This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Coastal Services Center's Sea Level Rise and Coastal Flooding Impacts Viewer (www.csc.noaa.gov/slr/viewer). This metadata record describes the DEM for Mobile County in Alabama and Escambia, Santa Rosa, and Okaloosa (southern coastal portion only) Counties in Florida. The DEM includes the best available lidar data known to exist at the time of DEM creation for the coastal areas of Mobile County in Alabama and Escambia, Santa Rosa, and Okaloosa (portion) counties in Florida, that met project specification.This DEM is derived from the USGS National Elevation Dataset (NED), US Army Corps of Engineers (USACE) LiDAR data, as well as LiDAR collected for the Northwest Florida Water Management District (NWFWMD) and the Florida Department of Emergency Management (FDEM). NED and USACE data were used only in Mobile County, AL. NWFWMD or FDEM data were used in all other areas. Hydrographic breaklines used in the creation of the DEM were obtained from FDEM and Southwest Florida Water Management District (SWFWMD). This DEM is hydro flattened such that water elevations are less than or equal to 0 meters.This DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 5 meters. This DEM does not include licensed data (Baldwin County, Alabama) that is unavailable for distribution to the general public. As such, the extent of this DEM is different than that of the DEM used by the NOAA Coastal Services Center in creating the inundation data seen in the Sea Level Rise and Coastal Impacts Viewer (www.csc.noaa.gov/slr/viewer).The NOAA Coastal Services Center has developed high-resolution digital elevation models (DEMs) for use in the Center's Sea Level Rise And Coastal Flooding Impacts internet mapping application. These DEMs serve as source datasets used to derive data to visualize the impacts of inundation resulting from sea level rise along the coastal United States and its territories.The dataset is provided "as is," without warranty to its performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of this dataset is assumed by the user. This dataset should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes.

These data were automated to provide an accurate high-resolution historical shoreline of Mobile Bay, Alabama suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attri...

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These data were automated to provide an accurate high-resolution composite shoreline of GRAND BAY TO PENSACOLA MOBILE BAY, AL suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies. This metadata describes information for both the line and point shapefiles. The NGS's attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST) was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so that the data would be more accurately translated into S-57.

Flood Zones map of the City of Mobile. (effective June 5, 2020) Size 36x48 / Format PDF. Updated as needed.Descripton of Flood Zone Data:The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated bathymetric-topographic DEMs are used to support tsunami forecasting and modeling efforts at the NOAA Center for Tsunami Research, Pacific Marine Environmental Laboratory (PMEL). The DEMs are part of the tsunami forecast system SIFT (Short-term Inundation Forecasting for Tsunamis) currently being developed by PMEL for the NOAA Tsunami Warning Centers, and are used in the MOST (Method of Splitting Tsunami) model developed by PMEL to simulate tsunami generation, propagation, and inundation. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to the vertical tidal datum of Mean High Water (MHW) and horizontal datum of World Geodetic System 1984 (WGS84). Grid spacings for the DEM ranges from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).This DEM includes the Mobile Bay, Alabama area including Mobile and Baldwin Counties.While every effort has been made to ensure that these data are accurate and reliable within the limits of the current state of the art, NOAA cannot assume liability for any damages caused by any errors or omissions in the data, nor as a result of the failure of the data to function on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.The dataset is provided "as is," without warranty to its performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of this dataset is assumed by the user. This dataset should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes.

The study linked watershed and hydrodynamic models to evaluate how land-cover land-use (LCLU) changes affect the bay. Data provided future scenarios, including temperature, precipitation, and sea level rise for 2005, 2025, and 2050.To identify areas of potential change in distribution of submerged aquatic vegetation (SAV) due to changes in Total Suspended Solids (TSS) in Mobile Bay, Alabama estuaries, datasets from 3 different time frames (2005, 2025, 2050) were used. The time frame for this dataset was 2025. The habitat models represent projected areas with high light (>= 18% Surface Irradiance) levels for Mobile Bay based on hydrodynamic modeling for future climate scenarios. SAV extent for 2009 is included.Increased urbanization affects freshwater flows, temperature, salinity, and TSS. Urbanization reduces TSS by replacing agricultural land, while replacing forest land increases TSS. The impact on sediment loads and light attenuation was analyzed to assess SAV habitat. GIS-based habitat suitability maps for various scenarios were developed, helping coastal environmental managers understand how LCLU and changes influence temperature, salinity, and sediment levels in the bay.Data: LCLU Maps (.zip)Potential SAV Habitat for LCLU Scenarios (.zip)Potential SAV Habitat for Change Scenarios (.zip)Watershed Modeling Charts (.zip)Hydrodynamic Modeling Charts (.zip)Metadata: NCEIThis is a component of the Gulf Data Atlas (V1.0) for the Biotic topic area.

This data set contains true color (RGB) ortho-rectified mosaic tiles, created as a product from the NOAA Integrated Ocean and Coastal Mapping (IOCM) initiative. The source imagery was acquired from 20110217 - 20110217. The images were acquired with an Applanix Digital Sensor System (DSS). The original images were acquired at a higher resolution than the final ortho-rectified mosaic. Ortho-rectified mosaic tiles are an ancillary product of NOAA's Coastal Mapping Program (CMP), created through a wider Integrated Ocean and Coastal Mapping initiative to increase support for multiple uses of the data.

Data are in Geotiff format with associated browse graphic (.jpg) and HIStory (.his) files. Federal Geographic Data Committee metadata is included as .txt and .xml files.

The ground sample distance (GSD) for each pixel is 0.50 m.

Parking Areas include paved parking within entire update area, and unpaved parking within commercial and industrial parcels and other areas specified by the City of Mobile. This dataset is provided as part of 1":100' planimetric update mapping of bridge, buildings, driveways, parking, edge of pavement, and sidewalk features. Updates were performed by Kucera International, Inc. in 2023-2024 for approximately 472 square miles, including the following areas: City of Mobile metropolitan area, the Big Creek Watershed, the City of Chickasaw, and portions of the Cities of Prichard, Saraland, and Satsuma. See 2023 update boundary or contact City of Mobile for more information. Using the YEAR_REVIEWED field will tell you which ortho image year the feature was updated. The updates are based on three inch resolution RGB ortho-rectified aerial imagery that was collected in 2022 for the western half of Mobile County and in 2023 for the eastern half of Mobile County. Features were manually updated using “heads-up” fashion digitizing at a 1” = 100’ scale in 2D using the 3-inch resolution ortho-rectified imagery. Features that are new, no longer present or of significant change (defined by 10' by 10') are updated as they appear in 2022/2023 imagery. Unpaved parking added in 2023/2024 are within commercial and industrial parcels, as well as other areas specified as per case by the City of Mobile. The following SURFACE_TYPE attribute domain was used for features added in 2023/2024, unless otherwise specified as per case by City of Mobile: PAVED, UNPAVED. Other various surface types in the dataset were unchanged or modified in 2023/2024.

From April 13-20, 2013, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) conducted geophysical surveys and collected sediment samples from Dauphin Island, Alabama. This dataset, Ground Penetrating Radar (GPR) Trackline Locations Collected from Dauphin Island, Alabama, in April 2013, contains geospatial data and raster images of the GPR data. The GPR trackline locations are presented as Geographic Information System (GIS) files and the subsurface profile data are provided as images in Joint Photographic Experts Group (JPEG) format.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

The SACS study area is subdivided into 22 planning reaches (Figure 4 1) derived from three datasets and visual edits based on coastal geomorphology and professional judgment. Datasets include the following:- The Nature Conservancy Ecoregions—boundaries of areas that The Nature Conservancy has prioritized for conservation- State boundaries- Maximum inland limit of Category 5 storm surge inundation represented by the NOAA Sea, Lake, and Overland Surges from Hurricanes (SLOSH) modelThe GIS process to develop the Planning Reaches entailed the follow:The most landward extent of the SLOSH model was manually measured. Based on that measurement a single sided buffer was generated contiguous to the Coast for the AOR. The buffer was manually edited to include some areas that fell outside the buffer distance, specifically in Northern North Carolina and around Mobile Alabama. The Union tool was then used in ArcGIS desktop to overlay Ecoregions and State boundary files. Then the intersect tool was used to overlay the SLOSH buffer with the Union file. The result of the Intersect was then manually cut along the lines defined by the coastal geomorphology using lines defined in the “Manual_Edit_lines” feature. The resulting feature class was then provided with names based on the state two-digit acronym and a sequential number.

Data from Mobile Bay National Estuary Program. This data set consists of digital data documenting the location and species composition of submerged aquatic vegetation (SAV) in coastal Alabama, collected as part of a remote sensing investigation of SAV distribution using ortho imagery from July 2002 as base maps. Survey areas included Mississippi Sound (AL), Mobile Bay, Mobile Delta, Little Lagoon, Bay La Launch, Perdido Bay, and their communicating tributaries. The data set includes 296 orthophotographs, which were digitized at Southeast Digital Mapping, L.L.C from true color aerial photography acquired July 2002.The intended use of this data set is to provide a comprehensive assessment of the distribution and extent of submerged aquatic vegetation along the Alabama Coast in 2002.

To identify areas of potential change in distribution of SAVs due to changes in Total Suspended Solids (TSS) in Mobile Bay, AL estuaries, datasets from 3 different time frames (2005, 2025, 2050) were used.