Object-Based Image Analysis Detection of Aquatic Vegetation, Lake Erie, 2018
January 20, 2021
The USGS developed the second in a series of informative spatial distribution datasets of submersed aquatic vegetation (SAV) in Lake Erie. The second dataset was developed by object-based image analysis of high-resolution imagery (US waters less than 6 meters deep) collected during peak biomass in 2018 to allow assessments of changes in SAV distribution. Assessing SAV abundance may contribute to inform the long-term impacts of Grass Carp, Common Carp, eutrophication, wind fetch and sedimentation on vegetation communities throughout Lake Erie and the impact these stressors may have on other organisms in the ecosystem. These data may also help inform the deployment of toxic bait deployments targeting Grass Carp. Bait placement can be strategically aligned with the spatial distribution and diet preferences of Grass carp to maximize control efforts while minimizing impacts to native species. These data provide a good baseline of SAV at an early point in the invasion/population growth curve for grass carp from which later assessments/models might project from, and are valuable for bioenergetic modeling efforts to project grass carp biomass or other species dependent on SAV.
Citation Information
Publication Year | 2021 |
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Title | Object-Based Image Analysis Detection of Aquatic Vegetation, Lake Erie, 2018 |
DOI | 10.5066/P936I3YN |
Authors | Jenny L Hanson, Erin E Hoy |
Product Type | Data Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Upper Midwest Environmental Sciences Center |
Rights | This work is marked with CC0 1.0 Universal |