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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) Program Long Term Resource Monitoring (LTRM) element has overseen the collection, processing, and serving of bathymetric data since 1989. A systemic data collection for the Upper Mississippi River System (UMRS) was completed in 2010. Water depth in aquatic systems is important for describing the physical characteristics of a river. Bathymetric maps are used for conducting spatial inventories of the aquatic habitat and detecting bed and elevation changes due to sedimentation. Bathymetric data is widely used, specifically for studies of water level management alternatives, modeling navigation impacts and hydraulic conditions, and environmental...
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Separate data for floodplain elevation and bathymetry were collected on the Upper Mississippi River System (UMRS) by the US Army Corps of Engineers (USACE), Upper Mississippi River Restoration (UMRR) program. While many information needs can be met by using these data separately, in many cases seamless elevation data across the river and its floodplain are needed. This seamless elevation surface was generated by merging lidar (i.e., floodplain elevation) and bathymetry data. Merging the data required special processing in the areas of transition between the two sources of data.
The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) Program Long Term Resource Monitoring (LTRM) element has overseen the collection, processing, and serving of bathymetric data since 1989. A systemic data collection for the Upper Mississippi River System (UMRS) was completed in 2010. Water depth in aquatic systems is important for describing the physical characteristics of a river. Bathymetric maps are used for conducting spatial inventories of the aquatic habitat and detecting bed and elevation changes due to sedimentation. Bathymetric data is widely used, specifically for studies of water level management alternatives, modeling navigation impacts and hydraulic conditions, and environmental...
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Separate data for floodplain elevation and bathymetry were collected on the Upper Mississippi River System (UMRS) by the US Army Corps of Engineers (USACE), Upper Mississippi River Restoration (UMRR) Program. While many information needs can be met by using these data separately, in many cases seamless elevation data across the river and its floodplain are needed. This seamless elevation surface was generated by merging lidar (i.e., floodplain elevation) and bathymetry data. Merging the data required special processing in the areas of transition between the two sources of data.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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This dataset is a digital elevation model (DEM) of the beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, Minnesota. The DEM has a 10-meter (m; 32.8084 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography, and multibeam sonar data representing the bathymetry. The survey area extends approximately 0.85 kilometers (0.5 miles) offshore, for an approximately 1.87 square kilometer surveyed area. Lidar data were collected July 28, 2020 using a boat mounted Velodyne unit. Multibeam sonar data were collected July 28-29, 2020 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar...
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A side scan image collected with Humminbird Helix 10 on November 14, 2019. Side scan sonar creates a picture or an image of the riverbed. To generate an image, side scanners measures the strength of how loud the return sonar pings are.
The main goal of this project is to ensure that the 2011-13 climate change update to the Baylands Ecosystem Habitat Goals Report (Baylands Goals) and other key, ongoing conservation activities in the San Francisco Bay region use the latest information about the current and future status of San Francisco Bay tidal marsh ecosystems, particularly in the context of sea-level rise. The main product of the project is the improved Sea Level Rise (SLR) Tool, specifically upgraded to inform the Baylands Goals Report update. The tool will continue to be available online at www.prbo.org/sfbayslr. All data layers going into the tool are and will continue to be downloadable from the site.
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With extraordinary resolution and accuracy, Light Detection and Ranging (LiDAR)-derived digital elevation models (DEMs) have been increasingly used for watershed analyses and modeling by hydrologists, planners and engineers. Such high-accuracy DEMs have demonstrated their effectiveness in delineating watershed and drainage patterns at fine scales in low-relief terrains. However, these high-resolution datasets are usually only available as topographic DEMs rather than hydrologic DEMs, presenting greater land roughness that can affect natural flow accumulation. Specifically, locations of drainage structures such as road culverts and bridges were simulated as barriers to the passage of drainage. This paper proposed...
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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This dataset is a longitudinal profile of the river bed and water surface along the thalweg of a an approximately 500 meter (m) reach of the Kalamazoo River upstream of Plainwell, Michigan (MI). The bed profile was derived from a digital elevation model (DEM) comprising topographic and bathymetric data for the Plainwell reach. Bathymetric data in the river channel were collected in October, 2021 with a single beam sonar and Acoustic Current Doppler Profiler (ADCP) operated along two longitudinal transects and 48 cross-sectional transects, respectively. River bank topographic data were collected with a backpack-mounted terrestrial lidar unit concurrently with the bathymetric data. The water surface profile was developed...
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This dataset contains topographic cross sections spanning the river channel for an approximately 500 meter (m) reach of the Kalamazoo River upstream of Plainwell, Michigan (MI). The 30 cross sections are oriented perpendicular to the channel and spaced evenly along the 500m reach to represent variability in channel geometry. Bankfull hydraulic geometry attributes and complexity metrics were calculated for each cross section. The cross section data were extracted from a digital elevation model (DEM) composed of topographic and bathymetric data, which is contained in this data release. Cross-section data are provided in tabular and graphical form in an Excel spreadsheet and CSV files. The spatial location of the cross-sections...
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This part of the data release presents topography data from northern Monterey Bay, California collected in September 2017 using a tripod-mounted Riegl VZ-1000 lidar scanner (USGS Field Activity 2017-678-FA). For each area surveyed, the scanner was placed at several positions which were selected to provide maximum line-of-sight coverage of the area of interest. Scans were typically conducted in panoramic mode, creating a detailed point cloud of all unobstructed surfaces in a 360 degree view of the scanner. At each scan position, co-registered photographic imagery was also collected with a scanner mounted DSLR camera. Scanner registration was performed by placing four or more cylindrical or flat reflective tripod-mounted...
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This part of the data release presents topography data from northern Monterey Bay, California collected in March 2015 using a tripod-mounted Riegl VZ-1000 lidar scanner (USGS Field Activity 2015-625-FA). For each area surveyed, the scanner was placed at several positions which were selected to provide maximum line-of-sight coverage of the area of interest. Scans were typically conducted in panoramic mode, creating a detailed point cloud of all unobstructed surfaces in a 360 degree view of the scanner. At each scan position, co-registered photographic imagery was also collected with a scanner mounted DSLR camera. Scanner registration was performed by placing four or more cylindrical or flat reflective tripod-mounted...
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A seamless topographic-bathymetric digital elevation model for an area around Arey Lagoon, Alaska created from a combination of lidar elevation data collected in 2009, single-beam bathymetric data collected in 2011, and NOS sounding data collected in 1948.
Low-resolution shaded relief maps and full resolution DEMs available! The Version 5 (final) Digital Elevation Models have 2-meter post spacing unless specified as (4m) below. File sizes are listed for each file. Shaded relief files are very generalized. Low-resolution shaded relief maps and full resolution DEMs available!
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Active channel as defined by remote sensing before (2010) a 40 year return period flood (December 2010) within the lower Virgin River, Nevada.
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The U.S. Geological Survey South Atlantic Water Science Center, in cooperation with the South Carolina Department of Transportation, implemented a South Carolina StreamStats application in 2018. This shapefile dataset contains vector lines representing streams, rivers, and ditches that were used in preparing the underlying data for the South Carolina StreamStats application. Data were compiled from multiple sources, but principally represent lidar-derived linework from the South Carolina Department of Natural Resources and the South Carolina Lidar Consortium.The South Carolina hydrography lines were created from elevation rasters that ranged from 4 to 10 ft resolution, to produce a product of approximately 1:6,000-scale....
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Abbeville County, Aiken County, Allendale County, Anderson County, Bamberg County, All tags...


map background search result map search result map Black Skimmer- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions UMRR Pool 06 Topobathy UMRR Starved Rock Topobathy UMRR Illinois River Peoria Reach Bathymetry Footprint UMRR Mississippi River Navigation Pool 20 Bathymetry Footprint Terrestrial lidar data from northern Monterey Bay, California, March 2015 Drainage Structure Datasets and Effects on LiDAR-Derived Surface Flow Modeling Project Summaries: Use of LIDAR to Assess the Effectiveness of Grass Plantings and Buffers on Playa Natural Inundation and Sedimentation Control in the Rainwater Basin Terrestrial lidar data from northern Monterey Bay, California, September 2017 Stream Lines Used to Produce the South Carolina StreamStats 2018 Release Active channel in the Lower Virgin River before a 40 yr flood (December 2010) ElevMHW: Elevation adjusted to local mean high water: Assateague Island, MD & VA, 2014 Seamless topo-bathy digital elevation model (DEM) of Arey Lagoon, Alaska Broken Forest Canopy Identified by Lidar for the Navigational Pool 8 of the Mississippi River Duluth Entry: 10-meter Digital elevation model (DEM) of beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, MN, July 2020 Lock and Dam 19 Side Scan, 2019 Channel Cross Sections of Kalamazoo River Reference Reach upstream of Plainwell, Michigan, 2021 Longitudinal Profile for Kalamazoo River Reference Reach upstream of Plainwell, Michigan, 2021 Lock and Dam 19 Side Scan, 2019 Channel Cross Sections of Kalamazoo River Reference Reach upstream of Plainwell, Michigan, 2021 Longitudinal Profile for Kalamazoo River Reference Reach upstream of Plainwell, Michigan, 2021 Duluth Entry: 10-meter Digital elevation model (DEM) of beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, MN, July 2020 Terrestrial lidar data from northern Monterey Bay, California, September 2017 Terrestrial lidar data from northern Monterey Bay, California, March 2015 Seamless topo-bathy digital elevation model (DEM) of Arey Lagoon, Alaska Active channel in the Lower Virgin River before a 40 yr flood (December 2010) ElevMHW: Elevation adjusted to local mean high water: Assateague Island, MD & VA, 2014 UMRR Illinois River Peoria Reach Bathymetry Footprint Black Skimmer- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Drainage Structure Datasets and Effects on LiDAR-Derived Surface Flow Modeling Project Summaries: Use of LIDAR to Assess the Effectiveness of Grass Plantings and Buffers on Playa Natural Inundation and Sedimentation Control in the Rainwater Basin Stream Lines Used to Produce the South Carolina StreamStats 2018 Release