This document summarizes Dawn Wright's presentation on how geospatial technologies can accelerate ocean impact. Geospatial provides a proven framework across many domains like ecology, hydrology, and ocean science. A global geospatial framework is emerging through collaboration between Esri, universities, the UN, NOAA, and other organizations. This framework uses techniques like machine learning, 3D modeling, and sensor networks to track issues like seagrass distribution and dissolved oxygen levels. The goal is to create a shared understanding and more sustainable ocean future through open data sharing and digital experiences.
The Perils and Promise of Environmental Data ScienceDawn Wright
Keynote address delivered in April 2019 to the Yale School of Forestry & Environmental Studies, during their annual research conference. "The mission of the Annual F&ES Research Conference is to provide a forum for research degree students and postdocs to share their original work with the F&ES community, as well as with the broader Yale and New Haven communities. After the success of last year's partnership with Yale Pathways to Science, we will again open conference attendance to local high school students and host events emphasizing research communication. Our aim is for the conference to facilitate interdisciplinary communication and collaboration both within the School and beyond the walls of Kroon."
Improving science (communication) through data visualizationZachary Labe
Creating visuals of data is an important part of our jobs as scientists. We use figures for journal publications, presentations, posters, lab group meetings, science communication, and more. In this workshop, we'll use examples from climate science to discuss a framework and network of resources available for making accessible figures. I will also share examples of what not to do and how to improve these figures moving forward.
The Perils and Promise of Environmental Data ScienceDawn Wright
Keynote address delivered in April 2019 to the Yale School of Forestry & Environmental Studies, during their annual research conference. "The mission of the Annual F&ES Research Conference is to provide a forum for research degree students and postdocs to share their original work with the F&ES community, as well as with the broader Yale and New Haven communities. After the success of last year's partnership with Yale Pathways to Science, we will again open conference attendance to local high school students and host events emphasizing research communication. Our aim is for the conference to facilitate interdisciplinary communication and collaboration both within the School and beyond the walls of Kroon."
Improving science (communication) through data visualizationZachary Labe
Creating visuals of data is an important part of our jobs as scientists. We use figures for journal publications, presentations, posters, lab group meetings, science communication, and more. In this workshop, we'll use examples from climate science to discuss a framework and network of resources available for making accessible figures. I will also share examples of what not to do and how to improve these figures moving forward.
Two way data sharing between government agencies and community groups is essential to ensure effective delivery of the Water Framework Directive and many other statutory and environmental management objectives. Achieving this will require some joined-up thinking and investment in strategic infrastructure, particularly for the community groups who aren't currently covered by the INSPIRE directive.
The Rivers Trust as the umbrella body for the rivers trusts movement are key players working towards this aim.
Presented as a 2015 Ecosystem Based Management Tools Webinar and also as a paper at the 2015 Coastal GeoTools Conference, North Charleston, SC.
The story map is a relatively new medium for sharing not only data, photos, videos, sounds, and maps, but for telling a specific and compelling story by way of that content. Story map apps provide the user with sophisticated cartographic functionality that does not require advanced training in cartography or GIS. Story maps are essentially web map applications built from web maps, which in turn are built from web-accessible data (including OGC WMS, WFS). Depending on the chosen complexity of a story map, it can be built in anywhere from a few minutes to a few days. With the beauty and utility of underlays such as the Esri Ocean Basemap, as well as a small tsunami of ocean content percolating up through a host of open data sites, there are powerful stories being told about coastal zone management, conservation, exploration and other forms of scientific field work. These stories are informing, educating, entertaining, and inspiring decision-makers on a wide variety of coastal issues. This presentation will take the audience on a small tour of a growing catalog of coastal and ocean story maps, many of which are accessible via MarineCadastre.gov and NOAA’s Digital Coast. It will also highlight the various resources available for building and deploying story maps, and discuss the utility of this medium for presenting, not just photos and videos, but more analytical results. Learn more about Story Maps at http://storymaps.esri.com.
This webinar was presented by Dawn Wright, Chief Scientist at Esri, along with Jenny Lentz, Education Specialist at the Aquarium of the Pacific. Slides here are Dawn Wright portion only.
The preliminary design of a low-cost Discovery class mission for prospecting Mars moons Phobos and Deimos is undertaken as capstone senior design class in spacecraft design. The mission is centered on a LCROSS-like mothership that carries a set of four 12U and eight 6U CubeSats. The mothership is equipped with a set of instruments for the investigation of regolith samples, similar to those with a similar functions on the Curiosity rover and the 2020 rover.
There is a small movement for change in development practices
Landscape Architect Ian McHargleads with new ideas for land planning
Understanding about the environment
Integration with environmental sciences
Addressing human adaptations to the environment
Ecological Marine Units: A 3-D Mapping of the Ocean Based on NOAA’s World Oce...Dawn Wright
This webinar to the Ecosystem Based Management Tools Network, May 17, 2017, reported progress on the Ecological Marine Units (EMU) project, a new undertaking commissioned by the Group on Earth Observations, to develop a standardized and practical global ecosystems classification and map for the oceans. The EMU is comprised of a global point mesh framework, created from 52,487,233 points from the NOAA World Ocean Atlas. Each point has x, y, z, as well as six attributes of chemical and physical oceanographic structure (temperature, salinity, dissolved oxygen, nitrate, silicate, phosphate) that are likely drivers of many ecosystem responses. We identify and map 37 environmentally distinct 3D regions (candidate ‘ecosystems’) within the water column. These units can be attributed according to their productivity, direction and velocity of currents, species abundance, global seafloor geomorphology, and more. A series of data products for open access will share the 3D point mesh and EMU clusters at the surface, bottom, and within the water column, as well as 2D and 3D web apps for exploration of the EMUs and the original World Ocean Atlas data. This webinar provided an overview of the EMU project and cover recent developments and future plans for the EMUs. Webinar recording at https://www.openchannels.org/webinars/2017/ecological-marine-units-3-d-mapping-ocean-based-noaas-world-ocean-atlas
Two way data sharing between government agencies and community groups is essential to ensure effective delivery of the Water Framework Directive and many other statutory and environmental management objectives. Achieving this will require some joined-up thinking and investment in strategic infrastructure, particularly for the community groups who aren't currently covered by the INSPIRE directive.
The Rivers Trust as the umbrella body for the rivers trusts movement are key players working towards this aim.
Presented as a 2015 Ecosystem Based Management Tools Webinar and also as a paper at the 2015 Coastal GeoTools Conference, North Charleston, SC.
The story map is a relatively new medium for sharing not only data, photos, videos, sounds, and maps, but for telling a specific and compelling story by way of that content. Story map apps provide the user with sophisticated cartographic functionality that does not require advanced training in cartography or GIS. Story maps are essentially web map applications built from web maps, which in turn are built from web-accessible data (including OGC WMS, WFS). Depending on the chosen complexity of a story map, it can be built in anywhere from a few minutes to a few days. With the beauty and utility of underlays such as the Esri Ocean Basemap, as well as a small tsunami of ocean content percolating up through a host of open data sites, there are powerful stories being told about coastal zone management, conservation, exploration and other forms of scientific field work. These stories are informing, educating, entertaining, and inspiring decision-makers on a wide variety of coastal issues. This presentation will take the audience on a small tour of a growing catalog of coastal and ocean story maps, many of which are accessible via MarineCadastre.gov and NOAA’s Digital Coast. It will also highlight the various resources available for building and deploying story maps, and discuss the utility of this medium for presenting, not just photos and videos, but more analytical results. Learn more about Story Maps at http://storymaps.esri.com.
This webinar was presented by Dawn Wright, Chief Scientist at Esri, along with Jenny Lentz, Education Specialist at the Aquarium of the Pacific. Slides here are Dawn Wright portion only.
The preliminary design of a low-cost Discovery class mission for prospecting Mars moons Phobos and Deimos is undertaken as capstone senior design class in spacecraft design. The mission is centered on a LCROSS-like mothership that carries a set of four 12U and eight 6U CubeSats. The mothership is equipped with a set of instruments for the investigation of regolith samples, similar to those with a similar functions on the Curiosity rover and the 2020 rover.
There is a small movement for change in development practices
Landscape Architect Ian McHargleads with new ideas for land planning
Understanding about the environment
Integration with environmental sciences
Addressing human adaptations to the environment
Ecological Marine Units: A 3-D Mapping of the Ocean Based on NOAA’s World Oce...Dawn Wright
This webinar to the Ecosystem Based Management Tools Network, May 17, 2017, reported progress on the Ecological Marine Units (EMU) project, a new undertaking commissioned by the Group on Earth Observations, to develop a standardized and practical global ecosystems classification and map for the oceans. The EMU is comprised of a global point mesh framework, created from 52,487,233 points from the NOAA World Ocean Atlas. Each point has x, y, z, as well as six attributes of chemical and physical oceanographic structure (temperature, salinity, dissolved oxygen, nitrate, silicate, phosphate) that are likely drivers of many ecosystem responses. We identify and map 37 environmentally distinct 3D regions (candidate ‘ecosystems’) within the water column. These units can be attributed according to their productivity, direction and velocity of currents, species abundance, global seafloor geomorphology, and more. A series of data products for open access will share the 3D point mesh and EMU clusters at the surface, bottom, and within the water column, as well as 2D and 3D web apps for exploration of the EMUs and the original World Ocean Atlas data. This webinar provided an overview of the EMU project and cover recent developments and future plans for the EMUs. Webinar recording at https://www.openchannels.org/webinars/2017/ecological-marine-units-3-d-mapping-ocean-based-noaas-world-ocean-atlas
Using data visualization for accessible science (communication)Zachary Labe
23 November 2022…
GFDL Lunchtime Seminar Series
Creating visualizations of complex data structures and patterns is an important part of our jobs. We use figures for journal publications, presentations, posters, lab group meetings, science communication, and more. However, creating suitable figures for the task can sometimes be an afterthought during the extensive scientific process. In this seminar, I’ll share examples from climate science to discuss a network of resources available for designing accessible figures in both publications and presentations by leveraging resources that support open science practices. I will also share examples of what not to do, which goes beyond only considering interpretable colormaps, and how to improve these figures moving forward. Finally, by using global mean surface temperature as a case study, I will share some creative instances of using data visualization as a form of storytelling for communicating climate change.
Department of Geography and Geoinformation Science Seminar, George Mason University, Falls Church, VA, September 2015.
Increasingly, GIS is part of the collaboration between computer scientists, information scientists, and domain scientists to solve complex scientific questions. Successfully addressing scientific problems, such as informing regional decision- and policy-making for coastal zone management and marine spatial planning, requires integrative and innovative approaches to analyzing, modeling, and developing extensive and diverse data sets. The current chaotic distribution of available data sets, lack of documentation about them, and lack of easy-to-use access tools and computer modeling and analysis codes are still major obstacles for scientists and educators alike. Contributing solutions to these problems is part of an emerging science agenda at Esri for a range of environmental, conservation, climate and ocean sciences that will be discussed. The talk will highlight some recent projects in progress, including a new global map of ecological land units, new tools to support multidimensional scientific data, continued work on an ocean basemap, and more.
Swells, Soundings, and Sustainability, but "Here be Monsters"Dawn Wright
18th Annual Roger Revelle Commemorative Lecture, National Academy of Sciences Ocean Studies Board, 5:30 – 6:30 p.m. on Friday, April 28, 2017, Baird Auditorium, Smithsonian National Museum of Natural History
From the stick charts of the ancient Marshall Islanders to the SONAR of World War II, humankind continues to devise ways to map the ocean. The newest maps, which are global, 3D, and increasingly intelligent, hold great promise for improving science and decision-making related to our oceans, but “here be monsters” to conquer data challenges. Join Dr. Dawn Wright, chief scientist at the Environmental Systems Research Institute (ESRI) and professor of geography and oceanography at Oregon State University, to learn about the past and present of ocean mapping and what must be done to overcome the challenges of “big data,” “dark data,” and the need to make data more resilient and more accessible to users.
The Roger Revelle Commemorative Lecture is presented by the Ocean Studies Board of the National Academies of Sciences, Engineering, and Medicine in cooperation with the Smithsonian National Museum of Natural History. The lecture was created in honor of Dr. Revelle’s contributions to the ocean sciences and his dedication to making scientific knowledge available to policymakers.
The Danish Geodata Agency and the Canadian Hydrographic Service have presented their joint vision about Trusted Crowd-Sourced Bathymetry this week during the 9th meeting of the IHO CrowdSourced Bathymetry Working Group (CSBWG).
C4.06: Towards continental-scale operational ocean and coastal monitoring usi...Blue Planet Symposium
Regionally tuned algorithms that deliver remotely sensed marine water quality products from the MODIS/Aqua sensor have been developed and validated for the Great Barrier Reef (GBR). Through the eReefs partnership, these algorithms are being transferred from the research domain and being deployed operationally via the national meteorological agency. Furthermore they are being adapted to work with two other ocean colour satellite instruments, SeaWiFS and VIIRS/NPP to enable extension of the monitoring time series, both historically and into the future. The production infrastructure to manage contemporary data flows from the VIIRS sensor is similarly being extended. In parallel, the validated remote sensing products are being integrated into a hydrodynamic and bio-geochemical regional ocean model through data assimilation to provide a holistic suite of monitoring products for the GBR.
This work is being undertaken with the goal of expanding the monitoring to more of Australia's marine jurisdiction. While the remote sensing algorithms themselves are parameterised for the atmospheric and optical characteristics of the GBR region, they are inherently flexible and are progressively being applied and tested in other locations where suitable in situ data are available. The data processing system for the GBR already is nested within the national data production operated by the Integrated Marine Observing System.
Head in the clouds: Engaging with the web for archaeologistsdavstott
This presentation was given on 22nd of september 2011 at the Aerial Archaeology Research Group (AARG) in Poznan, Poland.
It explores how archaeologists could exploit citizen science collaborations to make better use of the ever proliferating quantity of aerial and satellite data.
DSD-NL 2018 Evolutie in het leveren van ruimtelijke en temporele water gerela...Deltares
Presentatie door Arnold Dekker, SatDek, Australian National University, op de Delft-FEWS NL Gebruikersdag 2018, tijdens de Deltares Software Dagen - Editie 2018. Dinsdag, 5 juni 2018, Delft.
Data for the Blue Future: New Collaborations for ProgressDawn Wright
2020 UN World Data Forum Ocean Data Panel -- Data on the world’s oceans is vital to protect the environment, track and manage changes to the marine ecosystem, ensure access to coastal resources, and sustainably grow the “Blue Economy.” Climate scientists have noted that ocean data is as important as atmospheric and satellite data in understanding, predicting, and mitigating climate change. But despite its importance, ocean data has not yet been collected, shared, analyzed, and applied in all the ways that can achieve its full benefit.
Many converging factors provide the opportunity to make a quantum leap in the use of this global data resource. UN SDG Goal 14 highlighted the need to improve the health of the oceans and to collect data to track progress. In the United States, the National Oceanic and Atmospheric Administration (NOAA) and private-sector partners are making NOAA’s vast ocean data resources available and computable in the cloud. Simultaneously, established industries, emerging start-ups, academic and research institutions, and other non-government entities are collecting more data than ever about the ocean through active and autonomous measurements.
This session will be a “participatory panel” that presents case studies of ocean data’s application, describes current data sources and collaborations, and invites participants to help envision new collaborative models for improving ocean data collection, sharing, and analysis. The panelists, representing diverse organizations, will give lightning talks to describe existing data resources and examples of ocean data’s application, including the use of AI and machine learning for data management and for managing ocean resources. They will also describe collaborative programs that bring diverse stakeholders together to support the use of ocean data, such as NOAA’s Big Data Project and the Global Ocean Observing System.
The talk will be divided into two parts. The first one is about geospatial open data and several Copernicus services where those data can be downloaded. The second one is about Forest and Climate project, as an example of geospatial analysis. The aim of the project was to identify the most suitable area for afforestation in Serbia by using satellite and Earth observation data. The results can be found at https://sumeiklima.org/.
Schmidt Ocean Institute 2018 Annual ReportEric Schmidt
Schmidt Ocean Institute 2018 Annual Report (Short Version) https://schmidtocean.org/about/annual-reports/
Falkor Deep Sea Oceanography Research Conservation Eric and Wendy Schmidt
Ease Leads to Exposure, Exposure Leads to AdoptionDawn Wright
Federation of Earth Science Information Partners (ESIP) ESIP 2019 Summer Meeting - Day 2 Plenary – Tacoma, WA, July 17, 2019 In thinking about my remarks this morning, it occurred to me that there is very little that I could say to an outstanding community such as yours that you haven’t already heard. I do know, however, that one of the hallmarks of your community is your wonderful ethic of sharing, of giving, and your deep understanding that the more you GIVE in this community, the more you RECEIVE, and all toward better science for everyone, and better actions to literally save our planet.
Toward this end, I want to share some remarks under a fun Star Wars theme, which I hope you’ll enjoy. These thoughts are about getting people to actually USE the resources that we’ve worked so very hard to build, and thus is in keeping with your conference theme: “Data to Action: Increasing the Use and Value of Earth Science Data and Information.”
Slide design based on the Powerpoint slide template of Joshua D. Clarke, foxgguy2001.deviantart.com, Annville, KY
AGU Sharing Science - Social Media TipsDawn Wright
Part of an American Geophysical Union (AGU) Sharing Science webinar on May 8, 2019, with yours truly and Scripps doctoral student Tashiana Osborne sharing our science communication, science policy and social media outreach tips in advance of World Oceans Day. The webinar is also on at http://ow.ly/4KVH50u5gUI.
AGU is one of the world's largest scientific societies with a membership of 60,000+. The AGU Sharing Science Program regularly runs webinars pertaining to science communication such as scicomm via storytelling, social media, multimedia, etc. Additionally, this year is AGU’s 100 year anniversary. As part of their centennial celebration, AGU is highlighting some national and international science days, among them World Oceans Day. In advance of World Oceans Day, AGU asked Dawn and Tashiana to describe to our scientific peers how we share our science as oceanographers, women in science, and effective science communicators.
Discovery, Technology, Hope: Colorado College Roberts SymposiumDawn Wright
A plenary talk within the Harold Roberts Endowed Symposium at Colorado College on the theme "Beyond Climate Change: The Earth in the Anthropocene." The symposium (in May 2019) featured commentary on the lithosphere, biosphere, cryosphere, and Dawn's treatment of the hydrosphere (including #SDGs), all with an eye toward developing a public (and student) understanding of the breadth of environmental issues facing humanity.
Marie Tharp, Giants of Tectonophysics Session, American Geophysical UnionDawn Wright
Invited paper U22A-02, Giants of Tectonophysics Session, American Geophysical Union Fall Meeting.
In honor of AGU's centennial, this session profiles breakthrough discoveries by leading contributors to the study of plate tectonics, geodynamics, earthquakes and faulting, and rock mechanics over the past century. Biographers and colleagues of these leading lights presented the stories of these giants to give us an understanding about how they worked, how they acquired their unique insight, what conflicts they faced in presenting their ideas, and what it was like to collaborate with or debate them.
By the latter half of the 20th century the technologies behind SONAR, marine gravity, and marine magnetics had advanced to the point that the complexities of the ocean floor and beneath could be unraveled in unprecedented detail. Hence, scientists would finally be able to provide conclusive evidence for plate tectonics by way of plausible, proven physical mechanisms. But it took a young woman with an unusual background in geology, mathematics, and art to use that info to posit one of the most fundamental proofs of continental drift: a rift valley caused by the faulting of seafloor spreading. She did this while a researcher at Columbia University, in the lab of the iconic Maurice “Doc” Ewing, founder of the Lamont Geological Observatory. Along with geologist Bruce Heezen, she began the first systematic, comprehensive attempt to map the entire ocean floor. Heezen collected the data at sea, while Tharp developed a truly unique process for translating millions of these ocean-sounding records into a single drawing. During this process, she discovered the rift valley of the Mid-Atlantic Ridge, which Heezen at first discounted, holding incorrectly to his expanding Earth theory. Tharp's name was absent from the 1956 scientific paper that released this discovery to the world, and she was not given proper recognition for this and many other accomplishments until decades later. In 1968, she finally had the opportunity to go to sea, and performed the first ever shipboard processing and plotting of bathymetric data. During this time, Tharp and Heezen also formed a successful partnership with Austrian landscape painter Heinrich Berann to produce several panoramas of the ocean floor, leading to some of the most widely recognized and beloved images in all of modern Earth science. Indeed, as her first, long-time employer, Doc Ewing, invented the field of marine geophysics, Tharp invented the field of marine cartography. Her story in words, data, and maps is a story that must continue be told for the future of science as well as the past. It is a remarkable testament to persistence, conviction, and courageous innovation.
EarthX Exhibition and EarthX Ocean Conference, Dallas, Texas, April 20-22, 2018
EarthX, the largest Earth Day celebration in the world! Multiplying Environmental Awareness. Visit earthx.org to discover the expo, conference and film festival for creating positive solutions for the Earth
Toward Easy Export of Imagery Products and Feature Classes as Training Data f...Dawn Wright
American Association of Geographers (AAG) 2018 Symposium on Artificial Intelligence and Deep Learning in Geospatial Research
Whether to train a Deep Learning (DL) model to find objects of interest such as cars or solar panels in satellite or aerial images, or to classify such images into different categories of land-use, or other such tasks, a common starting point is always labeled ground truth or training data. From an industry perspective, an organization such as ESRI has a large user base of roughly 350,000 agencies, universities, non-profits, and other partners, with most of them maintaining and permanently updating their own GIS data. But how to allow this treasure trove of data to be effectively and appropriately used for training new DL models? This talk will provide an overview of new tools to export GIS data from multiple sources into popular DL formats such as KITTI or PASCAL_VOC. These can then be directly used as input to DL frameworks such as Microsoft CNTK or Google TensorFlow in order to train DL models. For example, NAIP images and building footprints of an entire county can be exported as a sequence of equally sized image chips plus one meta data file per image chip containing the bounding boxes around all buildings in KITTI format. From this data a DL model can be trained that detects buildings. The hope is that this new suite of tools will make it easier for DL researchers and students at all levels (from undergraduate to doctoral and beyond) to access existing GIS data and to use them for training new DL models.
Integrated GIS/Machine-Learning Workflows - Seagrass Use CaseDawn Wright
Integrated GIS/Machine-Learning Workflows
for Modeling Spatiotemporal Variations in Potential Seagrass Habitats within a Changing Climate, European Geosciences Union General Assembly Paper ESSI4.3 – EGU2018-10081, Vienna, Austria, April 2018.
Coastal marine plant habitats are impacted by changes in ocean conditions and the resulting changes in plant
populations can produce positive climate feedbacks which exasperate warming. (Waycott et al., 2009). One such
example is seagrasses, marine plants that can sequester vast amounts of carbon. When compared to tropical
terrestrial forests, seagrasses can store up to 100 times more CO2 at a rate that is 12 times faster (Mcleod et al.,
2011). Understanding the future of an important biologic carbon sink such as seagrass can shed some light into
future carbon balance. Modeling the relationships between seagrass occurrence and ocean conditions, current and
future, can aid in quantifying the impacts on future carbon balance. In this work, we use an integrated GIS and
machine learning approach to build a data-driven model of seagrass presence-absence in a changing climate. We
quantify the relationships between observed seagrass occurrence and ocean conditions. This relationship allows us
to delineate patterns in current ocean conditions that promote favorable seagrass habitats.We pose this relationship
as a binary classification problem and utilize Random Forest to establish a relationship for seagrass occurrence.
This relationship is projected into the future under changing ocean conditions. We use deep-learning methods,
recurrent neural networks, to forecast ocean conditions as the oceans get warmer and use these conditions in
conjunction with the Random Forest model to predict the abundance of future seagrass habitats. We integrate
multiple data sources including fine-scale seagrass data from MarineCadastre.gov and the recently available,
globally extensive publicly available Ecological Marine Units (EMU) dataset. In addition, we use global ocean
models from NOAA to calibrate our ocean forecasts. Our analysis includes a sensitivity study which investigates
the vulnerability of seagrass to changes in specific ocean variables. We use the proposed model to provide an
upper bound of the amount of carbon that can be stored in seagrasses as ocean conditions change. Finally, we
use a Getis-Ord Gi* statistic within a space-time window to quantify the temporal changes in potential seagrass
habitats.
Keynote address for 20th Society of Conservation GIS (SCGIS) Meeting, Asilomar Conference Center near Monterey, CA, July 17, 2017. Full notes available at http://esriurl.com/scgis17.
Ecological Marine Units: A New Public-Private Partnership for the Global OceanDawn Wright
Invited keynote for the 2017 Marine GIS User Group meeting held Thursday, May 25th at Stanford’s Hopkins Marine Station, 120 Ocean View Blvd., Pacific Grove, CA. The main web site for this user group is walrus.wr.usgs.gov/MontereyBayMarineGIS. The event page for the talk: https://hopkinsmarinestation.stanford.edu/events/dawn-wright-oregon-state-university-new-public-private-partnership-global-ocean
A Dark Side to Data-Centric Geography? Where are the Reward Systems?Dawn Wright
Introduction to a panel session at the 2016 American Association of Geographers Annual Meeting in San Francisco. The panel was part of the AAG Symposium on Human Dynamics Research and discussed an apparent disconnect in academia where skills in research computing and programming are still not properly rewarded.
In geography as in other disciplines, our ability to collect, process, visualize, and interpret datasets of unprecedented size and detail is helping to push the boundaries of our knowledge. This stands to affect just about every aspect of geography. Other disciplines are now discussing how best to promote a (new) culture where achievements in computational or “data science” are rewarded. This includes the emerging fields of computational social science and digital humanities. But where does geography fall within this “landscape?”
Should we not seek to train and reward a new breed of geographer, broadly skilled in computing and coding, as well as in the careful management and analysis of very large datasets? What of the reward structure for the geography faculty member or postdoc who brings these skills to the classroom, while also releasing his/her own scientific code, workflows and datasets? In many geography departments these activities do not fall within the traditional modes of writing, publishing, or even grantsmanship. Hence they may not translate to academic career advancement.
By not properly rewarding these activities, are we unwittingly driving a host of promising researchers away from the academic community?
Full notes on the session at http://dusk.geo.orst.edu/aag16-darkside.html
Feature Geo Analytics and Big Data Processing: Hybrid Approaches for Earth Sc...Dawn Wright
Invited talk for 2016 AGU Fall Meeting Session IN12A Big Data Analytics I
Introduced is a new approach for processing spatiotemporal big data by leveraging distributed analytics and storage. A suite of temporally-aware analysis tools summarizes data nearby or within variable windows, aggregates points (e.g., for various sensor observations or vessel positions), reconstructs time-enabled points into tracks (e.g., for mapping and visualizing storm tracks), joins features (e.g., to find associations between features based on attributes, spatial relationships, temporal relationships or all three simultaneously), calculates point densities, finds hot spots (e.g., in species distributions), and creates space-time slices and cubes (e.g., in microweather applications with temperature, humidity, and pressure, or within human mobility studies). These “feature geo analytics” tools run in both batch and streaming spatial analysis mode as distributed computations across a cluster of servers on typical “big” data sets, where static data exist in traditional geospatial formats (e.g., shapefile) locally on a disk or file share, attached as static spatiotemporal big data stores, or streamed in near-real-time. In other words, the approach registers large datasets or data stores with ArcGIS Server, then distributes analysis across a cluster of machines for parallel processing. Several brief use cases will be highlighted based on a 16-node server cluster at 14 Gb RAM per node, allowing, for example, the buffering of over 8 million points or thousands of polygons in ~1 minute. The approach is “hybrid” in that ArcGIS Server integrates open-source big data frameworks such as Apache Hadoop and Apache Spark on the cluster in order to run the analytics. In addition, the user may devise and connect custom open-source interfaces and tools developed in Python or Python Notebooks; the common denominator being the familiar REST API.
Latest Developments in Oceanographic Applications of GIS, including Near-real...Dawn Wright
Invited presentation for Schmidt Ocean Institute Research Planning Workshop on Transforming Seagoing Science with Robotic Platforms, Innovative Software Engineering, and Data Analytics, August 2015
Creatures of the Deep and Treasure Maps of the Ocean FloorDawn Wright
Invited Evening Public Lecture, Redlands Forum, Redlands, CA. The Redlands Forum (formerly Town and Gown) is a free cultural series that welcomes new speakers every month. The event, sponsored by Esri and the University of Redlands Town & Gown, offers educational and cultural programs on a variety of topics for free or at nominal cost. Presenters include government and business leaders, environmentalists, filmmakers, and performers. It is one of the more popular things to do in Redlands. This Redlands Forum was introduced by Esri President Jack Dangermond and delivered to a capacity audience in May 2015.
Climate Information, Tools, and Services for Enhancing Resilience Dawn Wright
Invited plenary presentation for the Global Frontiers Track of The White House Frontiers Conference, October 13, 2016 on the campuses of the University of Pittsburgh and Carnegie Mellon University. This national conference, hosted by President Barack Obama, brought together thought leaders to address the growth and challenges in science, technology and innovation. Discussions focused on improving lives by investing in those areas.
Toward a Digital Resilience (with a Dash of Location Enlightenment)Dawn Wright
AGU Earth and Space Science Informatics Leptoukh Lecture, AGU Fall Meeting, December 15, 2015, San Francisco.
The Greg Leptoukh Lecture honors the life and work of Earth scientist, Greg Leptoukh. Leptoukh was very active in the informatics community and involved in many projects related to data quality and data provenance. This Earth and Space Science Informatics focus group named lecture is presented annually at the AGU Fall Meeting. The Leptoukh Lecturer is selected for significant contributions to informatics, computational, or data sciences through research, education, or other activities. Specifically, this lecture aims to raise awareness about computational and data advances that enable breakthroughs in domain science, as well as foster exceptional individuals to make continued contributions in informatics and data science. This prestigious honor is only bestowed once per individual.
2015 lecture abstract: The AGU Earth and Space Science Informatics Focus Group addresses a compelling array of research questions and projects. This year’s session topics range from large-scale data management within global cyberinfrastructures or virtual observatories, to intelligent systems theory, semantics, and handling of near-real-time data streams, to issues of “dark data,” data transparency, reproducibility, and more. The aim of this lecture is to build in part on these themes but to consider more broadly how we might push the boundaries of informatics knowledge more along the lines of use-inspired science (responsive to the needs and perspectives of society while still being fundamental and cutting edge). To wit, as we contend with human impacts on the biosphere recent innovations in computational and data science are now facilitating community resilience to climate change (e.g., helping communities to monitoring air quality or drought, find available drinking water, determine habitat vulnerability, etc.). But not often discussed is a path toward digital resilience. If digital tools are to continue helping communities, it stands to reason that they must engender some resilience themselves. The capacity to deal effectively with change and threats, to recover quickly from challenges or difficulties, even to withstand stress and catastrophe, can apply to data too. As investments in digital data continue to rise, we find ourselves in new “digital world order” comprised of ubiquitous technologies from satellites to wristwatches to human biochip implants. And a significant proportion of these are geospatial, given the incredible power of maps to communicate, persuade, inspire, understand, and elicit action. Therefore, the lecture reviews and recommends seven fundamental digital research and communication practices. The aim is ensuring not only a modicum of resilience for our nascent discipline, but in prototyping and delivering repeatable solutions that all can use to help guide the planet towards a more resilient future.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Geospatial as an Accelerator of Impact: Already Converging!
1. Smart Oceans 2020 | October 5th | Virtual Plenary
Geospatial as an Accelerator of Impact
Already Converging!
Dawn J. Wright, Ph.D.
Chief Scientist
Environmental Systems Research Institute (aka Esri)
@deepseadawn
2. Sea Surface Temperature
NOAA
Chlorophyll-a Concentration
NOAA
Global Species Range Rarity
E.O. Wilson Biodiversity Foundation
Ocean Warming Ocean Health Biodiversity
A Global Geospatial Framework is Emerging
3. Geospatial Provides a Proven Framework
Agricultural Science
Hydrology
Ecology
Geology/Geophysics
Conservation Biology
Forestry
Ocean ScienceGeographic Information Science
Spatial Data Science
Computer Science
Cartographic Science
Remote Sensing
Sustainability Science / Geodesign
/ Social Science
Climate Science
4. C-Accel Track A: KnowWhere Graph
Enriching and Linking Cross-Domain Knowledge Graphs using Spatially-Explicit AI
NSF Award 2033521, Lead PI K. Janowicz, UCSB
5. C-Accel Track A: KnowWhere Graph
Enriching and Linking Cross-Domain Knowledge Graphs using Spatially-Explicit AI
NSF Award 2033521, Lead PI K. Janowicz, UCSB
6. Esri is Working with a Loosely Connected Network of Organizations
Microsoft
National
Geographic
Society
Pristine Seas
Universities
Scripps, UCSB,
Lamont, more
UN
Esri
Users
NGOs
Conservation
Education
Esri
Science
GEO
Blue Planet
SDSN
SDGs
Esri
Partners
To Leverage and Extend This Global Framework
E.O. Wilson
Foundation
Ocean Data
Platform
C4IR-Ocean
Seabed
2030
NOAA
Big Data
Sustainability
POGO
NSF
OceanObs
RCN
9. “GeoAI”
Classification
Clustering
Prediction
• Maximum Likelihood
• Random Trees
• Support Vector Machine
• Empirical Bayesian Kriging (EBK)
• Areal Interpolation
• EBK Regression Prediction
• Ordinary Least Squares Regression and Exploratory
Regression
• Geographically Weighted Regression (GWR)
• K means | Spatially Constrained Multivariate Clustering
• Multivariate Clustering | Density-based Clustering
• Hot Spot Analysis | Image Segmentation
• Space Time Pattern Mining Outlier Analysis
10. “GeoAI” – Predicting Seagrass Distribution in a Warming Ocean
Australia could lose significant seagrass
habitat by 2030
AGU Eos feature, Jan 2018 +
Aydin et al., Estuaries &Coasts, in press
11. “GeoAI” – 3D Modeling of Dissolved Oxygen in Monterey Bay
Flip book esriurl.com/flipbook, p. 44
Learning module https://learn.arcgis.com/en/projects/interpolate-3d-oxygen-measurements-in-monterey-bay/
12. “GeoAI” – 3D Modeling of Dissolved Oxygen in Monterey Bay
Flip book esriurl.com/flipbook, p. 44
Learning module https://learn.arcgis.com/en/projects/interpolate-3d-oxygen-measurements-in-monterey-bay/
15. Tracking, Monitoring, Alerting via Sensor Networks and IoT
Analytics for Internet of Things (including IUU Vessels)
Situational
Awareness
Analytics
Alerting
Real-Time
Data
17. Smart Oceans 2020 | October 5th | Virtual Plenary
Geospatial as an Accelerator of Impact
Already Converging!
Dawn Wright
dwright@esri.com
www.esri.com/sciences --> Ocean Science
@deepseadawn
dusk.geo.orst.edu/Pickup/Esri/smartocean.pdf
18. Smart Oceans 2020 | October 5th | Virtual Plenary
Extra slides for Q&A
19. Geospatial Infrastructure for a Digital Ocean
DistributedServices
Real-Time Measurement
Extensive
Content
StoryMaps
Data Science
Geocoding
GeoEnrichment
Analytic
Services
Big Data
AI & ML
Designed to work together…
Open & Interoperable….
Standards Based….
Secure….
SharedApps
Tracking
Field
Operations
Search &
Discover Publishing
Services
Remote Sensing
Content
Management
Open Data
Containers
Editor's Notes
...involving and supporting many organizations and communities, all seeking to share data sets and services, dramatically extending the impact of geographic information systems or GIS, which provides a SPATIAL FRAMEWORK toward helping ocean data achieve its full benefit
Because Geospatial is special – yes, points, line, areal observations, but photography/videography and other imagery, seismics, surfaces and volumes of ocean parameters. Geospatial lies at the heart of just about everything that matters to us in the ocean such as
WHERE to best establish and enforce additional marine protected areas, especially in the high seas
WHERE and HOW to sustainably feed a rapidly growing population with ocean-based protein?
WHERE to address hot spots of rapidly declining ocean oxygen and increasing ocean acidification?
WHERE to mitigate and adapt to a changing climate? All of these are inherently spatial issues.
Are we not all beginning to create and speak the common SPATIAL language of maps and even 3D scenes that we can mash up and integrate dynamically? Indeed Geospatial is providing a proven framework in a virtuous circle of measurement, analysis & modeling, mapping & visualization, planning & evaluation leading to decision-making and most importantly ACTION in many fields, especially the ones show, which are quickly converging under this geospatial umbrella. They are all building integrated platforms that are bringing together and applying a collective geographic knowledge, sharing it back and forth among these fields and their stakeholders (academia, industry, policy, philanthropy).
To wit, my colleagues and I at Esri are no-cost senior personnel on a new NSF Convergence Accelerator Pilot Phase II Active project LED BY GEOGRAPHERS that greatly desires to integrate with Smart Oceans because of the value add that it is building for a host of domains
Knowledge graphs power search engines, catalogs, apps – building a new much more open web of structured scientific data an open Open Knowledge Network (semantics, ontologies, vocabularies, standards)
Where the X-Ray is an emerging technology called “geoenrichment” which is the enhancing of EXISTING data with additional location-based context (it could be demographics, infographics, blue economy financials, fisheries stock assessments, movement data, migrations, even parameters from climate models). It fills in needed attributes that are currently missing
AI-powered geoenrichment services with an open cross-domain knowledge graph
https://www.nsf.gov/awards/award_visualization.jsp?org=NSF&pims_id=505777&ProgEleCode=095Y,096Y&from=fund#region=US-CA&instId=0013201000
AI-powered geoenrichment services with an open cross-domain knowledge graph
Seeking to add value to a host of domains, including in the future, Smart Oceans!
Knowing where and when things happen is key to understanding why they happen. Our graph, services, and ontologies will be of value across domains and to other OKNs.
This team will also be the first to incorporate satellite data, drone imagery, and maps into a knowledge graph
Our millions of users and thousands of business partners
Collaborations both formal and informal with the ocean organizations and initiatives in yellow
Centre for the 4th Industrial Revolution-Ocean in Norway is an affiliate of the World Economic Forum’s C4IR Network, and is currently building the Ocean Data Platform
POGO = Partnership for Global Ocean Observation
RCN = Research Coordination Network
E.O. Wilson Foundation in building the Half Earth Map
Microsoft in building their Planetary Computer and partnering in AI for Earth
A big part of this effort is our new Living Atlas Indicators of the Planet, which is like a “report card” for the entire Earth. If you go to this URL the indicators fill up your entire browser window. We’ve partnered with @microsoft, @natgeo, and the @UnitedNations Sustainable Development Solutions Network to compile 18 pressing topics affecting our planet with real-time or near real-time data to match. We keep these indicators updated up to the minute with hosted Python notebooks touching the data in the cloud with AI that provides dynamic integration of data from multiple sources, and then running consistent analytics on the fly. Click on each indicator to go deeper with higher resolution maps and resources
The result is a single point to understand the day to day and year to year changes that are occurring on Earth. As you can see these are marked by the relevant SDG and there are several for the ocean. The Living Atlas, by the way is one of the world’s largest catalogs of geospatial data, information, apps (including ~200 million map requests by ~2 million users per DAY) and is being used by Microsoft as a content provider for its AI for Earth initiative and as a backbone for its emerging Planetary Computer initiative.
Speaking of AI, GEOAI, Geospatial AI has made great strides with both vector and raster data in the areas of classification, clustering, and prediction with some examples of the specific types of functions in each category.
Modeling Dissolved Oxygen in Monterey Bay -
https://dusk.geo.orst.edu/Pickup/Esri/Science_flipbook/#p=44
Scientists and researchers often encounter the problem of unknown values within a range of known values. To solve this problem, they use mathematical and statistical methods to create or interpolate new data points. They use these data points to fill in the gaps and model phenomena occurring across a landscape or in 3D space. Researchers use interpolation to accurately predict values for new data points using the existing values of a limited number of sample data points where the measurements were gathered. Researchers have begun using Empirical Bayesian Kriging 3D, a geostatistical interpolation method developed by Esri, to get new estimated values between the known values, and then model the measurements in 3D.
Kriging
Kriging is a method of interpolation used in spatial analysis in which data points exist at specific locations in space and time. Each data point is defined by geographic coordinates (i.e., latitude, longitude, and often, elevation) and other measurements, such as the amount of particulate matter in the air. Kriging applies the basic principle that distributed data points are spatially correlated. This principle assumes that while everything is related to everything else, near things are more related than distant things.
Researchers can use kriging to predict unknown values for any data point, such as elevation, rainfall, chemical concentrations, and noise levels. Empirical Bayesian Kriging 3D is used when the data points are distributed within a geographic volume, such as a square-mile study area of an ocean, ranging from the ocean surface to the ocean floor.
Cross validation
Empirical Bayesian Kriging 3D provides cross-validation tools to assess how well the model predicts values at unknown locations. Cross validation removes a measured point and then uses all remaining points to go back to the location of the removed point. This process is called the “leave-one-out” validation method. The measured value at the hidden point is then compared to the prediction value from cross validation. The difference between these two values is called the cross-validation error and is performed on every input point.
Modeling dissolved oxygen levels in Monterey Bay
Recent research has established that global oxygen levels in the ocean have declined for decades. Dissolved oxygen is the essential ingredient for life beneath the surface of lakes, rivers, and oceans. Using data from the World Ocean Database (WOD) provided by NOAA’s National Centers for Environmental Information, researchers measured the levels of dissolved oxygen by sampling water at different locations in Monterey Bay on the California coast. From above, the sample locations would appear as dots on a map riding on a flat surface. However, researchers sampled at multiple depths at each location, leaving lots of distance between measurements, where dissolved oxygen levels are unknown. Researchers filled in the blanks using Empirical Bayesian Kriging 3D to interpolate the values between these known measurements and create estimated but reliable measurements at each sampling depth.
The result is a 3D map layer stack of surface models, each depicting ranges of dissolved oxygen levels. It is easy to see that dissolved oxygen levels vary across each surface and vertically through the layers. Cross-validation tools and charting allow researchers to explore any location across each surface and slide up and down through the surface layer stack at a specific location.
Modeling Dissolved Oxygen in Monterey Bay -
https://dusk.geo.orst.edu/Pickup/Esri/Science_flipbook/#p=44
Scientists and researchers often encounter the problem of unknown values within a range of known values. To solve this problem, they use mathematical and statistical methods to create or interpolate new data points. They use these data points to fill in the gaps and model phenomena occurring across a landscape or in 3D space. Researchers use interpolation to accurately predict values for new data points using the existing values of a limited number of sample data points where the measurements were gathered. Researchers have begun using Empirical Bayesian Kriging 3D, a geostatistical interpolation method developed by Esri, to get new estimated values between the known values, and then model the measurements in 3D.
Kriging
Kriging is a method of interpolation used in spatial analysis in which data points exist at specific locations in space and time. Each data point is defined by geographic coordinates (i.e., latitude, longitude, and often, elevation) and other measurements, such as the amount of particulate matter in the air. Kriging applies the basic principle that distributed data points are spatially correlated. This principle assumes that while everything is related to everything else, near things are more related than distant things.
Researchers can use kriging to predict unknown values for any data point, such as elevation, rainfall, chemical concentrations, and noise levels. Empirical Bayesian Kriging 3D is used when the data points are distributed within a geographic volume, such as a square-mile study area of an ocean, ranging from the ocean surface to the ocean floor.
Cross validation
Empirical Bayesian Kriging 3D provides cross-validation tools to assess how well the model predicts values at unknown locations. Cross validation removes a measured point and then uses all remaining points to go back to the location of the removed point. This process is called the “leave-one-out” validation method. The measured value at the hidden point is then compared to the prediction value from cross validation. The difference between these two values is called the cross-validation error and is performed on every input point.
Modeling dissolved oxygen levels in Monterey Bay
Recent research has established that global oxygen levels in the ocean have declined for decades. Dissolved oxygen is the essential ingredient for life beneath the surface of lakes, rivers, and oceans. Using data from the World Ocean Database (WOD) provided by NOAA’s National Centers for Environmental Information, researchers measured the levels of dissolved oxygen by sampling water at different locations in Monterey Bay on the California coast. From above, the sample locations would appear as dots on a map riding on a flat surface. However, researchers sampled at multiple depths at each location, leaving lots of distance between measurements, where dissolved oxygen levels are unknown. Researchers filled in the blanks using Empirical Bayesian Kriging 3D to interpolate the values between these known measurements and create estimated but reliable measurements at each sampling depth.
The result is a 3D map layer stack of surface models, each depicting ranges of dissolved oxygen levels. It is easy to see that dissolved oxygen levels vary across each surface and vertically through the layers. Cross-validation tools and charting allow researchers to explore any location across each surface and slide up and down through the surface layer stack at a specific location.
There is also the emerging concept of the “digital twin,” which will be powerful for the ocean – this is a virtual representation of an object, process, or system that bridges the gap between the physical and digital worlds. However, it is MORE than just a visualization, as when implemented with IoT and AI it can accelerate innovation, build consensus, and save time and money by iteratively modeling changes, testing how components or systems function, and troubleshooting malfunctions inexpensively in a virtual world.
Esri has been writing about digital twins in the geospatial realm since 2017, especially with regard to ports (e.g., https://www.esri.com/about/newsroom/publications/wherenext/digital-twin-for-supply-chain-management/)
A recent news article in Science reports that the European Union is finalizing plans for an ambitious “digital twin” of planet Earth that would simulate the atmosphere, ocean, ice, and land with unrivaled precision, providing forecasts of floods, droughts, and
fires from days to years in advance.
To reach the ultimate goal of being the first port in the world to accept autonomous (self-sailing) ships, the port of Rotterdam is already working with Esri to create a digital twin of the port. The port calls this a “moonshot”
Rotterdam’s GIS-powered digital twin would allow port managers to view the operations of all the primary players, provide an accurate, current picture of what is going on in the port, everything from the weather to how many ships are sailing about, their speed, and where they are headed. Simulations would be run digitally to improve efficiency and save money in the real port. Rotterdam officials anticipate being able to pinpoint the best times for ships to berth and offload or take on cargo, because the digital twin simulations will give them the optimal water depths and berth vacancies, among other variables.
https://www.esri.com/about/newsroom/podcast/port-of-rotterdam-the-digital-transformation-of-europes-largest-port/
https://www.esri.com/about/newsroom/publications/wherenext/rotterdam-autonomous-ships-and-digital-twin/
Digital twins rely on sensor networks and IoT especially to monitor and track IUU fishing via AIS and precise radio frequency signals – showing also an R Studio session bridged with ArcGIS where appropriate feature services, image services, REST APIs, JSONs, and geodatabases can be more fully analyzed and interactively mapped
(e.g., Hawkeye 360 is a Silver-level Esri business partner, https://www.he360.com/about/)
HawkEye 360 is a Radio Frequency (RF) data analytics company. We operate a first-of-its-kind commercial satellite constellation to identify, process, and geolocate a broad set of RF signals. They extract value from this unique data through proprietary algorithms, fusing it with other sources to create powerful analytical products that solve hard challenges for our global customers. Their products include maritime domain awareness and spectrum mapping and monitoring; their customers include a wide range of commercial, government and international entities.
And one of our longest standing ocean public-private partnerships to date is with these agencies and organizations to create a 3D basemap of the entire ocean (1/4 deg or 27 km horizontally and at 102 depth zones down to 5000 m) of the top physical parameters that control ocean’s ecology – a massive statistical clustering of global T, S, O2, nitrate, phosphate, silicate NOAA’s authoritative World Ocean Atlas, which in turn is based on the World Ocean Database of the UNESCO IOC IODE and NOAA. Published in these outlets, also available in apps for the web, phone, or tablet.
And a number of use cases are underway to deploy this 3d basemap for ecological studies or better yet to build biological/biodiversity data INTO the EMUs themselves
the capabilities foundational for digital oceanography, to strengthen the geospatial infrastructure that you’re already creating, a digital nervous system of sorts that’s intelligent, open, interoperable, based on standards, and secure. This is Esri’s ecosystem of tools that extend well beyond mapping, from data collection in the field to artificial intelligence/machine learning functions. This is all extremely powerful. Yes, I know. You had no idea!
And a number of use case underway to deploy the 3d basemap for ecological studies or to build biological/biodiversity data INTO the EMUs themselves
Wright, D.J., Kavanaugh, M.T., Henry, L.-A., Brandt, A., Saeedi, H., Bednarsek, N., Van Graafeiland, K., Butler, K.A., Breyer, S., and Sayre, R.G., Use cases of Ecological Marine Units for improved regional ocean observation data integration within the Marine Biodiversity Observation Network (MBON) (Highlighted), Eos, Trans. AGU, 99, Fall Meet. Suppl., Paper B41L-2897, 2018.
We report on a series of use cases underway to augment and test the viability of the global Ecological Marine Units (EMUs). EMUs were commissioned in 2015 by the Group on Earth Observations (GEO) as a means of developing a standardized and practical global ecosystems classification and map for the oceans. They are a key outcome for the GEO Biodiversity Observation Network (GEO BON), and a recent contribution to the Marine Biodiversity Observation Network (MBON).EMUs are comprised of a global 3D point mesh framework of 52 million ocean observations of salinity, temperature, dissolved oxygen, nitrate, silicate, and phosphate from the NOAA World Ocean Atlas. Many cite the need to scale this global framework down regionally and up temporally. Hence, over 15 teams of researchers are implementing EMUs in regional use cases, based on their own higher-resolution data for a richer geospatial accounting framework and visualization of species distributions.
Among these are use cases in temperate upwelling, shallow subtropical and polar regions, where boundaries of surface seascapes are compared to surface EMUs, and at seasonal scales. The EU-funded ATLAS project is comparing EMUs to species-based biogeographic clusters of Vulnerable Marine Ecosystems in the North Atlantic to further refine UNESCO's Global Open Ocean and Deep Seafloor effort for this region. German researchers compiling 5000-6000 deep-sea distribution records from expeditions to the Sea of Okhotsk, the Aleutian Trench, and the Kuril-Kamchatka Trench are comparing their EMU use case with the ATLAS use case. Another use case seeks to add data on NE Pacific carbonate chemistry and pteropod shell dissolution to the EMU 3-D point mesh network to provide information on the responses of ecosystems to influences such as ocean acidification.
In sum, we are building a strong user community based on these use cases to improve understanding of global and regional drivers of biogeography, refine tools to classify and prioritize areas for improved marine management including area-based management tools, and to enhanced visualizations of ocean trends and/or forecasts.