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Computational Tools and Services

CDI projects tagged with Computational Tools and Services. Computational tools and services include applications, Web services, data discovery tools, models, semantic services and tools, infrastructure, data brokers, and visualization tools.

Filter Total Items: 128

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

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

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

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

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

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

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

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

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
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Processing a new generation of hyperspectral data on the Cloud using Pangeo

We aim to migrate our research workflow from a closed system to an open framework, increasing flexibility and transparency in our science and accessibility of our data. Our hyperspectral data of agricultural crops are crucial for training/ validating machine learning algorithms to study food security, land use, etc. Generating such data is resource-intensive and requires expertise...
Processing a new generation of hyperspectral data on the Cloud using Pangeo

Processing a new generation of hyperspectral data on the Cloud using Pangeo

We aim to migrate our research workflow from a closed system to an open framework, increasing flexibility and transparency in our science and accessibility of our data. Our hyperspectral data of agricultural crops are crucial for training/ validating machine learning algorithms to study food security, land use, etc. Generating such data is resource-intensive and requires expertise, proprietary
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Real-time Coastal Salinity Index for monitoring coastal drought and ecological response to changing salinity values

Many coastal areas are experiencing departures from normal conditions due to changing land use and climate patterns, including increased frequency, severity, or duration of floods and droughts, in some cases combinations of the two. To address these issues, the U.S. Geological Survey developed the Coastal Salinity Index (CSI) to identify and communicate fluctuating salinity conditions...
Real-time Coastal Salinity Index for monitoring coastal drought and ecological response to changing salinity values

Real-time Coastal Salinity Index for monitoring coastal drought and ecological response to changing salinity values

Many coastal areas are experiencing departures from normal conditions due to changing land use and climate patterns, including increased frequency, severity, or duration of floods and droughts, in some cases combinations of the two. To address these issues, the U.S. Geological Survey developed the Coastal Salinity Index (CSI) to identify and communicate fluctuating salinity conditions due to such
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Enabling AI for citizen science in fish ecology

Artificial Intelligence (AI) is revolutionizing ecology and conservation by enabling species recognition from photos and videos. Our project evaluates the capacity to expand AI for individual fish recognition for population assessment. The success of this effort would facilitate fisheries analysis at an unprecedented scale by engaging anglers and citizen scientists in imagery collection...
Enabling AI for citizen science in fish ecology

Enabling AI for citizen science in fish ecology

Artificial Intelligence (AI) is revolutionizing ecology and conservation by enabling species recognition from photos and videos. Our project evaluates the capacity to expand AI for individual fish recognition for population assessment. The success of this effort would facilitate fisheries analysis at an unprecedented scale by engaging anglers and citizen scientists in imagery collection.This
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GrassCast: A multi-agency tool using remote sensing, modeling, and on-the-ground science to forecast grassland productivity in the Southwest

Rangeland ecosystems are one of the largest single providers of agro-ecological services in the U.S. The plant growth of these rangelands helps determine the amount of forage available for our livestock and for wildlife, as well as information about fire likelihood and restoration opportunities. However, every spring, ranchers and other rangeland managers face the same difficult...
GrassCast: A multi-agency tool using remote sensing, modeling, and on-the-ground science to forecast grassland productivity in the Southwest

GrassCast: A multi-agency tool using remote sensing, modeling, and on-the-ground science to forecast grassland productivity in the Southwest

Rangeland ecosystems are one of the largest single providers of agro-ecological services in the U.S. The plant growth of these rangelands helps determine the amount of forage available for our livestock and for wildlife, as well as information about fire likelihood and restoration opportunities. However, every spring, ranchers and other rangeland managers face the same difficult challenge —trying
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