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Community for Data Integration (CDI)

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The Community for Data Integration (CDI) is a dynamic community of practice working together to grow USGS knowledge and capacity in scientific data and information management and integration.

News

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January 12, 2022 CDI Monthly Meeting

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November 10, 2021 CDI Monthly Meeting

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October 13, 2021 CDI Monthly Meeting

Publications

Community for Data Integration 2019 annual report

The Community for Data Integration is a community of practice whose purpose is to advance the U.S. Geological Survey’s data integration capabilities. In fiscal year 2019, the Community for Data Integration held 9 monthly forums, facilitated 11 collaboration areas, held several workshops and training events, and funded 14 projects. The activities supported the U.S. Geological Survey priorities of e

U.S. Geological Survey Community for Data Integration 2019 Workshop Proceedings—From big data to smart data

The U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held during June 3–7, 2019, at Center Green in Boulder, Colo. The theme of the workshop was “From Big Data to Smart Data” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps forward to advance twenty-first century science at the USGS. The workshop agenda was d

Community for data integration 2018 funded project report

The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 10 projects funded in fiscal year 2018, outlining their goals, activities, and accomplishments.

Science

Coast Train: Massive Library of Labeled Coastal Images to Train Machine Learning for Coastal Hazards and Resources

Scientists who study coastal ecosystems and hazards such as hurricanes, flooding, and cliff failure collect lots of photographs of coastal environments from airplanes and drones. A large area can be surveyed at high resolution and low cost. Additionally, satellites such as Landsat have provided imagery of the Nation’s coastlines every few days for decades. Scientist’s ability to understand coastal...
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Coast Train: Massive Library of Labeled Coastal Images to Train Machine Learning for Coastal Hazards and Resources

Scientists who study coastal ecosystems and hazards such as hurricanes, flooding, and cliff failure collect lots of photographs of coastal environments from airplanes and drones. A large area can be surveyed at high resolution and low cost. Additionally, satellites such as Landsat have provided imagery of the Nation’s coastlines every few days for decades. Scientist’s ability to understand coastal...
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Improving forest structure mapping andregeneration prediction with multi-scale lidar observations

To make informed decisions, land managers require knowledge about the state of the ecosystems present. Vegetation structure is a key indicator of the state of forested systems; it influences habitat suitability, water quality and runoff, microclimate, and informs wildfire-related characteristics such as fuel loads, burn severity, and post-fire regeneration. Field data used to derive vegetation st
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Improving forest structure mapping andregeneration prediction with multi-scale lidar observations

To make informed decisions, land managers require knowledge about the state of the ecosystems present. Vegetation structure is a key indicator of the state of forested systems; it influences habitat suitability, water quality and runoff, microclimate, and informs wildfire-related characteristics such as fuel loads, burn severity, and post-fire regeneration. Field data used to derive vegetation st
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The Wildfire Trends Tool: A data visualization and analysis tool to meet land management needs and facilitate scientific inquiry

Fighting wildfires and reducing their negative effects on natural resources costs billions of dollars annually in the U.S. We will develop the Wildfire Trends Tool (WTT), a data visualization and analysis tool that will calculate and display wildfire trends and patterns for the western U.S. based on user-defined regions of interest, time periods, and ecosystem types. The WTT will be publicly avail
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The Wildfire Trends Tool: A data visualization and analysis tool to meet land management needs and facilitate scientific inquiry

Fighting wildfires and reducing their negative effects on natural resources costs billions of dollars annually in the U.S. We will develop the Wildfire Trends Tool (WTT), a data visualization and analysis tool that will calculate and display wildfire trends and patterns for the western U.S. based on user-defined regions of interest, time periods, and ecosystem types. The WTT will be publicly avail
Learn More