Geomorphon landforms in the Bad River (Mashkiiziibii) Estuary, derived from 2019 lidar data
Landforms in the Bad River (Mashkiiziibii) Estuary were mapped with geomorphons, an automated terrain analysis method that classifies digital elevation model (DEM) cells into ten fundamental 3-dimensional geometric forms – summit, ridge, shoulder, spur, slope, hollow, footslope, valley, depression, and flat – based on the topography within the visibility neighborhood of each cell. The geomorphons were developed from a (DEM) comprising topographic and bathymetric data for the estuary, developed from elevation data collected by airborne topographic and bathymetric lidar and single-beam sonar. Resulting landform features were attributed with a variety of characteristics, including an array of morphometrics quantifying the detailed three-dimensional shape of each feature, and the hydrologic setting as characterized by the distance and orientation relative to the nearest National Hydrologic Dataset (NHD) river channel, and by the frequency and maximum depth of flooding according to an inundation mapping analysis. We used a subset of these attributes in a K-means multivariate statistical clustering analysis, identifying five groupings or process zones within the landform features, including river channels, leveed and un-leveed channel margins, estuary flats, and distal, convex-up features.
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| description | Landforms in the Bad River (Mashkiiziibii) Estuary were mapped with geomorphons, an automated terrain analysis method that classifies digital elevation model (DEM) cells into ten fundamental 3-dimensional geometric forms – summit, ridge, shoulder, spur, slope, hollow, footslope, valley, depression, and flat – based on the topography within the visibility neighborhood of each cell. The geomorphons were developed from a (DEM) comprising topographic and bathymetric data for the estuary, developed from elevation data collected by airborne topographic and bathymetric lidar and single-beam sonar. Resulting landform features were attributed with a variety of characteristics, including an array of morphometrics quantifying the detailed three-dimensional shape of each feature, and the hydrologic setting as characterized by the distance and orientation relative to the nearest National Hydrologic Dataset (NHD) river channel, and by the frequency and maximum depth of flooding according to an inundation mapping analysis. We used a subset of these attributes in a K-means multivariate statistical clustering analysis, identifying five groupings or process zones within the landform features, including river channels, leveed and un-leveed channel margins, estuary flats, and distal, convex-up features. |
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| identifier | http://datainventory.doi.gov/id/dataset/USGS_664f5ec1d34e702fe8747eba |
| keyword |
[
"Ashland County",
"Bad River",
"Chequamegon Bay",
"Coastal wetlands",
"Estuary",
"Floods",
"Geomorphology",
"Kakagon River",
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| modified | 2024-09-30T00:00:00Z |
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| spatial | -90.80530, 46.59210, -90.59450, 46.69120 |
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| title | Geomorphon landforms in the Bad River (Mashkiiziibii) Estuary, derived from 2019 lidar data |
