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Object-Based Image Analysis Detection of Aquatic Vegetation, Lake Erie, 2018

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Hanson, J.L., and Hoy, E.E., 2021, Object-Based Image Analysis Detection of Aquatic Vegetation, Lake Erie, 2018: U.S. Geological Survey data release, https://doi.org/10.5066/P936I3YN.

Summary

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 < 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 [...]

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Purpose

These efforts contribute to the assessment of long-term impacts of grass carp on vegetation communities throughout Lake Erie and the impact this may have on other organisms in the ecosystem. Additionally, they can inform the deployment of grass carp-specific attractants or deterrents used in management context. Attractant or deterrent deployments can be strategically placed on the spatial distribution and diet preferences of grass carp to maximize control efforts while reducing impacts to native species.

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ScienceBase WMS

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  • USGS Data Release Products
  • Upper Midwest Environmental Sciences Center (UMESC)

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Harvest Set
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DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P936I3YN

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