{2FF66877-A037-4693-9718-D1870AA3F084} eng; USA utf8 dataset EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact 2025-02-13 ISO 19115 Geographic Information - Metadata ISO 19115:2003/Cor.1:2006(E) EnviroAtlas -- Durham, NC -- Meter-Scale Urban Land Cover (MULC) Data (2010) 2017-09-05 publication U.S. EPA Office of Research & Development (ORD) - National Exposure Research Laboratory (NERL) Research Triangle Park NC publisher US Environmental Protection Agency (US EPA) originator The EnviroAtlas Durham, NC Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from July 2010 at 1 m spatial resolution. Five land cover classes were mapped: impervious surface, soil and barren, grass and herbaceous, trees and forest, and water. An accuracy assessment using a stratified random sampling of 500 samples yielded an overall accuracy of 83 percent using a minimum mapping unit of 9 pixels (3x3 pixel window). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Durham, and includes the cities of Durham, Chapel Hill, Carrboro and Hillsborough, NC. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). The purpose of the Meter-Scale Urban Land Cover (MULC) is to provide a detailed snapshot of the urban environment and ecosystem for analysis of multiple human and ecosystem health metrics and services. This analysis is performed typically by U.S. Census block group. Greenspace and impervious surface land cover classes figure prominently. Land cover maps are integral to sound, scientific decision making and effective stewardship. A high-resolution urban land cover (LC) map quantitatively and qualitatively represents the physical environment and ecosystem matrix of a city. Land cover varies at a fine scale in urban environments, and the existing NLCD (National Land Cover Database, www.mrlc.gov) land cover maps at 30 m spatial resolution are too coarse to measure many urban phenomena. There are many possible applications, for example: - Knowing the exact location and size of green and gray spaces; - Identifying highly impervious areas that would most benefit from additional trees and other vegetation to mitigate surface runoff and urban heat island effects; - Measuring the width of urban riparian buffers; - Locating potential wildlife corridors, gaps and linkages; - Planning park development for maximum benefits. The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation. completed EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact asNeeded Ecology Ecosystem Environment Health Impact Land theme EPA GIS Keyword Thesaurus Agriculture Biophysical Communities Ecosystem Services EnviroAtlas Environment Environmental Atlas Green Space Land Land Cover Surface Water Water Wetlands theme EnviroAtlas North Carolina Durham, NC place None https://edg.epa.gov/EPA_Data_License.html otherRestrictions Use Constraints: None. Please check sources, scale, accuracy, currency and other available information. Please confirm that you are using the most recent copy of both data and metadata. Acknowledgement of the EPA would be appreciated. otherRestrictions Access Constraints: None. PUBLIC https://project-open-data.github.io/schema/#accessLevel Standard Technical Controls eng; USA environment geoscientificInformation imageryBaseMapsEarthCover -79.134618 -78.788325 35.844552 36.133857 2010-07-01 true Entity and Attribute Information Entity and Attribute Overview: For easier readability, this XML metadata can be opened in a text editor (e.g., Notepad). The Durham, NC Meter-Scale Urban Land Cover (MULC) dataset was developed using United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) Digital Orthophoto Quarter Quadrangles (DOQQ) ("quarter quads"). Each quarter quad contains 4 bands (visible red/green/blue and Near Infrared (NIR)) with 1 meter pixel resolution. The NAIP data is specified to be within 6 meters horizontal accuracy. We found very good alignment of the NAIP data with other data sets such as street and water layers, and Google and Bing maps. The National Hydrography Data (NHD+) was used to locate most water features. A supervised classification was performed using Genie Pro 2.3 feature extraction software (www.observera.com) to map the following land cover classes: Impervious Surface, Tree and Forest, Grass and Herbaceous, Soil and Barren and Water. Genie Pro uses genetic algorithms to generate solution algorithms that condition the data as input to the classifier. Synthetic bands (attributes) such as texture, band ratios and edges are created to increase the dimensionality of the data for better classification results. Training pixels were collected from multiple image quarter quads to capture and mitigate brightness variations and artifacts resulting from differences in sun angle and radiometric preprocessing of the flight lines. Multiple Genie Pro solution algorithms were applied to create the final product. Obvious errors in the classification were hand edited on all results files. Soil/Impervious Surface confusion and salt-and-pepper grass in forest canopy were the most common errors corrected. The land cover mosaic was reclassified using a modified Anderson Level 1 classification similar to that used for the North American Land Cover Data 2001 (NLCD) with the following classes: 0 - Unclassified 10 - Water 20 - Impervious Surface 30 - Soil & Barren 40 - Trees & Forest 70 - Grass & Herbaceous 80 - Agriculture 91 - Woody Wetlands 92 - Emergent Wetlands. *12/2016 UPDATE: A 2016 quality assurance review of EnviroAtlas Communities MULC data revealed some minor issues that required update in certain communities. These updates consisted of correction of areas of misclassified pixels, and less frequently, correction of areas with artifacts that caused an apparent reduction in spatial resolution over limited areas. In Durham, NC such areas constituted <1 percent of the total study area and did not measurably change the overall accuracy of the classification. These areas were marked and reclassified to the correct classes using ArcMap and Genie Pro. Also, the prior published Durham, NC data included areas beyond the study area boundary. This land cover product was clipped to match the 2010 US Census Urban Area boundary plus 1 km buffer (https://www.epa.gov/enviroatlas/enviroatlas-spatial-extents). Please make sure to use the most up to date version of this land cover product. A stratified random sample of approximately 100 points per land cover class was generated to assess the accuracy of the classified land cover map. To reduce the number of sample points on edges of landscape features (ambiguous or impossible to interpret), only points contained in homogeneous patches at least 3x3 pixels (3x3 meters) were used in the sample. A shapefile of sampling points was provided to two analysts who had not been involved with generating the land cover map. They performed photo interpretation of the five hundred validation points on the original NAIP imagery used to develop the land cover map, assigning a land cover class to each point. Ancillary data such as Google Satellite and Street Views, and Bing Aerial and Birdseye views, were used as needed to substantiate the interpretation. The following error matrix summarizes the accuracy assessment data. For easier readability, this XML metadata can be opened in a text editor (e.g., Notepad) and the confusion matrix may be copied from text editor to an Excel spreadsheet. Confusion matrices can also be viewed in original formatting by opening in ArcCatalog: Impervious Soil Forest Grass Water Row Total User's Accuracy Impervious 80 4 3 13 0 100 80.00% Soil 1 65 9 24 1 100 65.00% Forest 1 1 93 5 0 100 93.00% Grass 5 0 16 79 0 100 79.00% Water 0 1 1 0 98 100 98.00% Column Total 87 71 122 121 99 500 Producer's Accuracy 91.95% 91.55% 76.23% 65.29% 98.99% Overall Accuracy: 83.00% Entity and Attribute Detail Citation: https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas distributor https://enviroatlas.epa.gov/download/DNC_MULC_tif.zip download Download The URL providing direct access to the downloadable dataset. download https://enviroatlas.epa.gov/arcgis/rest/services/Supplemental/Landcover_AllCommunities/ImageServer ESRI:ArcGIS API The endpoint of a web service to access the dataset (REST endpoint, WMS GetCapabilities URL, or a SOAP WSDL endpoint). webMapService https://www.epa.gov/enviroatlas/enviroatlas-data information Documentation URL for accessing related documents such as data dictionary, technical information about a dataset, developer documentation, etc. information https://www.epa.gov/enviroatlas information Home Page Alternative landing page used to redirect user to a contextual, Agency-hosted "homepage" for the Dataset or API information dataset Horizontal Positional Accuracy Report Data were collected using methods that are accurate to within 2-5 meters (EPA National Geospatial Data Policy [NGDP] Accuracy Tier 2). For more information, please see EPA's NGDP at https://www.epa.gov/geospatial/geospatial-policies-and-standards) Features represented have not been tested for completeness Features represented have not been tested for completeness Tests for integrity have not been performed. This lineage was generated by the FGDC CSDGM to 19139 transformation Acquire full resolution, four band (blue green red infrared), 1 meter pixel, uncompressed GeoTIFF aerial photo quarter quadrangles from USDA APFO (Aerial Photography Field Office). 2011-01-01T00:00:00 Visually inspect mosaic of aerial photo quarter quadrangles for errors, image quality, illumination and preprocessing artifacts, etc. Illumination differences between tiles (and acquisition dates). 2011-01-01T00:00:00 Visually estimate the land cover types present on the landscape, with support from ancillary GIS data and literature. 2011-01-01T00:00:00 Plan an image processing workflow appropriate for the combination of local land cover and landscape, data quality, ancillary data, and capacity of image classification algorithms. 2011-01-01T00:00:00 Perform supervised classification on the imagery using genetic algorithms in the Genie Pro software (version 2.3) (www.observa.com). 2011-01-01T00:00:00 Display a quarter quadrangle NAIP tile in Genie Pro. Collect representative training pixels of Durham land cover. 2011-01-01T00:00:00 Evolve an algorithm to classify the image into land cover classes. 2011-01-01T00:00:00 Add and remove training pixels as necessary to improve algorithm performance. 2011-01-01T00:00:00 Evaluate results by comparing classified map with photo interpreted reference points in the NAIP image. 2011-01-01T00:00:00 Add and remove training pixels as necessary to iterate and improve the algorithm. 2011-01-01T00:00:00 Overlay NHD+ (National Hydrography Data Plus) to identify surface waters. 2011-01-01T00:00:00 Search for additional water using near infrared band. 2011-01-01T00:00:00 Combine the classified individual tiles into a seamless mosaic using ENVI 4.8. 2011-01-01T00:00:00 Stratified random sample: 100 points per land cover class. Generate a set of coordinates for map validation using ENVI 4.8. 2011-01-01T00:00:00 Randomize the 500 validation points and provide to an analyst other than the land cover map developer to avoid bias. 2011-01-01T00:00:00 Analyst 2 photo-interprets and records the land cover type at each coordinate on the original NAIP imagery. Refer to supplementary information such as Google Maps or Bing aerial imagery in case of ambiguity in photo interpretation of the validation points. 2011-01-01T00:00:00 Construct a confusion matrix using the validation data collected by Analyst 2. 2011-01-01T00:00:00 Evaluate errors of omission and commission. Overall accuracy for Durham = 82%. See error matrix in Entity and Attribute Information. 2011-01-01T00:00:00 (Use of trade names does not imply endorsement by the authors or US E.P.A.) 2011-01-01T00:00:00 unknown 2029-02-13 This metadata was automatically generated from the FGDC Content Standard for Digital Geospatial Metadata standard (version FGDC-STD-001-1998) using the 2024-02-09T11:11:00 version of the FGDC CSDGM to ISO 19139 transform. EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact