In 2006 and 2007 the NOAA Coastal Services Center purchased services to process existing digital multi-spectral imagery (ADS-40) 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.
These data have been created to support change detection, and to inform coastal management research and decision making.
The geographic extent of San Antonio and Espiritu Santo Bays is ~370mi2. Benthic habitat data was generated from 2007 orthoimagery collect with an UltraCam digital camera for all estuarine lands below mean high water within the study area. No benthic data was required for the marine side of the barrier beaches.
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NOAA Coastal Services Center
Horizontal accuracy of the source imagery was verified to exceed the project specification of +/- 5 meters CE95 of position on the ground.Overall final thematic map deterministic accuracy is 90%and overall fuzzy accuracy is 91%, which exceeds the contract standard of 85%. Additionally, 13 of the 14 final individual class producer's and user's deterministic accuracies exceed the contract standard of 80%. The deterministic user's accuracy for emergent marsh is 76%.All of the individual class producer's and user's fuzzy accuracies exceed the contract standard of 80%. Detailed error matrices can be found in the thematic accuracy report.
Eight photo-identified ground control check points were established for the purpose of assessing the accuracy of the final orthoimagery. These points were randomly distributed over the San Antonio Espiritu Santo Bay area. Two of the control points fell outside the project extent,and one additional point was discarded, as it was not associated with a well-defined feature. The five remaining points were used to calculate the accuracy of the orthoimagery. For the final map product Initial Map accuracy assessment was used as a tool to prioritize areas for further field examination and after field investigation to prioritize those areas where additional modeling or interpretation was needed. Error matrices showing both deterministic and fuzzy accuracies were compiled for the initial map. Based on the results compiled from the assessment, the team visit any classes exhibiting inaccuracy and addressed the classes through modeling, additional analysis or manual editing.
Compliance with the accuracy standard for the imagery was ensured by the placement of photo-identifiable ground control check points. Compliance with the accuracy standard for the final map product was ensured by field checks and manual editing.
The orthoimagery was produced by Sanborn Map Company, Inc. for NOAA. The imagery for the San Antonio Espiritu Santo Bay project was acquired on December 5,2007 and the orthoimagery and horizontal analysis was completed on January 28, 2007.
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 ArcMapv9.1 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.
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