Computational Tools and Services
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: 119
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
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
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 proje
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
Waterbody Rapid Assessment Tool (WaterRAT): 3-dimensional Visualization of High-Resolution Spatial Data
Autonomous Underwater Vehicles (AUVs) are instruments that collect water-quality, depth, and other data in waterbodies. They produce complex and massive datasets. There is currently no standard method to store, organize, process, quality-check, analyze, or visualize this data. The Waterbody Rapid Assessment Tool (WaterRAT) is aPython application that processes and displays water-quality data with
Using machine learning to map topographic-soil & densely-patterned sub-surface agricultural drainage (tile drains) from satellite imagery
In the mid-1800s, tile-drains were installed in poorly-drained soils of topographic lows as water management to protect cropland during wet conditions; consequently, estimations of tile-drain location have been based on soil series. Most tile drains are in the Midwest, however each state has farms with tile and tile-drain density has increased in the last decade. Where tile drains quickly remove w
Moving towards EarthMAP: Establishing linkages among USGS land use, water use, runoff, and recharge models
Understanding and anticipating change in dynamic Earth systems is vital for societal adaptation and welfare. USGS possesses the multidisciplinary capabilities to anticipate Earth systems change, yet our work is often bound within a single discipline and/or Mission Area. The proposed work breaks new ground in moving USGS towards an interdisciplinary predictive modeling framework. We are initially l
Developing a "fire-aware" stream gage network by integrating USGS enterprise databases
Wildfires affect streams and rivers when they burn vegetation and scorch the ground. This makes floods more likely to happen and reduces water quality. Public managers, first responders, fire scientists, and hydrologists need timely information before and after a fire to plan for floods and water treatment. This project will create a method to combine national fire databases with the StreamStats w
USGS Cloud Environment Cookbook
The cloud offers new and exciting opportunities for USGS employees to leverage computing resources and services that can quickly improve their workflows and reduce expenditures typically associated with establishing a comparable environment with physical infrastructure. However, due to the novelty of access to and use of the cloud environment, there is limited documentation and shared examples det
Using Jupyter Notebooks to tell data stories and create reproducible workflows
Increasingly, USGS scientists seek to share and collaborate while working on data and code. Furthermore, these scientists often require advanced computing resources. Jupyter Notebooks are one such tool for creating these workflows. The files are interactive, code “notebooks” which allow users to combine code and text in one document, enabling scientists to share the stories held within their data.
Implementing a Grassland Productivity Forecast Tool for the U.S. Southwest
Rangeland systems are some of our nation’s largest providers of agro-ecological services, sustaining plant productivity that is highly variable across seasons and years. Although the ability to predict the upcoming growing season’s rangeland productivity would have enormous economic and management value – such as for making decisions about cattle stocking rates, fire, restoration, and wildlife – t
Coupling Hydrologic Models with Data Services in an Interoperable Modeling Framework
Computational models are important tools that aid process understanding, hypothesis testing, and data interpretation. The ability to easily couple models from various domains such as, surface-water and groundwater, to form integrated models will aid studies in water resources. This project investigates the use of the Community Surface Dynamics Modeling System (CSDMS) Modeling Framework (CMF) to