Tuesday, July 27, 2021 from 12:00 PM to 1:30 PM (PDT)
California Water Data Consortium
The California Water Data Consortium is a nonprofit organization that supports data-informed decision-making in California about water in the face of climate change and other pressures on water resources. We amplify efforts to improve water data infrastructure by creating a neutral organizational space to build trust and facilitate collaboration across sectors.
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Data for Lunch Series
This event is part of the Consortium’s Data for Lunch series, which provides an opportunity to learn about innovative water data-related projects.
Date: July 27th from 12 – 1:00 pm, with additional Q&A from 1-1:30pm
Presenters: Dr. Tony Hale
- Welcome and introduction (10 mins)
- Presentation by Dr. Tony Hale (30 mins)
- Facilitated discussion (15 mins)
- Additional Q&A time (30 mins)
The San Francisco Estuary Institute and Southern California Coastal Water Research Project, with funding from the Ocean Protection Council and the California Department of Public Health, conducted twin projects to determine the viability of detecting trash in creeks, rivers, and streams from the skies above Northern and Southern California. The team leveraged on-the-ground fieldwork to measure accuracy. Determining what could be seen from this new low-altitude perspective was valuable in itself, but the team also sought to address concerns regarding inefficiencies for monitoring trash in such environments. Could automation help promote faster and reasonably accurate delivery of data salient to management concerns?
This talk will share some of the findings and opportunities associated with UAS-based imagery, in particular in service of water quality management. The team analyzed the imagery to determine the observability of trash generally, while also developing solutions to detect cigarette butts. The results from these efforts offered new opportunities to measure the effectiveness of management actions. From these specific examples might be derived lessons that can apply to the broader application of such technologies to natural resource monitoring. The permitting challenges, piloting rules, and other constraints will apply more broadly. But against these constraints are balanced tremendous opportunities to address the mandates posed by the State Water Board’s Trash Amendments mandating further management actions to control trash.
Dr. Tony Hale worked in a range of corporate and educational organizations, as well as both private nonprofit and public institutions, before establishing himself as an environmental science technologist. As Program Director for Environmental Informatics, Dr. Hale represents five technical teams: Geographic Information Systems, Application Development, Data Services, IT Systems, and Design & Communications. He always pursues compelling ways to promote technology initiatives, environmental stewardship, and meaningful, collaborative innovations.
While completing his doctorate at UC Berkeley, Dr. Hale consulted in technology for several years before launching a career at Mills College where he eventually served four years as an IT Director. He then progressed to become head of the enterprise applications team for Peralta Community College District, the second-largest educational organization in the San Francisco Bay Area.
Making the transition to environmental science, Dr. Hale joined the California Ocean Science Trust and led the development of OceanSpaces, an online community to foster new knowledge of ocean health. He also served as member of several state-level committees including the California Coastal & Marine Geospatial Workgroup, Data Management Workgroup, and currently the Trash Monitoring Workgroup. In December 2018, he was selected to serve as a member of USEPA’s National Advisory Council for Environmental Policy and Technology.
With SFEI, Dr. Hale has advanced the Institute’s communications practices, overseen the development of new data visualization technologies, and partnered with state and federal agencies to address complex technology and data challenges.
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