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 2015 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 2015 from
aerial imagery, 2015 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 2015 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.