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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...
Categories: Data,
Publication;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Federal resource managers,
GPLCC,
GPLCC,
Great Plains,
Great Plains,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Minnesota,
Mississippi River,
Navigation Pool 03,
Navigational Pool 04,
Upper Mississippi River,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Iowa,
Minnesota,
Mississippi River,
Navigation Pool 03,
Navigational Pool 09,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Minnesota,
Mississippi River,
Navigation Pool 03,
Navigational Pool 05,
Upper Mississippi River,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Minnesota,
Mississippi River,
Navigation Pool 03,
Navigational Pool 08,
Upper Mississippi River,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Minnesota,
Mississippi River,
Navigational Pool 05a,
Upper Mississippi River,
Wisconsin,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Minnesota,
Mississippi River,
Navigational Pool 07,
Upper Mississippi River,
Wisconsin,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Illinois,
Minnesota,
Mississippi River,
Missouri,
Navigation Pool 03,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Illinois,
Iowa,
Minnesota,
Mississippi River,
Navigation Pool 03,
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.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Minnesota,
Mississippi River,
Navigational Pool 03,
Upper Mississippi River,
Wisconsin,
Inundation is a critical parameter of wetland hydrologic performance. This study uses Annual Habitat Survey data from 2004 to 2012 in the Rainwater Basin in south-central Nebraska to examine differences between the actual inundation conditions and three datasets: the National Wetland Inventory (NWI), the Soil Survey Geographic database (SSURGO), and LiDAR-derived depressions. The results show that current wetland inundated areas were well overlaid with these datasets (99.9% in SSURGO data, 67.9% in NWI data, and 87.3;% in LiDAR-derived depressions). However, the hydrologic degradation of playa wetlands was not reflected in these datasets. In SSURGO data, only 13.3% of hydric soil footprint areas were inundated and...
Categories: Data,
Publication;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Federal resource managers,
GPLCC,
GPLCC,
Great Plains,
Great Plains Landscape Conservation Cooperative,
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