Maxwel F. Schwid Mackenzie K. Keith Brandon T. Overstreet 20250826 raster digital data https://doi.org/10.5066/P13V7HBC In cooperation with the U.S. Army Corps of Engineers (USACE), the U.S. Geological Survey (USGS) surveyed ground control points and coordinated aerial photograph acquisition of Cougar Reservoir, a multi-purpose reservoir in western Oregon impounded by the 158-meter ([m]; 518-foot [ft]) tall Cougar Dam. Aerial photographs were acquired by the Civil Air Patrol (CAP) in December 2023 when water levels were at 467 m (1531 ft; National Geodetic Vertical Datum of 1929 [NGVD 29]) elevation, near typical annual “low pool” or minimum pool for flood risk management operations. Photographs were acquired at a single altitude with a WaldoAir XCAM Ultra 50 camera mounted on a Cessna aircraft and captured the entire reservoir area as defined by full pool (or maximum conservation pool elevation), including the major tributary entering the reservoir, the South Fork McKenzie River. Dam operations at the 518-hectare (1280-acre) Cougar Reservoir, located about 7 kilometers upstream of the confluence of the South Fork McKenzie River and the McKenzie River, along with other hydrogeomorphic conditions, result in a diverse array of geomorphic processes and landforms within the reservoir. To document reservoir floor geomorphology, the USGS applied structure-from-motion (SfM) techniques to these aerial photographs, following the workflow outlined in Over and others (2021) and used for similar datasets (Schwid and others, 2025), and generated a three-dimensional xyz point cloud, digital surface model (DSM), and orthomosaic of Cougar Reservoir. This data release includes ground control points, dataset footprints, original aerial photographs, a point cloud, a DSM, and an orthomosaic of Cougar Reservoir that were developed from imagery acquired on December 28, 2023. The point cloud has an average point density of 29 points per square meter, the DSM resolution is 18.6 centimeters per pixel, and the orthomosaic ground resolution is 9.28 centimeters per pixel. The DSM and orthomosaic are formatted as Cloud Optimized GeoTIFFs (COGs) for enhanced web visualization (GDAL, 2024). This documentation describes a DSM of Cougar Reservoir, Oregon, generated from SfM techniques using aerial photographs acquired on December 28, 2023. References: Agisoft, 2025, Agisoft Metashape User Manual - Professional Edition Version 2.2: Agisoft LLC, 115 p., accessed August 11, 2025, at https://www.agisoft.com/pdf/metashape_2_2_en.pdf. American Society for Photogrammetry and Remote Sensing [ASPRS], 2008, LAS Specification Version 1.2: ASPRS, approved September 2, 2008, 13 p., accessed August 11, 2025, at https://www.asprs.org/wp-content/uploads/2010/12/asprs_las_format_v12.pdf. Geospatial Data Abstraction Library [GDAL], 2024, COG -- Cloud Optimized GeoTIFF generator: GDAL, webpage, accessed August 11, 2025, at https://gdal.org/drivers/raster/cog.html#raster-cog. Over, J.R., Ritchie, A.C., Kranenburg, C.J., Brown, J.A., Buscombe, D., Noble, T., Sherwood, C.R., Warrick, J.A., and Wernette, P.A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation: U.S. Geological Survey Open-File Report 2021–1039, 46 p., https://doi.org/10.3133/ofr20211039. Schwid, M.F., Keith, M.K., and Overstreet, B.T., 2025, High-resolution orthoimagery and digital surface models of Fern Ridge Lake, Oregon, during annual low pool, January and February, 2023: U.S. Geological Survey data release, https://doi.org/10.5066/P1Q5K657. The original aerial photographs acquired by CAP, along with the point cloud, DSM, and orthomosaic covering Cougar Reservoir were created to provide high-resolution datasets depicting the reservoir floor that is exposed during low pool (467 m/1531 ft NGVD 29) conditions. These datasets are useful for evaluating geomorphic characteristics of the reservoir and assessing other landscape conditions; when compared with future datasets, these datasets will also be useful for tracking changes over time. 20231228 ground condition Complete None planned -122.26458 -122.20228 44.16048 44.05144 ISO 19115 Topic Categories biota elevation environment inlandWaters geoscientificInformation imageryBaseMapsEarthCover USGS Thesaurus structure from motion geospatial analysis aerial photography remote sensing geomorphology geospatial datasets digital elevation models image collections GPS measurement None fluvial geomorphology SfM photogrammetry orthoimagery orthophotograph orthomosaic GeoTIFF Cloud Optimized GeoTIFF dam reservoir drawdown river processes Civil Air Patrol Cessna Waldo USGS Metadata Identifier USGS:681933ced4be0208bc3e03bb Geographic Names Information System (GNIS) Cougar Creek Cougar Reservoir East Fork South Fork McKenzie River Lane County South Fork McKenzie River State of Oregon Walker Creek Willamette River None Willamette Valley Cougar Lake none These data are in the public domain in accordance with Creative Commons Zero v1.0 Universal Public Domain Dedication (CC0-1.0) and have no use constraints. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data retrieved from the system. Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. The U.S. Geological Survey should be acknowledged as the data source in products derived from these data. Schwid, Maxwel F. U.S. Geological Survey Hydrologist Mailing and Physical

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Portland OR 97204 United States 503-758-5589 gs-w-or_sciencebase@usgs.gov These data were produced in cooperation with the U.S. Army Corps of Engineers. We thank Heather Bervid and Will Long from the U.S. Geological Survey for field assistance. None Unclassified None Agisoft Metashape Professional Version 2.2.0; GDAL Version 3.6.2. Two R12i Trimble global navigation satellite system (GNSS) receivers with Trimble’s real-time precise point positioning technology, Real Time eXtended (RTX), were used to collect the ground control points. Where RTX corrections were unavailable, points were corrected using post-processed kinematic (PPK) solutions derived from a regional GNSS base station that occupied a USACE benchmark. Additionally, two USACE benchmarks were occupied to compare RTX and PPK corrections; their coordinates were within one centimeter. All data were acquired and handled in a consistent manner. A single crewed flight was contracted through the USACE to the Civil Air Patrol, Eugene, Oregon on December 28, 2023. A total of 965 aerial photographs were captured at an average flight altitude of about 1,600 meters above ground level, collectively covering about 27 square kilometers. Photographs were acquired as three-band (RGB) images in JPEG format using a WaldoAir XCAM Ultra 50 camera, consisting of two oblique-mounted Canon EOS 5DS R cameras that were triggered simultaneously, mounted to a Cessna 182 aircraft. A NovAtel OEMStar GPS recorded camera positions in the image file EXIF data in UTC time zone. All aerial photographs were contemporaneously aligned in Agisoft Metashape software. Agisoft software determined which aerial photographs were used in SfM product (point cloud, DSM, and orthomosaic) generation based on photograph alignment and the validity of identified tie points, which represent common pixels in photographs as determined by the software. To provide check points for model accuracies, a portion of the ground control points were excluded from SfM product generation and used for model validation. Specifically, 10 checkpoints out of the 34 survey points were excluded. The tie points were visually inspected and filtered to exclude obvious anomalous points from the derivative products (dense point cloud, DSM, and orthomosaic). The orthomosaic contains compression-derived artifacts occurring as erroneous pixel values that border the outer extent of the raster’s multiple overviews; these artifacts do not occur in, nor affect the underlying full-resolution image. The dataset is considered complete and consists of ground control points, a coverage footprint, raw aerial photographs, a dense point cloud, a DSM, and an orthomosaic. All 44 surveyed ground control points are listed in the CSV text file and all 965 aerial photographs are included in two zipped folders. All aerial photographs (excluding 27 that only captured cloud cover and could not be aligned) were used to create SfM products (point cloud, DSM, and orthomosaic). The dense point cloud was generated in the Agisoft Metashape software after a standardized filtering process that excludes low-certainty or anomalous points. The filtered dense point cloud was used to create the DSM and orthomosaic. The dense point cloud and DSM generated may contain false topography and high error propagated from the software’s identification of false tie points below the translucent, shallow water surface of the pool or in areas influenced by lake waves (Over and others, 2021). The DSM and orthomosaic were clipped during export from Agisoft software to exclude areas of high uncertainty or distortion, particularly in densely vegetated or forested areas or near edges where minimal photograph overlap inhibited photogrammetric processing. No formal horizontal accuracy tests were performed. Sources of potential error that affect the horizontal accuracy include ground control point accuracy and error incurred during alignment, optimization, and ground control processing procedures within the Agisoft Metashape software. Although the aerial photograph locations (recorded by a NovAtel OEMStar GPS located on the aircraft) are used by the photogrammetric software during initial alignment, these location data are not included in the generation of any derivative products and therefore the positional accuracy and potential errors do not contribute to the overall horizontal accuracy of the products (point cloud, DSM, and orthomosaic). Horizontal accuracy likely decreases with distance from ground control. Ground control points surveyed with an RTX-enabled GNSS receiver had a reported horizontal precision ranging from 0.01 to 0.15 meters. Though not an assessment of horizontal or vertical accuracy, horizontal positions of ground control points were used to calculate a root mean square (RMS) estimate of positional error at discrete locations by the photogrammetric software and are described here. Additionally, residuals between withheld ground control points (check points) and the model can serve as an indication of accuracy. Ground control and check point error is reported by the software with precision that is higher than provided by model inputs (RTX-GNSS precision) and thus has been rounded. For the model, 34 ground control points were used to construct SfM datasets, and the model had a horizontal error of 21 centimeters, vertical error of 14 centimeters, and overall error of 25 centimeters. The 10 ground control points withheld as check points were compared to the model and had a horizontal error of 26 centimeters, vertical error of 35 centimeters, and overall error of 44 centimeters. Visual comparison of the generated orthomosaic to publicly available aerial imagery indicated horizontal displacement was minimal for all datasets, although some obvious distortion (for example, holes, blurry areas, and discontinuity or irregularity of linear features) is noticeable where vegetation is present or there was very little photograph overlap. Increasing noise at surface water locations occurs within the model; these areas were not edited. No formal vertical accuracy tests were performed. However, vertical accuracy likely decreases with distance from ground control. Ground control points surveyed with an RTX-enabled GNSS receiver had a reported vertical precision ranging from 0.04 to 0.21 meters. Though not an assessment of horizontal or vertical accuracy, horizontal positions of ground control points were used to calculate an RMS estimate of positional error at discrete locations by the photogrammetric software and are described here. Additionally, residuals between withheld ground control points and the model can serve as an indication of accuracy. Ground control and check point error is reported by the software with precision that is higher than provided by model inputs (RTX-GNSS precision) and thus has been rounded. For the model, 34 ground control points were used to construct SfM datasets, and the model had a horizontal error of 21 centimeters, vertical error of 14 centimeters, and overall error of 25 centimeters. The 10 ground control points withheld as check points were compared to the model and had a horizontal error of 26 centimeters, vertical error of 35 centimeters, and overall error of 44 centimeters. Digital surface models, particularly in edge areas where photograph overlap was limited, may contain false topography as a result of the photogrammetric reconstruction process and/or model interpolation within sparse dense point cloud areas. American Society for Photogrammetry and Remote Sensing 20080902 publication online American Society for Photogrammetry and Remote Sensing https://www.asprs.org/wp-content/uploads/2010/12/asprs_las_format_v12.pdf Digital and/or Hardcopy 20080902 publication date ASPRS (2008) Laser file format specifications for point clouds. Jin-Si R. Over Andrew C. Ritchie Christine J. Kranenburg Jenna A. Brown Daniel D. Buscombe Tom Noble Christopher R. Sherwood Jonathan A. Warrick Phillipe A. Wernette 2021 publication online U.S. Geological Survey https://doi.org/10.3133/ofr20211039 Digital and/or Hardcopy 20210614 publication date Over and others (2021) Software settings and processing procedures. Maxwel F. Schwid Mackenzie Keith Brandon T. Overstreet 2025 dataset https://www.sciencebase.gov U.S. Geological Survey https://doi.org/10.5066/p1q5k657 Digital and/or Hardcopy 20250311 publication date Schwid and others (2025) Software settings and processing procedures. Agisoft 2025 publication online Agisoft https://www.agisoft.com/pdf/metashape_2_2_en.pdf Digital and/or Hardcopy 20250211 publication date Agisoft (2025) Software settings and processing procedures. Geospatial Data Abstraction Library (GDAL) 2024 3.6.2 application/service online Geospatial Data Abstraction Library (GDAL) https://gdal.org/drivers/raster/cog.html#raster-cog https://gdal.org/api/python_bindings.html Digital and/or Hardcopy 20240218 publication date GDAL (2024) Raster conversion program for Cloud Optimized GeoTIFF creation. Aerial photographs were acquired by the Civil Air Patrol on December 28, 2023, between 13:24 to 14:22 Pacific Standard Time (PST) covering approximately 27 square kilometers of the reservoir area. Photographs were acquired as high-resolution JPG images using a WaldoAir XCAM Ultra 50 camera, consisting of two oblique-mounted Canon EOS 5DS R cameras that are triggered simultaneously, mounted to a Cessna 182 aircraft. A NovAtel OEMStar GPS recorded camera positions in the image file EXIF data in UTC time zone. The pilot flew in sub-longitudinal passes at about 1,600 meters above ground level over Cougar Reservoir. A total of 965 photos were taken from takeoff to landing of flight. 20231228 The USGS surveyed 44 control point features throughout Cougar Reservoir on December 03, 2024, with a GNSS receiver; points were corrected in real-time through RTX or post-collection with PPK. The control points consisted of static infrastructure features (for example, parking lot pavement arrows, retaining-wall corners, stumps) that were visible in the photographs. 20241203 All 965 photographs from the December 28 flight were added to Agisoft Metashape software (v. 2.2.0) for alignment to identify tie points (common pixels the software identifies between photos). All subsequent steps conducted in Agisoft Metashape software follow the workflow outlined in Over and others (2021). Camera groups were created based on the two oblique cameras, but all photos remained in a single chunk. The coordinate system of the aerial photographs was converted from WGS84 (EPSG:4326) to NAD83(2011) UTM Zone 10 North (EPSG:6339) for the horizontal datum and projection and NAVD88 meters, GEOID 18 (EPSG:5703) for the vertical datum. The following reference settings were updated: measurement camera accuracy of 150 meters and marker accuracy of 0.1 meters; image coordinates marker accuracy of 1 pixel and tie point accuracy of 1 pixel 2025 All aerial photographs were aligned together with an accuracy setting of "High", the generic preselection box checked, the reference preselection box checked and set to "Source," key point limit set to 60,000, and tie point limit set to 0 (meaning no tie point limit). The "Exclude stationary tie points," "Guided image matching," and "Adaptive camera model fitting" boxes were all left unchecked. 2025 The camera calibration model was optimized with the following coefficients: f, cx, cy, k1, k2, k3, p1, p2, and where f is focal length; cx and cy are the optimal point; k is radial distortion; and p translational distortion. 2025 A ground control point file (CSV) containing XYZ coordinates (NAD83(2011) UTM Zone 10 North (EPSG:6339) and NAVD88 meters, GEOID 18 (EPSG:5703)) was imported. The Agisoft software identified photos that contained each marker. Photographs were filtered by each marker and were inspected for marker placement relative to the ground control point visible in each photo. Markers were either left in their position and verified, moved to the correct position and verified, or removed. An even spatial distribution of ground control points were converted to check points for use in later model accuracy assessment (10 checkpoints out of the 44 survey points; see CSV). Camera GPS locations were excluded from further processing by unchecking (not disabling) all cameras in the reference-camera pane. 2025 The camera calibration model was optimized with the following coefficients: f, cx, cy, k1, k2, k3, p1, p2, where f is focal length; cx and cy are the optimal point; k is radial distortion; and p translational distortion. 2025 The sparse cloud of approximately 3 million photogrammetric tie points generated during alignment was gradually filtered based on several criteria of model fit to identify and remove points with high reprojection error, with camera calibration model optimization in between each filtering step. First, the point cloud was visually inspected for anomalous points which were selected then deleted. Second, points with a “Reconstruction uncertainty” greater than 11.4 were selected then deleted; this removed approximately 2.3 million points that were generated due to poor camera geometries. The camera calibration model was then optimized with the following coefficients: f, cx, cy, k1, k2, k3, p1, p2. Third, points with a “Projection accuracy” greater than 4.7 were selected then deleted; this removed approximately 0.5 million points that were generated due to pixel matching errors derived from variations in image scaling. The camera calibration model was then optimized with the following coefficients: f, cx, cy, k1, k2, k3, p1, p2. Last, points with a “Reprojection error” greater than 0.2 were iteratively selected and deleted, without exceeding 10% of all points with each selection; this removed approximately 0.13 million points in total that were incorrectly reprojected after alignment. The camera calibration model was then optimized with the following coefficients: f, cx, cy, k1, k2, k3, k4, p1, p2, b1, b2, with “Fit additional corrections” checked. The final unweighted RMS reprojection error for the tie point cloud was 0.37 pixels. 2025 A dense point cloud was built using the high quality setting and mild depth filtering. Any anomalous or “floating” points were visually inspected and deleted. 2025 A DSM was built using the dense point cloud and interpolation enabled. Color was homogenized using the "Calibrate Colors" with the "Calibrate white balance" option checked. 2025 An orthomosaic was built using the Mosaic blending mode, digital elevation model (DEM) surface, hole filling enabled, and default pixel size. 2025 All SfM products were exported using their default resolutions. The dense point cloud and DSM were exported using default settings. The orthomosaic was exported without compression and saved as a BigTIFF file. The DSM and orthomosaic were clipped using the footprint polygon to remove distorted areas or areas with missing raster values. 2025 The DSM and orthomosaic were converted from standard GeoTIFFs to Cloud Optimized GeoTIFFs (COGs) using the Python binding of the Geospatial Data Abstraction Library’s (GDAL) COG raster driver (GDAL, 2024). Standard raster driver settings were maintained except for the following: The DSM was created using LZW (lossless) compression, floating point predictor, bilinear overview resampling, and BigTIFF set to “IF_SAFER;” the orthomosaic was created using JPEG compression (default quality of 75), bilinear resampling, and BigTIFF set to “IF_SAFER.” This JPEG compression may alter pixel values from the original values output by the Agisoft software. The orthomosaic contains compression-derived artifacts occurring as erroneous pixel values that border the outer extent of the raster’s multiple overviews; these artifacts do not occur in, nor affect the underlying full resolution image. 2025 Raster Pixel 65009 26263 1 Universal Transverse Mercator 10 0.9996 -123.0 0.0 500000.0 0.0 row and column 0.1856 0.1856 meters NAD83_National_Spatial_Reference_System_2011 GRS 1980 6378137.0 298.257222101 North American Vertical Datum of 1988 0.001 meters Explicit elevation coordinate included with horizontal coordinates CougarReservoir_2023_dsm.tif Elevation raster Other Value Elevation Agisoft Metashape 0 NoData Producer defined 355.839 1021.516 Meters U.S. Geological Survey - ScienceBase Mailing and Physical

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Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Although these data have been used by the U.S. Geological Survey, U.S. Department of the Interior, no warranty expressed or implied is made by the U.S. Geological Survey as to the accuracy of the data. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of these data, software, or related materials. The use of firm, trade, or brand names in this report is for identification purposes only and does not constitute endorsement by the U.S. Geological Survey. The names mentioned in this document may be trademarks or registered trademarks of their respective trademark owners. GeoTIFF GDAL 3.6.2 32-bit TIFF 32-bit floating point Cloud Optimized GeoTIFF with LZW compression and FGDC CSDGM metadata LZW compression. 3600 https://doi.org/10.5066/P13V7HBC https://prod-is-usgs-sb-prod-publish.s3.amazonaws.com/681933ced4be0208bc3e03bb/CougarReservoir_2023_dsm.tif The first link points to the landing page for the entire data release, which includes links to pages of the various data files. The second link is for accessing this digital surface model raster via cloud-based storage and can be used to download the data or for cloud-based queries. None. This dataset is provided by USGS as a public service. 20250826 Schwid, Maxwel. F U.S. Geological Survey Hydrologist Mailing and Physical

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Portland Oregon 97204 United States 503-758-5589 gs-w-or_sciencebase@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 local time