Coastal Bend Texas Benthic Habitat Mapping Redfish Bay 2004 Geoform

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Sample of benthic cover data

Date that the source FGDC record was last modified.

Converted from FGDC Content Standard for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.

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The digital orthophotography was developed from imagery acquired as part of the 2004 overflight of the State of Texas developed for the USDA National Agricultural Imagery Program (NAIP). In order to achieve a horizontal accuracy of 5 meters, CE90 it is necessary to reprocess the imagery incorporating new GPS field control. It should be noted that the imagery was not tide coordinated so tidal variation may exist between sorties. The imagery was acquired between November 3, 2004 and November 7,2004. | Source Geospatial Form: remote-sensing image | Type of Source Media: digital

TerraSurv, Inc. of Pittsburgh, PA was contracted by EarthData International of Frederick, MD to perform a geodetic control survey in support of mapping an area along the southeasterly coast of Texas between Port Lavaca and Brownsville. Thirty-eight photo identifiable locations were surveyed to provide ground control and quality assurance checks for the mapping. Twenty of the stations were used for mapping control and eighteen of the stations were used for quality checks. The horizontal datum was the North American Datum of 1983, CORS adjustment (NAD 1983 CORS). The vertical datum was the North American Vertical Datum of 1988 (NAVD 1988). | Source Geospatial Form: model | Type of Source Media: paper

The original 1m DOQQs for the project area were resampled to 2m and mosaicked. For habitat classification,the mosaicked imagery was divided into six processing one set of six mosaics for true color and one set of six mosaics for color-IR. Image segmentation was performed using on the blue, green, red, and near-infrared bands for each of the six processing areas. The classification of the habitat segments (as ESRI polygon shapefiles) was performed using CART analysis. The habitat maps for each of the six areas was refined with the aid of field data collected during May, June, and July 2006 and January 2007. The six processing area shapefiles were edgematched and combined into a single shapefile which was clipped to the final project area boundary and then clipped into six separate shapefiles representing the six bay systems in the project area. Adjacent bay systems do not overlap,resulting in no overlapping habitat polygons across the entire project area. Each polygon, within and across all six bay systems, has a unique polygon identification number.Each shapefile was checked for proper topology and to insure that each polygon has a correct habitat label,habitat code, modifier label if present, unique identification number, and an area calculation. Polygons below the 100m2 minimum mapping unit (MMU) were eliminated,though some polygons less than 100m2 were retained if their area changed to below the MMU due to the polygon boundary smoothing process.

The habitat data also went through an independent validation review. Accuracy assessment was performed on seven classes with Patchy SRV and Continuous SRV being combined into a single accuracy class. For field data collection, non-random sites in the form of polygons were chosen by analysts with an attempt to sample all available image signatures. These sites were visited in the field and data on each site was collected directly into digital format (ESRI shapefile) using a laptop or onto a paper form that was later entered into digital format.Sites were navigated to primarily using a Garmin GPS 76unit connected to a Panasonic Toughbook laptop displaying the project imagery and polygons in ArcMap v9.1 or using the GPS unit alone. Habitat classification was estimated as accurately as possible using different methods or combination of methods which included above water observation, snorkeling, wading, and underwater video. This data was entered into an ESRI shapefile via a digital field form in ArcMap specifically developed for this type of field data collection. After collection, sites were classified as either "sand" or "mud" bottom type using Texas Bureau of Economic Geology sediment maps. More sample polygon sites were collected in-office based on the in-field collected sites in order to meet the 50 sites per class per bottom type accuracy assessment requirement.Once all the sites were chosen, they were again divided into "sand" and "mud" bottom types. For each class, per bottom type, a random selector macro in ArcMap was used to randomly select 50 sites for accuracy assessment. The entire pool of accuracy sites was kept separate from the remaining sites and only used for accuracy assessment during the project. Anonymity of the accuracy sites was maintained throughout the project because it was unnecessary to ever visually review these sites in order to perform the accuracy analysis. More accuracy assessment sites were collected in a later field collection trip to add to the analysis. These sites were chosen by randomly selecting polygons within specific regions that were pre-determined to be visited. Information for these sites was collected using the same methods for the other sites. Accuracy information was compiled using ArcMap. Accuracy polygons were transformed into polygon centroid points forced to be located within the polygon. These points were used to select the corresponding polygons in the habitat map. The selected polygons' attributes were joined to the accuracy polygons so that each accuracy polygon had both the accuracy habitat label and its map label. An accuracy assessment error matrix was generated using this information by importing it to Microsoft Excel and building the matrix. Both deterministic and fuzzy accuracy assessment were performed. The accuracy analysis and error matrices are presented and discussed in the project final report entitled Coastal Bend of Texas Benthic Habitat Mapping Phase 1 Final Report.

The data were converted from a single ESRI polygon shapefile classified according to the System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) to the Coastal and Marine Ecological Classification Standard (CMECS) 2012 format (which can be found at https://coast.noaa.gov/digitalcoast/tools/cmecs-crosswalk) which produces separate geoform, geoform, and geoform feature layers from the original input benthic habitat dataset. This geoform feature layer contains CMECS geoform component attributes where an "Equal" or "Nearly Equal" SCHEME value was present in the original data. Polygons for which no geoform information was present have been removed. No other changes to the original polygon boundaries or any other alterations of the original SCHEME data were made during this process.