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This dataset includes: The locations of EPA listed sites that are vulnerable to a 100-year coastal flood with a 1.4 meter sea-level rise. Extents of dune and bluff erosion given a 1.4 meter (approx. 55") sea-level rise for the entire California coast. Extent of a 100-year coastal flood, based on FEMA 100-year flood elevations, with a sea-level rise of 1.4 meters (55 inches) (year 2100). Extent of inundation due to Mean Higher High Water (MHHW), after a 1.4 meter sea-level rise (scenario for year 2100), for the California coast (excluding the San Francisco Bay). The current inundation due to MHHW was based on NOAA tide stations elevation data (mhhw_2000 raster), to which 140 centimeters were added to the Z-value...
Abstract (from http://www.bioone.org/doi/abs/10.2112/JCOASTRES-D-13-00202.1): Traditional long-term (decadal) and large-scale (hundreds of kilometers) shoreline change modeling techniques, known as single transect, or ST, often overfit the data because they calculate shoreline statistics at closely spaced intervals along the shore. To reduce overfitting, recent work has used spatial basis functions such as polynomials, B splines, and principal components. Here, we explore an alternative to such basis functions by using regularization to reduce the dimension of the ST model space. In our regularized-ST method, traditional ST is an end member of a continuous spectrum of models. We use an evidence information criterion...
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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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMGP, Coastal Erosion, All tags...
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In July 2012, a helicopter-based crew photographed approximately 22 miles (35 km) of shoreline near Golovin, Alaska, from the Yuonglik River delta southeast to Portage Creek. During this flight 572 oblique aerial photographs were collected and spatially referenced using a Garmin Dakota 20 handheld GPS.
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This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios...
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This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...


map background search result map search result map California Sea Level Rise Coastal Erosion Mapping Spatially referenced oblique aerial photography of the Golovin shoreline, July 2012 CoSMoS v3.1 flood hazard projections: 100-year storm in San Luis Obispo County points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 CoSMoS v3.1 wave-hazard projections: 100-year storm in San Luis Obispo County CoSMoS v3.1 water level projections: 20-year storm in San Luis Obispo County Spatially referenced oblique aerial photography of the Golovin shoreline, July 2012 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 CoSMoS v3.1 flood hazard projections: 100-year storm in San Luis Obispo County CoSMoS v3.1 wave-hazard projections: 100-year storm in San Luis Obispo County CoSMoS v3.1 water level projections: 20-year storm in San Luis Obispo County California Sea Level Rise Coastal Erosion Mapping