Software
Software
Filter Total Items: 33
SeeOtter: Improving software for AI-assisted processing of imagery for wildlife surveys
Expanding documentation, accessibility, and flexibility of a powerful AI tool for wildlife aerial photo-survey processing
Expansion of the Geophysical Survey (GS) data standard and open-source tools
Advancement of GS standard and GSPy software for improved functionality and interoperability of geophysical datasets
Beginners Git, GitLab & Software Release Carpentries-like Training for USGS Personnel to Facilitate Open Science
Teach USGS personnel Git within code.usgs.gov to develop, track, share, and publish their code.
Automated accuracy and quality assessment tools (AQAT = “a cat”) for generalized geospatial data
This project develops an open-source toolkit for the consistent, automated assessment of accuracy and cartographic quality of generalized geospatial data. The toolkit will aid USGS and other stakeholders with the development and use of multiscale data and with associated decision-making.
Informing the use of native plant materials in restoration and rehabilitation with the Native Plant Seed Mapping Toolkit
Restoring ecosystems using native plant materials is a critical pursuit of federal land management agencies following natural disasters and disturbances. The Native Plant Seed Mapping Toolkit provides practitioners with quantitative data to support successful restoration outcomes.
Extracting data from maps: applying lessons learned from the AI for Critical Mineral Assessment Competition
This project will share techniques developed in two AI/ML competitions run in Fall 2022, Automated Map Georeferencing, and Automated Map Feature Extraction with USGS stakeholders. We will develop a strategy to operationalize successful approaches, benefiting any activity that uses legacy map data.
Seg2Map: New Tools for ML-based Segmentation of Geospatial Imagery
This proposal would fund the development of Seg2Map, a new open-source, browser-accessible software deployed on the cloud that will apply Machine Learning to imagery and image time-series, to make highly customizable to study Earth’s changing surface for a range of scientific purposes.
CorVis: A lidar point cloud tool for visualization and analysis of corridors such as hydrologic, energy, and transportation networks
An open-source tool for 3D visualization of lidar point cloud data along a vector line network and output of related lidar metrics. This tool will make available the valuable attribute data of point clouds to enable research such as riparian zone and migration corridor vegetation structure analysis or characterizing the related built environment.
Database tools for standardization & automation of eDNA workflows
We propose to bring in expertise from multiple USGS environmental DNA (eDNA) labs to create a database to track samples from initial collection through analysis and reporting and to long-term storage. We will publish this tracking template so it can be implemented within eDNA labs across the USGS.
Enhancing Decision Support with Restoration Project Data Pipelines
Effectively documenting and distributing information about restoration projects is essential for measuring progress towards national conservation goals. We will improve the National Fish Habitat Partnership Project Tracking database by creating a data pipeline to compile project information and link data with other decision support tools.
Separating the land from the sea: image segmentation in support of coastal hazards research and community early warning systems
This proposal would fund the testing of quantitative methods for extracting total water level from imagery, with add-on applications including satellite shoreline detection, digital stream gauges, and flood detection. This project supports national scale USGS coastal hazards products.
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...