Session Convener(s): Sudhir Raj Shrestha (Esri), Ana Pinheiro Privette (Amazon) and Joe Flasher (AWS) Session recording
here.
Session Description:Sustainability’s geospatial processes are complex since environmental, societal, and economic systems are deeply interconnected. This creates challenges for researchers working in this field because the impact from changes in one system are not always well understood or predictable for the other systems. As a result, extracting timely and meaningful insights for sustainable environmental decision making often requires large datasets from many different domains, and tools capable of capturing the multidimensional nature of the problem. To address these challenges, many users are exploring the use of cloud computing to leverage its scalable storage and geospatial analytical capabilities. In this session, we are soliciting presentations that utilizes cloud-based workflows and applications of GIS technology to derive insights for sustainability.
PresentationsTitle: Amazon Sustainability Data Initiative: promoting innovation and problem solving for sustainability
Presenter: Ana Pinheiro Privette (Amazon)
Abstract: Last December, Amazon launched its Sustainability Data Initiative (ASDI) to promote sustainability research, innovation, and problem-solving by making key data easily accessible and even more widely available. ASDI Initiative leverages Amazon Web Services’ technology and scalable infrastructure to stage, analyze, and distribute data. The initiative identifies foundational data for sustainability and works closely with data providers like NOAA, NASA and the UK Met Office to stage their data in the AWS Cloud by giving them complete ownership and control over how their data is shared. While these datasets have always been freely available, they aren’t always easily accessible and researchers may not have the compute power necessary to take advantage of these resources through their own on-premises data centers. To encourage application development, researchers can apply for AWS Promotional Credits through the AWS Cloud Credits for Research program. Offsetting these costs will encourage experimentation and promote innovative solutions. Amazon believes that providing easier access to massive datasets (i.e. petabyte-scale) in the cloud and providing access to analytical tools will help researchers and innovators address a wide range of sustainability challenges, such as the impacts of climate change and weather extremes.
Contact the ASDI team if you would like to learn more or get involved!
Title: Blue Dot Water Observatory
Presenter: Grega Milcinski (Sinergise)
Abstract: Water lies at the heart of economic and social development. As it is becoming scarce, stakeholders need innovative ways to better understand water conditions, predict risks, and tackle problems. Cost-effective, yet reliable solutions for monitoring water resources are needed, as ground-based monitoring networks are often too costly and due to networks deterioration in some cases also unreliable. This is even more true for developing countries.
Being enlightened by JRC’s Global Surface Water project we have built a service, which does not only show historic data but is also up-to-date. Copernicus Sentinel mission, with its global coverage and short revisit time, combined with an efficient use of AWS infrastructure resources makes it feasible to do a global scale project with limited resources. The Blue Dot Water Observatory is an EO-based solution that provides reliable and timely information about surface water levels of water bodies across the globe.
With this service, we also wish to demonstrate how global monitoring of the environment
using Earth observation data can be done efficiently and orders of magnitude cheaper than before, if done in an intelligent way. To make it possible to others to build on top of our experience, we share all the code as an open-source.
Slides: https://doi.org/10.6084/m9.figshare.9121994Title: Systematic Data Transformation to Enable ArcGIS Image Services and Web Coverage Services (WCS) within the NASA Earth Science Data System’s Cloud
Presenter: Jason Barnett (Booz Allen Hamilton)
Abstract: This presentation will provide an overview of current efforts underway to develop and deploy scalable Amazon Web Services (AWS) Step Functions and serverless Lambda Functions in order to orchestrate a workflow of customized micro-services executing GDAL transformations in order to geospatially enable and serve new cloud-optimized MetaRaster Format (MRF) NASA Earth science data products. These analysis-ready data products will be served to end users as cloud-based multidimensional ArcGIS Image Services and OGC Web Coverage Services, to be eventually discoverable within catalogs such as NASA Earthdata Search, NASA ArcGIS Online, Esri Living Atlas, etc. Thus, enabling NASA Earth Science datasets to be usable inputs for analysis within ArcGIS, QGIS, custom web mapping applications and enable the ability to derive insights for sustainability across multiple domains.
Title: Understanding Bob the bias by using true diversity of thought
Presenter: Alexis Hannah Smith (IMGeospatial)
Abstract: IMGeospatial is in development of an open source QA app that will be used on android devices to provide a Proof of Concept for our central objective: namely the participation in quality assuring and validation of extracted features from remote-sensed data undertaken by individuals who sign up to our scheme. This project forms part of a wider collaboration with the European Space Agency (ESA), Anglian Water, Affinity Water and the World Bank. Our motivation is to clearly demonstrate that a freelancer sitting outside his or her dwelling in the heart of an African desert, in a Finnish forest (or indeed anywhere) can be part of, and make a significant contribution to, the AI revolution. At the same time also enriching the lives of those in our global community who need support from the developed world. IMGeospatial believes that by developing and deploying this system using true diversity of thought, we can not only improve the quality of AI-derived data for the whole community, but also understand and measure the dormant devil, Bob the Bias.
Title: Improving Information and Communications in a Disaster Scenario with AWS Snowball Edge
Presenter: Dan Pilone (Element 84)
Abstract: Volunteers and emergency personnel carefully coordinate their response to natural disasters. This coordination requires data and making data actionable and accessible at the tactical edge remains a challenge. We'll give a quick overview of the results of our disaster response user needs study and demonstrate a prototype disaster response pipeline for field data management. The serverless, cloud-based pipeline combines public and private data sources with open source software. It can provide the field with a ruggedized remote data center (AWS Snowball Edge), preloaded with critical information, including reach-back capabilities. You'll see how this works and learn ways first responders can update data from in-situ sources such as drones.
Title: Upstream Ancillary Ingest: Keep Up Best You Can
Presenter: Namrata Malarout (JPL)
Abstract: The ARIA project generates products process
