Community for Data Integration (CDI)

All Funded Projects

Filter Total Items: 119
Date published: April 2, 2021
Status: Active

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...

Date published: April 2, 2021
Status: Active

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...

Date published: April 2, 2021
Status: Active

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...

Date published: April 2, 2021
Status: Active

Development of a web-based tool for coastal water resources management

The sustainability of coastal water resources is being affected by climate change, sea level rise, and modifications to land use and hydrologic systems. To prepare for and respond to these drivers of hydrologic change, coastal water managers need real-time data, an understanding of temporal trends, and information about how current and historical data compare. Coastal water managers often must...

Date published: April 2, 2021
Status: Active

Advancing Post-Fire Debris Flow Hazard Science with a Field Deployable Mapping Tool

Mapping the occurrence of post-fire flooding and debris flow is crucial for 1) integrating observations into models used to define rainfall thresholds for early warning, 2) understanding patterns of inundation, and 3) improving models for predictive hazard assessment. Despite the critical role mapping plays in post-fire hazard assessment and early warning, there has not been a standardized...

Date published: April 2, 2021
Status: Active

Diverse data to improve Southwest fire forecasts: Joining novel remote sensing, post-fire dynamics, and intra-annual precipitation patterns

Fire has increased dramatically across the western U.S.and these increases are expected to continue. With this reality, it is critical that we improve our ability to forecast the timing, extent, and intensity of fire to provide resource managers and policy makers the information needed for effective decisions. For example, an advanced, spatially-explicit prediction of the upcoming fire season...

Date published: April 2, 2021
Status: Active

Delivering the North American tree-ring fire history network through a web application and an R package

Wildfires are increasing across the western U.S., causing damage to ecosystems and communities. Addressing the fire problem requires understanding the trends and drivers of fire, yet most fire data is limited only to recent decades. Tree-ring fire scars provide fire records spanning 300-500 years, yet these data are largely inaccessible to potential users. Our project will deliver the newly...

Date published: April 2, 2021
Status: Active

GIS Clipping and Summarization Tool for Points, Lines, Polygons, and Rasters

Geographic Information System (GIS) analyses are an essential part of natural resource management and research. Calculating and summarizing data within intersecting GIS layers is common practice for analysts and researchers. However, the various tools and steps required to complete this process are slow and tedious, requiring many tools iterating over hundreds, or even thousands of datasets....

Date published: April 2, 2021
Status: Active

Landsat-derived fire history metrics to provide critical information for prioritizing prescribed fire across the Southeast

Detailed information about past fire history is critical for understanding fire impacts and risk, as well as prioritizing conservation and fire management actions. Yet, fire history information is neither consistently nor routinely tracked by many agencies and states, especially on private lands in the Southeast. Remote sensing data products offer opportunities to do so but require...

Date published: April 2, 2021
Status: Active

Modernizing sensor data workflows to leverage Internet of Things (IoT) and cloud-based technologies

Drought is a major problem in the American Southwest that is expected to worsen under the effects of climate change. Currently, the Southwest Biological Science Center is monitoring the effects of drought with soil moisture probes in a range of ecosystems across an elevational gradient on the Colorado Plateau. These data are used in multiple studies to analyze the effects of drought on...

Date published: April 2, 2021
Status: Active

Making USGS/NOAA Total Water Level and Coastal Change Forecast data accessible through user-friendly interfaces

The Total Water Level and Coastal Change Forecast delivers 6-day forecasts of hourly water levels and the probability of waves impacting dunes along 5000 km of sandy coasts along the Atlantic and Gulf of Mexico and will soon expand to the Pacific. These forecasts provide needed information to local governments and federal partners and are used by the USGS to place sensors before a storm. The...

Date published: April 2, 2021
Status: Active

From reactive- to condition-based maintenance: Artificial intelligence for anomaly predictions and operational decision-making

The USGS maintains an extensive monitoring network throughout the United States in order to protect the public and help manage natural resources. This network generates millions of data points each year, all of which must be evaluated and reviewed manually for quality assurance and control. Sensor malfunctions and issues can result in data losses and unexpected costs, and are typically only...