Jenny L. Hanson Jayme M. Strange Stephanie R. Sattler 20201124 raster digital data https://doi.org/10.5066/P9KY6JEJ Using high-resolution sonar technologies with geographic information systems (GIS) and object based image analysis, benthic characteristics of the Illinois River have been interpreted to support Asian carp research, monitoring, and control. The study plan consisted of data collection and analysis of the Brandon, Dresden, Starved Rock, Marseilles, Peoria, La Grange, and Alton reaches of the Illinois River. Reaches with larger aquatic areas (Peoria, La Grange and Alton), had areas prioritized for data collection and analysis. Remote sensing technologies, such as high-resolution sonars, can be used to collect detailed information about the benthic characteristics of macrohabitats in the Illinois River. Using a combination of multibeam sonar and side/down scan imaging, the objective is to describe macrohabitat features of benthic and pelagic habitats of the Illinois River that are preferentially used by Asian carp. This dataset is a characterization of the existing physical benthic habitat that includes the bed surface type and common fish habitat like woody debris and submersed vegetation at the time of multibeam collection (2017 - 2018). The benthic classification developed for this dataset was based on an assessment of combined datasets surveyed for the Illinois River. This included the bathymetry and derivatives, sidescan imagery, and underwater video captures. Classes were determined by viewing underwater videos with reference to the signature at each location on the image datasets. The sidescan sonar imagery and bathymetric hillshade show changes in topography and surficial sediment type. Object-based image analysis was used to characterize these changes in surficial substrate type and other habitat structures (i.e. woody debris, submersed vegetation, and anthropogenic features) of the Illinois River. Note that "bedrock" is a term used for any type of layered rock surface, including shale beds. A minimum mapping unit (MMU) of 10x10-meters was used for all classes except Rock, Wood, and Anthropogenic, where a 2x2-meter MMU was used in order to capture those smaller types of habitat. 20170824 20170825 20170911 20170912 20170913 20180523 ground condition Complete None planned -88.9790 -88.7644 41.3500 41.3103 ISO 19115 Topic Category biota USGS Thesaurus sidescan sonar image mosaics topography invasive species Marine Realms Information Bank (MRIB) keywords benthos river channel USGS Metadata Identifier USGS:61cce1fad34ed79293fc64e9 Common geographic areas Illinois Starved Rock None. Please see 'Distribution Info' for details. None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Jenny L Hanson U.S. Geological Survey, MIDCONTINENT REGION Biologist mailing address

2630 Fanta Reed Road

La Crosse WI 54603 US 608-781-6372 608-783-8058 jhanson@usgs.gov Funding for the project was provided by the Great Lakes Restoration Initiative (GLRI). Windows 10 Enterrprise (version 1809); Esri ArcGIS 10.7.1 (Build 11595); Hypack 2018; Trimble eCognition (version 9.5), and QGIS (version 3.6.3). Jenny L Hanson Jayme M. Stone Erin Hoy Stephanie R. Sattler 20181002 raster digital data Jenny L. Hanson, and Jayme M. Stone, 20181002, Illinois River, Starved Rock, Sidescan Image Mosaic, 2017-2018: U.S. Geological Survey data release, https://doi.org/10.5066/P9IHNSFT. https://www.sciencebase.gov/catalog/item/5d753e62e4b0c4f70d01a7f3 Jayme M. Stone Jenny L. Hanson Stephanie R. Sattler 20190908 raster digital data Jayme Stone, Jenny Hanson, and Stephanie Sattler, 2019, Illinois River, Starved Rock, Multibeam Bathymetry, May 2018: U.S. Geological Survey data release, https://doi.org/10.5066/P97HJ8Q5. https://www.sciencebase.gov/catalog/item/5b3fb1a5e4b060350a10be7b No formal attribute accuracy tests were conducted. No formal logical accuracy tests were conducted. Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. A formal accuracy assessment of the horizontal positional information in the data set has not been conducted. A formal accuracy assessment of the vertical positional information in the data set has either not been conducted, or is not applicable. High-resolution multibeam data (400-kHz) was developed into bathymetric derivatives and sidescan imagery. The Benthic Terrain Modeler toolbox in ArcGIS (Walbridge and others, 2018) was used to derive Vector Ruggedness Measure (VRM) and Slope. The VRM is a tool that measures terrain ruggedness as the variation in three-dimensional orientation of grid cells within a neighborhood. Ruggedness values in the output raster can range from 0 (no terrain variation) to 1 (complete terrain variation). The slope tool calculates the gradient or rate of maximum change in z-value from each cell of a surface raster in degree units. QGIS was used to derive Roughness, Topographic Position Index (TPI), and a Terrain Ruggedness Index (TRI). These raster datasets were analyzed in ArcMap to determine which rasters have the greatest detail to help classify substrate type. For this pool, all raster types were used. Walbridge, S.; Slocum, N.; Pobuda, M.; Wright, D.J. Unified Geomorphological Analysis Workflows with Benthic Terrain Modeler. Geosciences 2018, 8, 94. doi:10.3390/geosciences8030094 20200520 Underwater videos were captured on September 11-12, 2019 at random locations. Random site locations were determined by the number of hectares per pool. For each hectare, one underwater video was recorded. Where the depth exceeded the length of the telescoping pole, a ponar grab was used to collect a substrate sample. Ponar grabs were documented using a camera. All underwater videos were assessed at each random location. A point vector shapefile was developed that captured the details and interpreted class at each location. 20200605 Image datasets (Roughness, VRM, Slope, TRI, and TPI) and the bed observations shapefile were analyzed using the object-based image analysis from Trimble eCognition Developer (version 9.5). First the image was classified into two categories: bedrock and sand. A multiresolution segmentation was performed using the scale parameter of 100 and image layers were given weights. Composition parameters were 0.1 for shape, and 0.9 for compactness. The sample editor was used to select samples according to the thematic layer (bed observations). A Nearest Neighbor classification was applied using mean and standard deviation layer values for the object features. Next a second mulitresolution was conducted for each class of bedrock and sand, using the scale of 42, composition parameter of 0.1, and 0.9 for compactness. Further analysis was completed using an unsupervised approach, by applying thresholds of the mean layer values to help classify range of classes. A merge region was completed for each class, and a minimum mapping unit (mmu) of 2-square meters was applied for the rock and wood classes. A second mmu of 10x10-meters was applied to the remaining classes by the remove objects algorithm. The vector layer was exported as a polygon shapefile. 20200620 The shapefile was imported into ArcMap to check for misclassification errors. Further editing was completed manually. Anthropogenic areas were manually digitized. Once the substrate map was satisfactory, the map underwent topology. The final step was a review for anomalies and accuracy. 20200628 Vector G-polygon 2810 Universal Transverse Mercator 15 0.9996 -93.0 0.0 500000.0 0.0 coordinate pair 0.6096 0.6096 meters North_American_Datum_1983 GRS_1980 6378137.0 298.257222101 Sta_substrate.shp Attribute Table Table containing attribute information associated with the data set. Producer Defined FID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Coordinates defining the features. Class Class used to describe the substrate at that location. Producer Defined A Anthropogenic (man-made structure) Producer defined B Bedrock (any layered or flat rock like surface; this includes shale beds) Producer defined S Sand (consists mostly of sand) Producer defined B-R Bedrock-Rock mix (rock larger than gravel lying on or between layered bedrock) Producer defined G Gravel (area of gravel bed) Producer defined R Rock (rock larger than gravel size) Producer defined M Mud (area consisting of silty-clay mixture, may contain some sand) Producer defined S-G Sand-Gravel mix (area consisting largely of sand and gravel mix) Producer defined S-R Sand-Rock mix (area consisting mostly of sand, but with some larger rock mixed in) Producer defined V Vegetation (submersed) Producer defined W Wood (debris pile or log) Producer defined Perimeter Measure of the boundary of the polygon. Producer Defined 5.75999999791 91086.2529551 meter Area Measure of the surface area computed as a 2D polygon. Producer Defined 2.04159999859 1193858.20772 square meters Acres Measurement or unit of surface area. Producer Defined 0.000504490346454 295.008787836 acre Hectares Metric unit of measure. Producer Defined 0.000204159999859 119.385820772 hectare U.S. Geological Survey GS ScienceBase mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Digital Data https://doi.org/10.5066/P9KY6JEJ 20260409 Jenny L Hanson U.S. Geological Survey, MIDCONTINENT REGION Biologist mailing address

2630 Fanta Reed Road

La Crosse WI 54603 US 608-781-6372 608-783-8058 jhanson@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998