Digital multispectral imagery with a ground sample distance of 24cm and black and white aerial photography are carefully examined to identify all visible SAV beds. Aerial imagery covering SAV beds are orthorectified. Digital imagery is orthorectified and combined to create orthophoto mosaics. Outlines of SAV beds are then interpreted on-screen, providing a digital database for analysis of bed areas and locations. Ground survey information collected in 2016 is tabulated and entered into the SAV geographic information system (GIS).

USGS 7.5 minute quadrangle maps are used to organize the mapping process, including interpretation of SAV beds from aerial photography, mapping ground survey data, and compiling SAV bed area measurements. The SAV quadrangle index page gives locations of the 258 quadrangles in the study area that includes all regions with potential for SAV growth. Most quadrangles are sequentially numbered north to south for efficient access to data.

Orthorectification and Mosaic Production

Digital multispectral imagery is georectified and orthographically corrected to produce a seamless series of aerial mosaics following the standard operating procedures (SOP). ERDAS IMAGINE Photogrammetry image processing software is used to orthographically correct the individual flight lines using a bundle block solution. Camera lens calibration data is matched to the image location of fiducial points to define the interior camera model. Control points from USGS DOQQ, National Agriculture Imagery Program (NAIP), MD Dept. of IT, Virginia Base Mapping Program (VBMP), and ESRI Word imagery provide the exterior control, which is enhanced by a large number of image-matching tie points produced automatically by the software when IMU data were not available. The exterior and interior models are combined with a 10-meter resolution digital elevation model (DEM) from the USGS National Elevation Dataset (NED) to produce an orthophoto for each aerial photograph.

The orthophotographs are mosaicked use a set of ArcGIS mosaic datasets for each flight line that are mosacked into a single Baywide mosiac dataset that is shared as an ArcGIS image service.

Photo Interpretation and Bed Delineation

The SAV beds are interpreted on-screen from the orthophoto mosaics using ESRI ArcInfo GIS software. The identification and delineation of SAV beds by photo interpretation utilizes all available information including: knowledge of aquatic grass signatures on film, distribution of SAV in 2016 from aerial imagery, 2016 ground survey information, and aerial site surveys.

In addition to delineating SAV bed boundaries, an estimate of SAV density within each bed was made by visually comparing each bed to an enlarged crown density scale similar to those developed for estimating crown cover of forest trees from aerial photography (Paine, 1981). Bed density was categorized into one of four classes based on a subjective comparison with the density scale. These were: 1, very sparse (<10% coverage); 2, sparse (10-40%); 3, moderate (40-70%); or 4, dense (70-100%). Either the entire bed or subsections within the bed were assigned a bed density number (1 to 4) corresponding to the above density classes. Some beds were subsectioned to delineate variations of SAV density. Additionally, each distinct SAV bed or bed subsection was assigned an identifying one or two letter designation unique to its map. Coupled with the appropriate SAV quadrangle number and year of photography, these letter designations uniquely identify each SAV bed in the database.

Standard operating procedures (SOPs) were developed to facilitate orderly and efficient processing of 2016 SAV maps and SAV computer files produced from them, and to comply with the need for consistency, quality assurance, and quality control. SOPs included: a detailed procedure for orthorectification, mosaicking, and photo-interpretation; tracking sheets to record the processing of flight lines and quadrangles; and weekly summary progress reports of all operations.