gov.noaa.nmfs.inport:56274 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 2026-04-30T00:00:00 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) C-CAP Land Cover, Erie County, Ohio, 2015 2019-05-28 publication NOAA/NMFS/EDM 56274 https://www.fisheries.noaa.gov/inport/item/56274 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information https://coast.noaa.gov/dataviewer/#/landcover/search/where:ID=8755 WWW:LINK-1.0-http--link Data Access Viewer Online Resource download https://coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires WWW:LINK-1.0-http--link Citation URL Online Resource download https://coast.noaa.gov/digitalcoast/data/ccaphighres WWW:LINK-1.0-http--link Citation URL Online Resource download imageDigital 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. The timeframe for this metadata is summer 2016. These maps are developed utilizing high resolution National Agriculture Imagery Program (NAIP) imagery, and can be used to track changes in the landscape through time. This trend information gives important feedback to managers on the success or failure of management policies and programs and aid in developing a scientific understanding of the Earth system and its response to natural and human-induced changes. This understanding allows for the prediction of impacts due to these changes and the assessment of their cumulative effects, helping coastal resource managers make more informed regional decisions. NOAA C-CAP is a contributing member to the Multi-Resolution Land Characteristics consortium and C-CAP products are included as the coastal expression of land cover within the National Land Cover Database. C-CAP is dedicated to the development, distribution, and application of land cover and change data for the coastal regions of the U.S. This effort is being conducted in close coordination with state coastal management agencies, the interagency Multi-Resolution Land Characteristics (MRLC) consortium, and the National Land Cover Database (NLCD). 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 Land Cover Land Cover Analysis Remotely Sensed Imagery/Photos theme Coastal Zone Erie County OH Ohio 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]: C-CAP Land Cover, Erie County, Ohio, 2015 [Data Date Range], https://www.fisheries.noaa.gov/inport/item/56274. 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: Data set is not 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 must assume responsibility to determine the usability of these data. unclassified eng; US imageryBaseMapsEarthCover Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 9.2.2.1350 -82.902 -82.338 41.28 41.485 | Currentness: Acquisition date of the NAIP imagery 2015 Attributes for this product are as follows: 0 Background, 1 Unclassified (Cloud, Shadow, etc), 2 Impervious, 3 4 5 Developed Open Space, 6 Cultivated Land, 7 Pasture/Hay, 8 Grassland, 9 10 11 Upland 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 Tundra, 25 Snow/Ice, Recommended Citation. NOAA Coastal Change Analysis Program (C-CAP) Regional Land Cover Database. Data collected 1995-present. Charleston, SC: National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management. Data accessed at coast.noaa.gov/landcover. 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://coast.noaa.gov/dataviewer/#/landcover/search/where:ID=8755 WWW:LINK-1.0-http--link Data Access Viewer Online Resource download https://coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires WWW:LINK-1.0-http--link https://coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires Online Resource download https://coast.noaa.gov/digitalcoast/data/ccaphighres WWW:LINK-1.0-http--link https://coast.noaa.gov/digitalcoast/data/ccaphighres Online Resource 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 270 total sample units distributed across the county. The accuracy of each class is as follows (Producer's, User's accuracies): Impervious (98.8%, 94.1%) Open Space Developed (80.8%, 89.1%) Cultivated (93.5%, 99.3%) Pasture/Hay (98.6%, 86.9%) Grassland (92.3%, 60.4%) Upland Forest (73.5%, 83.5%) Shrub/Scrub (87.5%, 83.4%) Palustrine Forested Wetland (84.9%, 100%) Palustrine Shrub/Scrub Wetland (63.5%, 79.4) Palustrine Emergent Wetland (89.2%, 81.7%) Unconsolidated Shore (N/A, N/A) Bare Land (100%, 100%) Water (100%, 99.0%) Palustrine Aquatic Bed (N/A, N/A) Overall accuracy (92.3%) Sample units were located using a stratified random distribution across the area with a minimum target number of 20. A few of the rare classes did not meet this threshold number. Unconsolidated Shore and Palustrine Aquatic Bed each received only one sample unit, not allowing for accuracy assessment calculations. Sample unit locations were initially established as a single coordinate. These locations were then used in eCognition software to generate image objects of homogenous land cover (based on the final map). The correct land cover call for the image objects were then determined through analyst interpretation of the imagery and ancillary data used to create the map. All sample units were interpreted by two analysts, plus a third who made the final determination when there was not agreement on the call. The accuracy assessment statistics were determined using area-weighted calculations (size of individual objects were factored into the calculations) as described in Congalton and Green (2019). Congalton, Russell G., and Kass Green. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. CRC Press, 2019. Completeness Report Data does not exist for all classes. There are no pixels representing class 9 (Deciduous Forest), 10 (Evergreen Forest), 24 (Tundra), 25 (Perennial Ice/Snow), 26 (Dwarf Scrub - Alaska specific class), 27 (Sedge/Herbaceous), and 28 (Moss - Alaska specific). Developed classes have been altered to exclude the percentage breakdown of impervious surfaces as the breakdown is not appropriate for high resolution mapping (Developed High Intensity (2), Developed Medium Intensity (3), and Developed Low Intensity (4) are reduced to Impervious (Class 2)). 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 by NOAA's Ocean Service, Office for Coastal Management (OCM). Random Forest Classification: The initial 1m spatial resolution 6 class high resolution land cover product was developed by EarthDefine using a Geographic Object-Based Image Analysis (GEOBIA) processing framework. This involves taking each image to be classified and grouping the pixels based on spectral and spatial properties into regions of homogeneity called objects. The resulting objects are the primary units for analysis. Additionally, these objects introduce additional spectral, shape, textural and contextual information into the mapping process and are utilized as independent variables in a supervised classification. Each object is labeled using a Random Forest Classifier which is ensemble version of a Decision Tree. Training data for the initial 6 classes (Herbaceous, Bare, Impervious, Water, Forest and Shrub) were generated through photo interpretation. The resulting Random Forest model was applied to the input data sets to create the initial automated map. Land Cover Refinement: Quantum Spatial took the initial automated map and made refinements to the existing land cover categories and incorporated new categories including Palustrine Forest, Palustrine Shrub, Palustrine Emergent, Palustrine Aquatic Bed, and Unconsolidated Shore. This work was performed through a combination of modeling in the object-based and pixel-based environment. USGS Color Orthoimagery (2015) served as the primary imagery data source. Ancillary data was collected from a variety of sources including the NOAA Digital Coast, National Wetland Inventory, Soil Survey Geographic Database, Open Street Maps, and the Ohio Geographically Referenced Information Program. This refined map was delivered to NOAA for final refinement. NOAA started with the refined map from Quantum Spatial and added Cultivated and Pastured land cover classes, as well as refining all land cover classes. Agriculture: Cultivated land and Pasture/Hay features were incorporated into the grassland category of the refined land cover product through a modeling process which relied on spectral data, parcel data from the state, 30m land cover from NOAA C-CAP, the National Land Cover Database, and the National Agriculture Statistics Service. Manual edits were made to the final classes. Impervious Surface and Open Space Developed: Ancillary data including road networks and parcel data were used in combination with spectral and spectral derivative data to refine these classes. Much of this refinement was performed on very small objects using parcel boundaries and vegetation indices to remove overestimated Impervious Surface (around buildings, along road edges, and in shadows). Open Space Developed was incorporated into areas as needed along road edges and homes, in industrial areas, and parks through a similar approach used to refine the impervious surface class. Additional cleanup was performed to remove speckle and slivers. Morphology and speckle: A final series of models were run on the land cover to clean-up illogical speckle (e.g. small grass feature in the middle of cultivated field) and refine the morphology of natural land cover classes. 2019-05-10T00:00:00