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Event

Space Enabled Presents at the American Geophysical Union Fall Meeting 2020

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AGU

AGU

Tuesday — Thursday
December 1, 2020 —
December 17, 2020

AGU supports 130,000 enthusiasts to experts worldwide in Earth and space sciences.

Through broad and inclusive partnerships, AGU aims to advance discovery and solution science that accelerate knowledge and create solutions that are ethical, unbiased and respectful of communities and their values. Their programs include serving as a scholarly publisher, convening virtual and in-person events and providing career support

AGU was established in 1919 by the National Research Council and operated as an unincorporated affiliate of the National Academy of Sciences for more than 50 years. They were independently incorporated in 1972.

AGU is an innovator among scientific organizations. They pioneer new approaches to growing the exchange of scientific knowledge through publishing and meetings. They promote excellence in scientific research by setting and promoting standards and best practices, strengthening the integrity of published and presented research, and leveraging science to help society worldwide. Members of the Space Enabled research group present updates on our work in three areas: Antiracism and Technology Design;  designing space systems in support of sustainable development; and design of tools to make space-based technology more accessible.

Earth Observation Technology Applied to SDG 15.8 in West Africa: Multi-data Stream Analysis and Validation Approaches

Ufuoma Oviemhada, Fohla Mouftaou, Felicien Badou, Belfrid Djihouessi, Eric Ashcroft, David Lagomasino, Lola Fatoyinbo, Seamus Lombard, Mulan Jiang, Danielle Wood

Session Date and Time: Monday, 7 December 2020; 8:46 - 8:50 PST 
Session Number and Title: SY006-04 - Earth Observation Technology Applied to SDG 15.8 in West Africa: Multi-data Stream Analysis and Validation Approaches

The water hyacinth is an invasive plant species that has spread throughout coastal West Africa, reducing biodiversity, clogging transportation networks and impacting fishing activities. Green Keeper Africa (GKA), an enterprise located in Benin, works to harvest and repurpose the plant. The MIT Media Lab Space Enabled Research Group is partnering with GKA to design an online observatory that uses satellite data, drone imagery and ground based sensor data to map the location of the water hyacinth over time and publish this information for government, private and public users. The observatory also includes information about acadja, a controversial traditional fish farming practice that is related to water hyacinth dynamics and management. This project responds to SDG 15.8 pertaining to the management of invasive species. 

First, the presentation will showcase cross correlation analyses between locally-collected climate data and water hyacinth extent estimations (derived from optical satellite data). Second, the presentation highlights an approach that utilizes optical and synthetic aperture radar data in a supervised machine learning model to estimate acadja presence. Lastly, the author describes and critiques several approaches for validating the water hyacinth and acadja classifications. The water hyacinth and acadja analyses have business and regulatory implications for Green Keeper Africa and management entities such as the Benin National Institute of Water, the Ministry of the Living Environment and Sustainable Development, the Ministry of Agriculture, Livestock and Fisheries, and the Ministry of Water and Mines. Green Keeper Africa can use the information presented about the water hyacinth to improve their harvesting practices in line with their priorities for profit and reduction of socioeconomic and ecological impacts. The Ministries can use this information to pursue new policies and practices that support SDG 15.8 and related SDG targets. 

Earth observation in support of the SDGs: Trends from the Humanitarian and Development sectors

Minoo Rathnasabapathy

Presentation Type: eLightning Session
Session Date and Time: Monday, 7 December 2020; 10:30 - 11:30 PST 
Session Number and Title: GC016: Advances in the Application of Earth Observations to Address the Sustainable Development Goals (SDGs) in a Changing Climate: Understanding the Enabling Environment

Click here to view the presentation.

Earth Observations provide unique insight in planning, tracking progress, and monitoring the Sustainable Development Goals (SDGs) at a national, regional and local level. Through organizations such as the Group on Earth Observations (GEO), a large number of national governments are connecting and collaborating with academic and research institutions, data providers, and commercial companies to create innovative applications to address pressing global challenges. With a focus on the development and humanitarian sectors, the Space Enabled Research Group at the Massachusetts Institute of Technology (MIT) Media Lab and Secure World Foundation created a project to draw insights from practitioners about t real-world case studies as well as opportunities and challenges for expanding the use of Earth Observation in efforts to achieve the SDGs. Space Enabled and Secure World hosted a series of webinars featuring presentations by topical experts, in-seminar data collection through live poll questions, and audience Q&A. After each event, participants were asked to complete a post-seminar survey to gain insights into their respective work, challenges they may face, and new initiatives. Importantly, the webinar series aimed to reach beyond the Earth Observation community  to identify trends in the utilization of Earth Observation to support in-situ data, how national governments and developmental organizations collaborate and partner with data-providers such as space agencies, unique considerations taken to validate, customize and combine data, and potential technical and legal barriers that limit the operational use of Earth observations by decision-makers, project managers, and development partners. While many of the participants noted that they were aware that Earth Observation is being utilized in some projects, participants also highlighted challenges such as overcoming the technical limitations of data processing and visualization, and the lack of training resources on how to efficiently manage large datasets. Preliminary findings from the questionnaires and polls  show that the most common barriers when using satellite data to provide better information to policy makers to affect change is the lack of political motivation to shift policies based on new data, followed by the lack of funding to shift policies based on new data, and finally the lack of access to data. The presentation summarizes the collection of diverse viewpoints and opinions from a multi-sector community that need to be addressed  to ensure that Earth Observation can be used effectively and enable countries to monitor and manage their progress towards their SDG targets. 


Inclusive Design of Earth Observation Decision Support Systems (DSS) for Environmental Governance

Ufuoma Ovienmhada

Presentation Type: Virtual Poster Session
Session Date and Time: Tuesday, 8 December 2020; 04:00 - 20:59 PST
Session Number and Title: GC027: Gender and Social Inclusion in Climate Data Services and Analyses

Click here to view the presentation.

Managing human-environmental systems can be complex in nature due to competing interests from multiple stakeholders. Effective management of these complex human-environmental systems requires information relevant to the social, economic, and environmental conflicts that can arise in these systems. Earth Observation (EO) data can enhance understanding of this type of information. This information can then be used to inform Decision Support Systems (DSS) for environmental governance and advance sustainable development. However, EO data is not always incorporated into the workflow for decision-makers for a multitude of reasons including awareness, accessibility and collaboration models. 

The Space Enabled Research Group (MIT Media Lab) aims to address these challenges to incorporating EO data in DSS by collaborating with local leaders in a way that produces scientific results in response to locally defined priorities, while honoring and respecting local knowledge. For example, the author has worked on a multi-year project to apply EO data to an environmental governance challenge in collaboration with the enterprise Green Keeper Africa (GKA), based in Benin. GKA addresses the management of an invasive plant species that threatens economic activities on Lake Nokoué. The presentation will highlight findings from this project on how to define principles for building non-exploitative, reciprocal relationships between multiple organizations. Examples of principles relate to presentations, fundraising and data collection. The research also discusses how to examine existing design methods in order to identify an inclusive process for project implementation that aligns with defined collaboration principles.

Due to climate change and population pressure, many regions are facing similar environmental governance challenges as Lake Nokoué. This presentation will also highlight several examples from the Space Enabled portfolio in Brazil, Chile, Ghana, India and Indonesia where we are similarly working with local leaders to build DSS in a way that empowers historically marginalized groups in the face of environmental harm.  

Antiracism & Technology Design: Building Frameworks to Advance Justice in Complex Sociotechnical Systems

Katlyn Turner

Presentation Type: Oral Session
Session Date and Time: Tuesday, 8 December 2020; 05:30 - 06:30 PST
Session Number and Title: SY016: Science and Society: Social and Behavioral Sciences

The Vida Decision Support System: an integrated modeling framework to inform and monitor regional COVID-19 responses

Jack Reid

Presentation Type: eLightning Session
Session Date and Time*: Wednesday, 9 December 2020; 05:30 - 06:30 PST
Session Number and Title: SY025: COVID-19: Assessing the Impacts of the Pandemic on the UN Sustainable Development Goals (SDGs) and Science Communication of Climate Change

Click here to view the presentation.

The COVID-19 pandemic has had a diverse range of both direct and indirect impacts on health (both physical and mental), the economy, and the environment. The relevant data sources used  to inform pandemic-related decisions have been similarly diverse, though decision-makers have primarily relied upon data sets from non-satellite sources such as traditional public health data. As we move from initial crisis response to more long-term management, there is both an interest and a need for considering a wider diversity of data sources and impacts. It is difficult for any person to absorb and respond strategically to the broad sets of data that are relevant to the issues regarding COVID management. To address this, the authors propose a five part, integrated data visualization and modeling framework entitled the Vida Decision Support System. The goal of Vida is to create an accessible and openly available online platform that can be customized by the leadership team for a city or region and bring together knowledge from several areas of expertise. The five components of Vida, each of which serve to model a specific domain, include Public Health, Environment, Socio-economic Impacts, Public Policy, and Technology. This framework is currently being designed and evaluated with collaborators in Angola, Brazil, Chile, Indonesia, Mexico and the United States. The environmental data comes from sources such as in-situ sensors and both civil and commercial earth observation instruments (Landsat, VIIRS, Planet Labs’ PlanetScope, etc.) to track factors such as water quality, forest extent and health, air quality, human mobility, and nighttime urban lighting. Similarly, socioeconomic data derives from both in-situ sources, such as local statistical agencies, and from satellite products, such as those hosted by NASA’s Socioeconomic Data and Applications Center. The authors discuss the value provided by this framework to each of the collaborators, the process used to apply the framework to each local context, and future possibilities for Vida. Even though Vida was first developed and applied in response to COVID-19, it has applications in other public health contexts where policy, environment, and socio-economic impacts are closely tied.

Designing Decision Support Systems with Interdisciplinary, International Teams: A Case Study of the Environment, Vulnerability, Decision, Technology Model

Seamus Lombardo

Presentation Type: Virtual Poster Session
Session Date and Time: Wednesday, 9 December 2020; 13:30 – 14:30 ET PST

Session Number and Title: SY023: Science to Action: Transformative Partnerships and Knowledge Coproduction to Advance Decision-Relevant Science

Click here to view the presentation.

The authors have developed the Environment-Vulnerability-Decision-Technology (EVDT) integrated modeling framework which considers the interactions between the environment, societal impact, human decision-making, and technology design to support decision making. The EVDT framework has been expanded to include a public health model in the Vida Decision Support System, which will help local leaders understand the relationships between important societal factors relating to COVID-19. Key to the development of Vida are collaborative design and mutual learning with international and interdisciplinary teams. Collaborations underway with academic researchers and government officials (including public health, economics, environmental, and demographic data collection officials) in Angola, Brazil, Chile, Indonesia, Mexico and the United States provide in-depth understanding of local contexts. Several important lessons learned from these collaborations include the value of holding dialogues with teams from the same geographic region but different topic areas (a space agency compared to a public health agency), allowing for time to learn the best way to combine diverse data types and find the tools each collaborator prefers, and encouraging the use of the preferred language of collaborators. During Vida’s development, each collaborator has worked to create their own version of Vida using local data sources, the US team has provided prototype analyses and models, and collaborators have facilitated the sharing of individual insights among the whole network. These partnerships have yielded promising initial results to support decision making, with prototype tools incorporating local data on COVID cases, the environment, and socio-economic factors from Rio De Janerio and Chile being  evaluated the effects of different policy scenarios on community outcomes. This collaborative design process will develop actionable insights for decision-making, create a network of international collaborators that can exchange technical methods beyond the COVID-19 pandemic, and emphasize the principles of inclusive innovation and decoloniality by submitting to the preferences of local leaders in each country.

Complex human-natural systems on Earth and in Space: Emerging Tools to Advance Just Outcomes for Long Term Challenges

Danielle Wood

Presentation Type: Oral Session
Session Date and Time: Thursday, 10 December 2020; 16:00 - 17:00 PST
Session Number and Title: IN020: Data-Driven Exploration of Interconnected Risks in Complex Human–Natural Systems

The global commons – Antarctica, Earth’s Orbit, the oceans, the atmosphere –illustrate the pivotal need to understand complex natural-human systems and the benefits of interdisciplinary work to characterize risk. Such risks require great care to understand when they unfold over long time scales, extend over wide geographic areas and result from distributed actions of many actors. Consider, for example, the risk of sea level rise and coastal erosion menacing an equatorial megacity due to ice sheet melting in Antarctica; or consider the risk of a catastrophic series of satellite collisions in Low Earth Orbit. What analysis frameworks and collaboration approaches allow scholars, decision makers, community members and business leaders to communicate in mutually understandable language to answer key questions?  What data sources are useful to characterize the relationship between human actions that change the environment and environmental forces that have social, cultural and economic impact? What data sources reveal the inequitable distribution of environmental harm that often threatens human communities with limited economic resources, such as indigenous peoples and small island nations? This presentation highlights research projects by the Space Enabled Research Group (MIT Media Lab) and our collaborators that show examples of interdisciplinary approaches to address complex systems problems at the nature-human interface. The Space Sustainability Rating project includes effort to characterize the risk of collision among space objects, estimate the difficulty of tracking satellites and create incentives for satellite operators to reduce space debris. The Antarctica Museum Project designs an experience to expose families to a broad range of data about the geography, wildlife and research traditions of Antarctica while explaining how global coastal resilience is linked to the sustainability of southern ice sheets. The projects reveal that a variety of approaches, including physics simulations, business strategy, industrial design, policy analysis, history and earth science are needed to progress in mitigating the risks in complex, natural-human systems.

The Impact of Social Distancing Policies on the Lives of Individuals from Vulnerable Job Sectors in Greater Boston

Katlyn Turner

Presentation Type: Virtual Poster Session
Session Date and Time: Thursday, 10 December 2020; 04:00 - 20:59 PST
Session Number and Title: NH018: Lessons Learned at the Intersection of Hazard Research and Policy Actions

Methods and tools to improve understanding and application of biodiversity data based on satellite Earth observation: Examples from Benin, Ghana and Brazil

Danielle Wood

Presentation Type: Oral Session
Session Date and Time: Friday, 11 December 2020; 20:30 - 21:30 PST
Session Number and Title: B073: Advances in the Application of Remote Sensing for Biodiversity Monitoring: Integrating Data and Models Across Scales and Technologies IV

People from a variety of backgrounds need to understand and apply biodiversity data as part of community leadership roles, such as tribal elders, entrepreneurs, researchers, city managers, business people and labor organizers. New technology trends are changing options for using biodiversity information due to the increasing use of low-cost aerial vehicles and in-situ sensors for scientific observation, combination of data from commercial and government satellites, and increased use of artificial intelligence to interpret large datasets. The Space Enabled Research Group (MIT) and collaborators design Decision Support Systems that use biodiversity data to inform policy and estimate the impacts on humans and wildlife. The presentation highlights three projects: 1) collecting data using active and passive satellite, airborne and water-based sensors to monitor an invasive plant in Benin; 2) using government and commercial satellite data to estimate and validate findings on deforestation due to mining in Ghana; and 3) combining field data and satellite observation to map biodiversity and socioeconomic change in mangrove forests in Brazil. In each of these examples, the analysis asks how human actions such as deforestation, fishing, and fires influence biodiversity. Experience from these projects reveals patterns that may be common. First, the projects seek to build information systems that meet local needs; this requires large investments of time by teams to exchange knowledge about local context. Second, the projects seek to build online tools with customized presentations of biodiversity data based on needs of local users. Simultaneously, the projects strive to make it easy to re-use the analytical framework for other geographic regions and application areas. Third, the projects apply tools from artificial intelligence and cloud computing to harness long-term data sets. The team also invests significant time to develop methods to quantify the errors when machine learning is used for classification. Fourth, these projects generate new data streams with low-cost sensors; this process can be complex to start in a new context. The presentation will highlight preliminary results from the ongoing research projects that illustrate how these patterns impact the biodiversity community.

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