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This publication provides digital flight line data for a high-resolution magnetic survey over an area of the central Upper Peninsula of Michigan. The survey area lies approximately between the towns of Iron Mountain and Chatham. Data for this survey were collected by EON Geosciences under contract with the USGS using a fixed wing aircraft with a magnetometer mounted in the tail stinger. The survey operated out of the Sawyer International Airport near Marquette, Michigan, from June of 2018 to September of 2018. A total of 38,474 line km of data were collected. Data were collected along north-south flight lines spaced 150 meters apart with east-west tie lines flown every 1,500 meters. The nominal terrain clearance...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Alger County,
Delta County,
Dickinson County,
Florence County,
GGGSC,
8 aerial photographs were taken along the Little Missouri River in 1966. All images were geo-referenced to the 1995 digital orthophoto quarter quadrangles as described by Miller and Friedman (2009). Both the flood plain and active channel of the river were delineated on the 1995 digital orthophoto quadrangles and overlain on rectified photos. ArcGIS was used to draw the polygons that delineate the flood plain and active channel; the delineation was saved as a SHP file. The separate images (geoTIFFs) can be viewed as a composite along with that year's channel delineation (SHP file) using ArcGIS, or any other geographic information system (GIS) compatible program. Reference: Miller, J.R., and J.M. Friedman. 2009....
Categories: Data;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Central US,
Little Missouri River,
McKenzie County,
ND,
North Dakota,
The landscape permeability model represents the structural connectivity of sagebrush ecosystem habitat in the Green River Basin (including ~5-10 km boundary outside of the GRB. This model connects patches of habitat, across the landscape using resistances that represent the degree of human modification and slope (energetic costs), using the Multi-Scale Landscape Permeability model (Theobald et al. 2012; Theobald unpublished). We used two metrics: (a) patch importance and (b) betweeness centrality amongst patches. These metrics were summarized for each HUC12. This dataset represents the vulnerability of sagebrush ecosystem permeability to human modification summarized for each HUC12 watershed within the Green River...
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
Bayesian Network,
CMHRP,
Cape Ann,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
Bayesian Network,
CMGP,
Cedar Island,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
Bayesian Network,
CMHRP,
Cape Cod,
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