The Environmental Health Program collaborates with scientists within the Geospatial Analyses and Applications Team to develop and apply geospatial analytical methods to answer broad-scale questions about source-sink and cause-effect relationships between contaminants and vulnerable communities. Multivariate statistics are used to identify connections between landscape gradients and observational data. These connections are used to develop risk assessments and make predictions across broad, regional scales.
Key Analytical Capabilities
- Study site selection and characterization
- Risk assessment – real vs. perceived
- Custom metric development
- Multivariate statistics
- Big-data analysis
- Landscape analysis
- Hydrological modelling and analysis
- Geomorphic assessment
- Lidar and Remote Sensing
Analytical Tools and Products
- Statistical analysis in R
- Field-form development
- Database design and development
- Geo-narratives and Web Applications
- ScienceBase and metadata creation
- ArcGIS, GRASS, Python, GitHub†
† Hypertext links to non-USGS products and services; and the use of trade names, trademarks, company names, or other references to non-USGS products and services are provided for information only and do not constitute endorsement or warranty by the U.S. Geological Survey (USGS), U.S. Department of the Interior, or U.S. Government.
- Overview
About the Research
The Environmental Health Program collaborates with scientists within the Geospatial Analyses and Applications Team to develop and apply geospatial analytical methods to answer broad-scale questions about source-sink and cause-effect relationships between contaminants and vulnerable communities. Multivariate statistics are used to identify connections between landscape gradients and observational data. These connections are used to develop risk assessments and make predictions across broad, regional scales.
Attribution of storm-weighted potential contaminant hazard ranks to sampling locations in the Sediment-Bound Contaminant Resiliency and Response (SCoRR) network. Figure 6 from USGS Open-File Report 2015-1188A.(Public domain.) Key Analytical Capabilities
- Study site selection and characterization
- Risk assessment – real vs. perceived
- Custom metric development
- Multivariate statistics
- Big-data analysis
- Landscape analysis
- Hydrological modelling and analysis
- Geomorphic assessment
- Lidar and Remote Sensing
Generalized schematic detailing the steps in the USGS decision support tool for prioritizing sampling locations based on perceived environmental hazards.(Public domain.) Screen shot of the Sediment-Bound Contaminant Resiliency and Response (SCoRR) Web site. U.S. Geological Survey (USGS) scientists have developed Web applications to visualize data and help coordinate sampling efforts.(Public domain.) Analytical Tools and Products
- Statistical analysis in R
- Field-form development
- Database design and development
- Geo-narratives and Web Applications
- ScienceBase and metadata creation
- ArcGIS, GRASS, Python, GitHub†
Two maps of the Chesapeake Bay Watershed showing locations of septic systems (left) and regulated facilities (right). Extensive databases detailing contaminant sources from local, state, and federal partners are used to understand source-sink linkages with observational field data.(Credit: Stephanie Gordon, USGS. Public domain.) Tablet-enabled field forms have been developed to help coordinate field efforts, collect site information, GPS coordinates, photos, and control data collection.(Credit: Shawn Fisher, USGS. Public domain.) † Hypertext links to non-USGS products and services; and the use of trade names, trademarks, company names, or other references to non-USGS products and services are provided for information only and do not constitute endorsement or warranty by the U.S. Geological Survey (USGS), U.S. Department of the Interior, or U.S. Government.