gov.noaa.nmfs.inport:79752 eng UTF8 dataset Office for Coastal Management resourceProvider NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information pointOfContact 2026-05-21T03:50:52 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) 3 row 149842 column 251383 vertical 1 area 0 2021 C-CAP High Resolution Land Cover of Coastal Alabama and Mississippi 2026-04-28 creation 2026-04-28 publication NOAA/NMFS/EDM 79752 https://www.fisheries.noaa.gov/inport/item/79752 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information https://ocmgeodatastor1.blob.core.windows.net/ccap/bulk_download/C-CAP_High-Resolution_Data/Refined_C-CAP_High-Resolution_Land_Cover_Classification/CONUS/index.html WWW:LINK-1.0-http--link Bulk Download Full file download. download imageDigital USE RESTRICTIONS: Users are granted a perpetual, non-exclusive, irrevocable, worldwide license to use these data, and to create derived and value-added products, in any manor and for any purpose with the exception of creating, training, improving, modifying, validating, testing, evaluating, or otherwise leveraging machine learning algorithms in order to explicitly create similar land cover data for a period of five years from its date of creation. The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products inventory coastal intertidal areas, wetlands, and adjacent uplands with the goal of monitoring changes in these habitats through time. High resolution C-CAP products are developed utilizing high resolution aerial imagery, along with lidar and various available ancillary information, and can be used to track changes in the landscape through time. This is a full-scheme C-CAP land cover product, which includes up to 20 land cover classes, including impervious surfaces, agricultural areas, tree/shrub canopy, water, and wetlands. These high-resolution C-CAP land cover products enable local mapping and analyses for several applications, including water quality and stormwater management, land use planning and community development, risk assessment, natural resource management, and other community-level activities. This dataset represents land cover for the timeframe of 2021 for the Northeast Region of Ohio. C-CAP is dedicated to the development, distribution, and application of land cover and change data for the coastal regions of the U.S. completed NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information pointOfContact NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information custodian 5 years EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER > LAND USE/LAND COVER CLASSIFICATION theme Global Change Master Directory (GCMD) Science Keywords 23.3 CAMERAS instrument Global Change Master Directory (GCMD) Instrument Keywords 23.3 Airplane > Airplane platform Global Change Master Directory (GCMD) Platform Keywords 23.3 Jackson County MS Mississippi Pearl River County Stone County AL Alabama Baldwin County George County Hancock County Harrison County Mobile County theme Geographic Names Information System C-CAP CCAP Land Cover Land Cover Analysis Remotely Sensed Imagery/Photos theme 2021 temporal Coastal Zone place DOC/NOAA/NOS/OCM > Office of Coastal Management, National Ocean Service, NOAA, U.S. Department of Commerce dataCentre Global Change Master Directory (GCMD) Data Center Keywords 2017-04-24 publication 8.5 Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA) https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords GCMD Keyword Forum Page Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 22. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords information custodian C-CAP project InPort otherRestrictions Cite As: Office for Coastal Management, [Date of Access]: 2021 C-CAP High Resolution Land Cover of Coastal Alabama and Mississippi [Data Date Range], https://www.fisheries.noaa.gov/inport/item/79752. NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose. otherRestrictions Access Constraints: None otherRestrictions Use Constraints: Users are granted a perpetual, non-exclusive, irrevocable, worldwide license to use these data, and to create derived and value-added products, in any manor and for any purpose with the exception of creating, training, improving, modifying, validating, testing, evaluating, or otherwise leveraging machine learning algorithms in order to explicitly create similar land cover data for a period of five years from its date of creation. C-CAP data sets are not jurisdictional or intended for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, NOAA, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. otherRestrictions Distribution Liability: Users are granted a perpetual, non-exclusive, irrevocable, worldwide license to use these data, and to create derived and value-added products, in any manor and for any purpose with the exception of creating, training, improving, modifying, validating, testing, evaluating, or otherwise leveraging machine learning algorithms in order to explicitly create similar land cover data for a period of five years from its date of creation. C-CAP data sets are not jurisdictional or intended for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, NOAA, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. unclassified grid eng; US imageryBaseMapsEarthCover -89.89 -87.14 29.98 31.5 | Currentness: Acquisition date of the Aerial Imagery 2021 Attributes for this product are as follows: 0 Background, 1 Unclassified (Cloud, Shadow, etc), 2 Developed Impervious, 3 4 Developed Impervious under Tree Canopy 5 Developed Open Space, 6 Cultivated Land, 7 Pasture/Hay, 8 Grassland, 9 10 11 Upland Tree (Forest), 12 Scrub/Shrub, 13 Palustrine Forested Wetland, 14 Palustrine Scrub/Shrub Wetland, 15 Palustrine Emergent Wetland, 16 Estuarine Forested Wetland, 17 Estuarine Scrub/Shrub Wetland, 18 Estuarine Emergent Wetland, 19 Unconsolidated Shore, 20 Bare Land, 21 Open Water, 22 Palustrine Aquatic Bed, 23 Estuarine Aquatic Bed, 24 25 Snow/Ice Recommended Citation. NOAA Coastal Change Analysis Program (C-CAP) Houston Region High Resolution Land Cover Data. Data collected 2020. Charleston, SC: National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management. Data accessed at https://coast.noaa.gov/digitalcoast/data/ccaphighres.html. NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information distributor https://ocmgeodatastor1.blob.core.windows.net/ccap/bulk_download/C-CAP_High-Resolution_Data/Refined_C-CAP_High-Resolution_Land_Cover_Classification/CONUS/index.html WWW:LINK-1.0-http--link Bulk Download Full file download. download dataset Accuracy According to the accuracy assessment performed by NOAA Office for Coastal Management staff, the overall accuracy of this product is 92.3%. There were 574 total points distributed across the study area. The accuracy of each class is as follows (Producer's, User's accuracies): Impervious (97.8%, 95.7%) Impervious under Tree Canopy (90.0%, 90.0%) Open Space Developed (100%, 97.9%) Cultivated (100%, 87.2%) Pasture/Hay (90.2%, 97.9%) Grassland (72.7%, 85.1%) Upland Tree (Forest) (78.0%, 97.9%) Shrub/Scrub (96.9%, 91.2%) Palustrine Forested Wetland (95.2%, 85.1%) Palustrine Shrub/Scrub Wetland (100%, 100%) Palustrine Emergent Wetland (97.3%, 78.3%) Estuarine Emergent Wetland (97.5%, 100%) Unconsolidated Shore (85.7%, 100%) Bare Land (96.7%, 87.9%) Water (95.9%, 100%) Palustrine Aquatic Bed (100%, 100%) Estuarine Aquatic Bed (100%, 50.0%) Overall accuracy (92.3%) Points were sampled using a stratified random sampling scheme, with a minimum target sample of 25 points per class. A few of the rarer categories did not meet this minimum threshold due to the relatively low total area of those classes. The following categories had fewer than the target 25 point minimum: Impervious Under Canopy (class 4), Palustrine Scrub/Shrub Wetland (class 14), Palustrine Emergent Wetland (class 15), Estuarine Forested Wetlands (class 16), Estuarine Scrub/Shrub Wetlands (class 17), Unconsolidated Shore (class 19), Palustrine Aquatic Bed (class 22), and Estuarine Aquatic Bed (class 23). The correct land cover classification was determined through analyst interpretation of the imagery used in creating the map, as well as possible references to GoogleEarth in order to reference additional dates/seasons of imagery for that location. All points were interpreted by two analysts, plus a third who made a final determination when there was disagreement on the call. This analysis allowed for the use of fuzzy designations, or alternate calls to the truth category where that truth call may not have been completely obvious, or where point locations are located so they could possibly be more than one category. Completeness Report Data does not exist for all standard C-CAP categories. There are no pixels representing: Unclassified (class 1) or Perennial Ice/Snow (class 25). Conceptual Consistency Tests for logical consistency indicate that all row and column positions in the selected latitude/longitude window contain data. Conversion and integration with vector files indicates that all positions are consistent with earth coordinates covering the same area. Attribute files are logically consistent. This dataset was created as part of NOAA's Coastal Change Analysis Program (C-CAP), which is housed within the National Ocean Service, Office for Coastal Management (OCM). Contractor work was performed through NOAA’s Coastal Geospatial Services Contract (CGSC) vehicle. Initial Classification Initial 1m spatial resolution feature extraction for Impervious, Water, and Canopy (tree and scrub/shrub) mapping was conducted by Ecopia AI (https://www.ecopiatech.com/) using a proprietary feature recognition technology. This involves taking each image and classifying the pixels based on spectral and spatial properties, based on training examples and analyst refinement. Refined Classification The refinement of initial mapping layers, including the additional of up to 20 standard C-CAP categories of land cover feature types was conducted by NV5 (https://www.nv5.com/). Refinement specifics were broken down into a series of stages, and the specifics of each are discussed below. Impervious Surface Refinement: Commission and omission errors associated with the Impervious class were addressed through manual interpretation and clean up using OpenStreetMap road, building, and railroad layers as reference. Once the review and edits were complete, the refined Impervious class was incorporated back into the land cover data set. Water Refinement: Commission and omission errors associated with the Water class were addressed through a combination of modeling, expert rulesets, and manual interpretation. Once the review and edits were complete, the refined Water class was incorporated back into the land cover data set. Canopy Surface Refinement: Commission and omission errors associated with the Canopy class were addressed through manual interpretation and clean up. Once the review and edits were complete, the refined Canopy class was incorporated back into the land cover data set. Agriculture and Open Space Developed: Cultivated land, Pasture/Hay, and Open Space Developed features were derived from the grassland class of the initial land cover product using a combination of deep learning and image segmentation approaches. Predictions from a Convolutional Neural Network were summarized by image objects generated for grassland regions withing the AOI. Commission and omission errors associated with these categories were addressed through manual review and editing. Once the review and edits were complete, the new classes were incorporated into the land cover data set. Wetlands: Wetlands were derived through a modeling process which used ancillary data such as Soils (SSURGO), the National Wetlands Inventory (NWI), and topographic derivatives (derived from USGS OPR data). Forest, shrub and grassland objects within the initial land cover that exhibited hydric characteristics based on the input ancillary layers were designated to their appropriate wetland category. The process relied mainly on the NWI to determine palustrine and estuarine distinctions. Grass and Bare: Grass and Bare classifications were extracted from regions within the AOI not covered by the Ecopia AI Impervious, Water, and Canopy layer. This was accomplished through a combination of image segmentation, expert rulesets, and manual editing. Once the review and edits were complete, Bare and Grass features were incorporated into the land cover data set. Attributes for this product are as follows: 0 Background 1 Unclassified 2 Developed Impervious 3 4 Developed Impervious under Tree Canopy 5 Developed, Open Space 6 Cultivated Crops 7 Pasture/Hay 8 Grassland/Herbaceous 9 10 11 Upland Tree (Forest) 12 Scrub/Shrub 13 Palustrine Forested Wetland 14 Palustrine Scrub/Shrub Wetland 15 Palustrine Emergent Wetland 16 Estuarine Forested Wetland 17 Estuarine Scrub/Shrub Wetland 18 Estuarine Emergent Wetland 19 Unconsolidated Shore 20 Bare Land 21 Open Water 22 Palustrine Aquatic Bed 23 Estuarine Aquatic Bed 2026-04-28T00:00:00 External Contractor Ecopia AI https://www.ecopiatech.com/ WWW:LINK-1.0-http--link Source Citation URL Source Citation URL information originator 2021 External Contractor NV5 https://www.nv5.com/ WWW:LINK-1.0-http--link Source Citation URL Source Citation URL information originator