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Mapping 3D floodplain forest understory and density of wild rice beds of UMRS with mobile mapping system to support UMESC research in landform characteristics, hydrologic position, and associated vegetation mapping

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By Upper Midwest Environmental Sciences Center May 17, 2022

The objectives of this project are to test new 3D mobile mapping equipment that could be used for future Upper Mississippi River System (UMRS) ecological research, specifically research in floodplain vegetation densities.

Majority of the field work and data processing will take place in fiscal year 2022, but the final data processing reporting out will be finalized in fiscal year 2023. Data collection will coincide with the University of Wisconsin – La Crosse (UWL) wild rice research sites (Image 1), data processing and reporting out will be completed by UMESC. Once the data is processed into a clean, usable point cloud, the vegetation density will be measured.

pool 8, UMRS, reference map, Mississippi River
Sources/Usage: Public Domain. View Media Details
Study area boundaries of wild rice beds found within Pool 8 of the Upper Mississippi River.

For example, vegetation density can be expressed as Plant Area Index (PAI), which refers to the total aboveground vegetation surface material area, including both leaf and wood areas, onto a horizontal plane (Grau, 2017). “Voxelization” is a commonly used computation of a 3D matrix of voxels that come from terrestrial lidar system point clouds (Grau et al, 2017). Vegetation density can be computed based on the number of echoes inside each voxel.

Tree canopies captured at the Upper Midwest Environmental Sciences Center.
Sources/Usage: Public Domain. View Media Details
Tree canopies captured at the Upper Midwest Environmental Sciences Center. This is an example of what the 3D Mobile Mapping unit captures when out in the field.

Expected Products:

  • USGS ScienceBase data release of compiled:
    • Rasters: digital surface model of study areas.
    • Shapefiles: Study area boundary that contains density and species information.

References:

Grau, E., Durrieu, S., Fournier, R., Gestellu-Etchegorry, J.P., Yin, T. (2017). Estimation of 3D Vegetation density with Terrestrial Laser Scanning data using voxels. A sensitivity analysis of influencing parameters. Remote Sensing of Environment, 191(2017), 373-388. http://dx.doi.org/10.1016/j.rse.2017.01.032

The objectives of this project are to test new 3D mobile mapping equipment that could be used for future Upper Mississippi River System (UMRS) ecological research, specifically research in floodplain vegetation densities.

Majority of the field work and data processing will take place in fiscal year 2022, but the final data processing reporting out will be finalized in fiscal year 2023. Data collection will coincide with the University of Wisconsin – La Crosse (UWL) wild rice research sites (Image 1), data processing and reporting out will be completed by UMESC. Once the data is processed into a clean, usable point cloud, the vegetation density will be measured.

pool 8, UMRS, reference map, Mississippi River
Sources/Usage: Public Domain. View Media Details
Study area boundaries of wild rice beds found within Pool 8 of the Upper Mississippi River.

For example, vegetation density can be expressed as Plant Area Index (PAI), which refers to the total aboveground vegetation surface material area, including both leaf and wood areas, onto a horizontal plane (Grau, 2017). “Voxelization” is a commonly used computation of a 3D matrix of voxels that come from terrestrial lidar system point clouds (Grau et al, 2017). Vegetation density can be computed based on the number of echoes inside each voxel.

Tree canopies captured at the Upper Midwest Environmental Sciences Center.
Sources/Usage: Public Domain. View Media Details
Tree canopies captured at the Upper Midwest Environmental Sciences Center. This is an example of what the 3D Mobile Mapping unit captures when out in the field.

Expected Products:

  • USGS ScienceBase data release of compiled:
    • Rasters: digital surface model of study areas.
    • Shapefiles: Study area boundary that contains density and species information.

References:

Grau, E., Durrieu, S., Fournier, R., Gestellu-Etchegorry, J.P., Yin, T. (2017). Estimation of 3D Vegetation density with Terrestrial Laser Scanning data using voxels. A sensitivity analysis of influencing parameters. Remote Sensing of Environment, 191(2017), 373-388. http://dx.doi.org/10.1016/j.rse.2017.01.032

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