the conversion of the raw data into physically meaningful values, like water-leaving reflectance, turbidity or chlorophyll concentrations is not so straightforward. This presentation will show the challenges faced when using airborne drone data over water surfaces through experiences from different field campaigns, organized in the framework of the MONOCLE H2020 research and innovation project.

Speaker Bios – Dr. De Keukelaere: A young researcher with a Master degree in Bio-Science Engineering, Liesbeth De Keukelaere’s focus is on soil, water and Earth Observation. During her first year after graduation, Liesbeth worked on spectral unmixing techniques to distinguish different tree species within one pixel. She then shifted her attention to water applications, investigating remote sensing’s potential for water quality monitoring in inland, coastal and transitional waters. In the summer of 2016 she was selected to participate with the IOCCG Summer Lecture Series: Frontiers in Ocean Optics and Ocean Colour Science, and in autumn 2016 she followed an introductory course on Aquaculture at Odisee Hogeschool (Belgium).  During her career she’s been involved in multiple projects including two FP7 projects – INFORM (Improved monitoring and forecasting of ecological status of European Inland waters by combining Future earth ObseRvation data and Models) and HIGHROC (High Spatial and Temporal Resolution Ocean Colour coastal water products and services) – Belspo funded projects including REMEDY (Remote Monitoring of tropical Ecosystem Dynamics) and DRONESED (Dronese-based Sediment Mapping for Dredging Operations) as well as the ESA PV-LAC project (Advanced Land, Aerosol and Coastal products for Proba-V).

Mr. Robrecht Moelans: Robrecht is working with VITO as R&D Professional in processing drone and satellite images for water & coastal applications. Before VITO, Robrecht worked as R&D Project Manager with G-tec in Liège, Belgium and as Operational Superintendent (expat) with dredging company Jan De Nul. He is holding a Master’s degree in Mining and Geotechnical Engineering from Katholieke Universiteit Leuven.

Video     Chat Transcript      Nechad et al (2009) TSM methodology

Sarantuyaa coordinates the UNESCO-IHP’s International Initiative on Water Quality (IIWQ) and leads IHP activities on water quality and wastewater. She has developed several UNESCO projects on emerging issues and innovative approaches to water quality such as: satellite-based water quality monitoring; emerging pollutants; nature-based solutions to water quality; and climate change and water quality. She has developed the concept of the satellite-based UNESCO World Water Quality Portal to enhance open access water quality data at the global level.

Between 2007 and 2015, Sarantuyaa was responsible for UNESCO-IHP’s urban water activities, implemented IHP projects on integrated urban water management, and coordinated the publication of UNESCO Urban Water Series, comprising eight major books. Sarantuyaa has published numerous research and policy publications (books, research journal papers, technical reports, policy reports, etc.) and has contributed as lead author of chapters in UNESCO-EOLLS Encyclopedia and United Nations World Water Development Reports.

Video (webinar starts at 3 minute mark) and Chat 

Recording:         Video       Q&A Chatfile