Jayme Strange 20260128 Raster Digital Data Set Online U.S. Geological Survey https://doi.org/10.5066/P9BLTSTZ In 2007, the U.S Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) program partnered with the Iowa Department of Natural Resources (IDNR) to collect FEMA-grade, bluff-to-bluff lidar for Navigation Pools 8-24 of the UMRS. In 2009, with American Recovery and Reinvestment (ARRA) funds awarded to UMRR, the remaining lidar for the Upper Mississippi River, to the confluence with the Ohio River, and the Illinois River was contracted. Data acquisition was completed in 2011. Lidar data are remotely sensed, high-resolution elevation data collected by airplane. The Upper Midwest Environmental Sciences Center is processing these data to create Digital Elevation Models (DEMs), 0.5 meter contour lines, and pool-wide hillshade images. Light Detection and Ranging (lidar) generates extremely accurate (vertical and horizontal) location information and has long been a desired product for the UMRS. Lidar data is used for 3D visualization, elevation based analysis and for feature extraction. Reflective surface data represents the DEM created by laser energy reflected from the first surface encountered by the laser pulse. Some energy may continue beyond this initial surface to be reflected by a subsequent surface as represented by the Last Return data. Intensity information is captured from the Reflective Surface pulse and indicates the relative energy returned to the sensor as compared to the energy transmitted. Points are classified as on ground surface or not on ground surface to support creation of a bare earth model from the data. 20091216 20111228 ground condition Complete None planned -90.771015199004 -90.123150841 39.018497335 38.779297845 USGS Thesaurus elevation lidar topography digital elevation models digital elevation models None elevation lidar laser topography digital elevation model DEM Surface Model USGS Metadata Identifier USGS:69728d65d4be024aa5bddf76 U.S. Department of Commerce, 1995, Countries, Dependencies, Areas of Special Sovereignty, and Their Principal Administrative Divisions (Federal Information Processing Standard (FIPS) 10-4): Washington, D.C., National Institute of Standards and Technology US Mississippi River State location Missouri Illinois Mississippi River Upper Mississippi River None. None. Jayme Strange U.S. Geological Survey Geographer mailing and physical

2630 Fanta Reed Road

La Crosse WI 54603 US 608-781-6290 jstrange@usgs.gov Sanborn Map Company, Inc., Western Air Maps, Inc, US Army Corps of Engineers Environment as of Metadata Creation: Microsoft [Unknown] Version 6.2 (Build 9200) ; Esri ArcGIS 10.6 (Build 8321) Service Pack N/A (Build N/A) No formal attribute accuracy tests were conducted. All DEMS were created from LAS data. All LAS formatted lidar data are validated using commercial GIS software to ensure proper formatting and loading before delivery. This validation procedure ensures that data on delivery media is in correct physical format and is readable.The extent of the digital elevation models do not match the lidar SAB (study area boundary) because the las tiles were clipped by the USACE before distributing the tiles to UMESC. Lidar raster data is visually inspected for completeness to ensure that any gaps between flight lines or loss of signal represents less than 5% of required collection area. Areas of open water where loss of lidar signal is common are corrected to the best estimate of water level at time of collection. Lidar is self-illuminating and has minimal cloud penetration capability. Water vapor in steam plumes or particulates in smoke may cause reflection of lidar signals and loss of elevation information beneath these plumes. Glass structures and roofs may appear transparent to the lidar signal and therefore may not register on the reflective surface. Some asphalt formulations have been shown to absorb topographic lidar wavelength energy resulting in "pitting" of roof surfaces using this material. Contracted to meet 1 meter (RMSE) horizontal accuracy. Contracted to meet 18.5cm (RMSE) on open bare terrain and 37cm (RMSE) in vegetative areas. Western Air Maps used testing procedures consistent with those specified in the National Standard for Spatial Data Accuracy (NSSDA) resulting in a tested vertical accuracy (preliminary checkpoint results located in various vegetation classifications yielded 15 cm (RMS) at 95% confidence level. Sanborn Map Company, Inc., Western Air Maps, Inc 2011 Digital and/or Hardcopy Resources Rock Island, IL USACOE na Digital and/or Hardcopy Resources 20091216 20111228 ground condition Source Input 1 Source information used in support of the development of the data set. Merrick & Co 2008 Las Jefferson City, Missouri Merrick & Co na Digital and/or Hardcopy Resources 20081113 20081118 ground condition Source Input 2 Missouri County Lidar Data Data Collection: Using a Leica ALS 50 Light Detection and Ranging (lidar) system, flight lines of standard density (FEMA grade 1.4-meter ground sample distance) data were collected as part of the project 2000 square mile corridor expanding the Mississippi River from Illinois to Missouri. Multiple returns were recorded for each laser pulse along with an intensity value for each return. During the lidar campaign, the field crew conducted a GPS field survey to establish final coordinates of the ground base stations for final processing of the base-remote GPS solutions. Airborne global positioning system (GPS) base stations were used to support the lidar data acquisition. 200801 Airborne GPS Processing: Airborne GPS data was differentially processed and integrated with the post processed IMU data to derive a smoothed best estimate of trajectory (SBET). The SBET was used to reduce the lidar slant range measurements to a raw reflective surface for each flight line. The overlap between flight lines was removed to provide a homogeneous coverage, and the coverage was classified to extract a bare earth digital elevation model (DEM). Airborne GPS is differentially processed using the GrafNAV V7.50 software by Waypoint Consulting of Calgary, Alberta, Canada. The PDOP and distance separation is as follows: IMU data is processed using the PosPac V4.2 software by Applanix Corporation of Richmond Hill, Ontario, Canada. The reflective surface is derived using the ALS Post Processor software by Leica Geosystems GIS & Mapping Division of Atlanta, Georgia. The classification and quality control (QC) of lidar data is carried out using TerraScan software by Terrasolid Limited of Helinski, Finland. 2008 IMU data Processing: IMU data provides information concerning roll, pitch and yaw of airplane during collection event. IMU information allows the pulse vector to be properly placed in 3D space allowing the distance from the aircraft reference point to be properly positioned on the elevation model surface. IMU data is processed using the PosPac V4.2 software by Applanix Corporation of Richmond Hill, Ontario, Canada. 2008 Reflective Surface Generation: The reflective surface is derived using the ALS Post Processor software by Leica Geosystems GIS & Mapping Division of Atlanta, Georgia. 2008 Lidar Point Classification The classification and quality control of lidar data is carried out using TerraScan software by Terrasolid Limited of Helinski, Finland. 2008 Output LAS Files Random lidar points maintained in UTM coordinate system converted to Geographic projection with units of Meters. Assigned point class, "unclassified" = 1; "ground" = 2. 2008 Water surfaces were hydroflattened using breaklines. 201505 LAS files were converted to first return DEM by using LP360 lidar point cloud processing software. DEM was clipped down to study area boundary. 20200113 Unknown Raster Grid Cell 25016 55535 1 Universal Transverse Mercator 15 0.9996 -93.0 0.0 500000.0 0.0 row and column 1.0 1.0 METERS D_North_American_1983 GRS_1980 6378137.0 298.257222101 Attribute Table Table containing attribute information associated with the data set. Producer defined Value Raster Value Producer defined 81.772850036621 1978.6984863281 Meter The entity and attribute information provided here describes the tabular data associated with the data set. Please review the detailed descriptions that are provided (the individual attribute descriptions) for information on the values that appear as fields/table entries of the data set. The entity and attribute information was generated by the individual and/or agency identified as the originator of the data set. Please review the rest of the metadata record for additional details and information. U.S. Geological Survey - ScienceBase mailing and physical

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 USA 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 for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. 20260128 Jayme M Strange U.S. Geological Survey, MIDCONTINENT REGION Geographer mailing and physical

2630 Fanta Reed Road

La Crosse WI 54603 US 608-781-6290 N/A jstrange@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 local time http://www.Esri.com/metadata/Esriprof80.html ESRI Metadata Profile