Data Management Plan

In 2006 and 2007 the NOAA Office for Coastal Management purchased services to process existing and new digital multi-spectral imagery and create digital benthic habitat data from this imagery for selected Texas coastal bend bays.The Center worked cooperatively with Fugro-EarthData, the Texas Parks and Wildlife Department (TPWD) and the Texas A and M University Center for Coastal Studies to develop benthic habitat data, primarily Submerged Aquatic Vegetation(SAV) for several coastal bays. This data will support the state's recently adopted Seagrass Monitoring Program which calls for regional mapping of SAV for status and trends assessment. The Center, Texas A and M, and TPWD have coordinated on the requirements of this project.

Original contact information:

Contact Org: NOAA Office for Coastal Management

Phone: 843-740-1202

Email: coastal.info@noaa.gov

Process Steps:

• 2009-02-03 00:00:00 - The original 1m DOQQs for the project area were resampled to 2m and mosaicked into a single four-band image. Image segmentation was performed using Definiens Professional. The classification of the habitat segments(as ESRI polygon shapefiles) was performed using CART analysis. The habitat map was refined with the aid of field data collected during May and July of 2008. The final habitat shapefile clipped to the final project area boundary. Each polygon has a unique polygon identification number in the attribute table (field"POLY_ID"). The final 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 a independent validation review.Accuracy assessment was performed on seven classes with Patchy SRV and Continuous SRV being combined into a single SRV 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 methods or combination of methods which included above water observation, snorkeling, wading, and underwater video.This data were entered into an ESRI shapefile via a digital field form in ArcMap specifically developed for this type of field data collection. More sample polygon sites were collected in-office based on the in-field collected sites in order to meet the 30 sites per class accuracy assessment requirement. For each class, a random selector macro in ArcMap was used to randomly select 30 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 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.The zonal stats tool in ArcMap was used to determine the majority map class each accuracy polygon intersected with. 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 Final Accuracy Assessment Report. (Citation: San Antonio Espiritu Santo Bay Digital Orthoimagery)
• 2015-01-01 00:00:00 - 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, biotic, and biotic feature layers from the original input benthic habitat dataset. This biotic feature layer contains CMECS biotic component attributes where an "Equal" or "Nearly Equal" SCHEME value was present in the original data. Polygons for which no biotic 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.