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20260302
12264300
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ISO19115_3
FGDC CSDGM Metadata
24000
5000
dataset
Virginia Institute of Marine Science
SAV Data Administrator
804/684-7088
Rt. 1208 Greate Rd.
Gloucester Point
VA
32062
US
savadmin@vims.edu
20260302
ArcGIS Metadata
1.0
File Geodatabase Feature Class
19.2
Virginia SAV Habitat (2010 - 2024)
2024-12-18T00:00:00
Virginia Institute of Marine Science
vector digital data
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The 2024 distribution of submerged aquatic vegetation (SAV) in Chesapeake Bay and its tributaries was mapped from aerial multispectral digital imagery and satellite imagery. The aerial imagery was acquired between May and October 2024, with a resolution of 24 cm, encompassing 189 flight lines. Due to a number of challenges, additional imagery was acquired from Maxar, SpaceWill, and Planet Labs in order to provide a more complete dataset for Chesapeake Bay. These imagery sources and their locations are detailed below:</SPAN></P><UL><LI><P><SPAN>Aerial imagery was not acquired for portions of the Honga and Nanticoke Rivers and Fishing Bay. WorldView 2 satellite imagery acquired from Maxar through the NGA NextView program and PlanetScope satellite imagery from Planet Labs were used to map these areas.</SPAN></P></LI><LI><P><SPAN>Due to late imagery acquisition, SuperView Neo 1 imagery from SpaceWill and PlanetScope satellite imagery from Planet Labs were used to supplement the aerial imagery for the upper Potomac River, including Nanjemoy Creek. PlanetScope imagery was also used to supplement the aerial imagery for the Pamunkey and upper Rappahannock Rivers and WorldView 2 satellite imagery acquired from Maxar through the NGA NextView program was used to supplement the aerial imagery for the Big Annemessex, Manokin, and Little Choptank Rivers, and Pocomoke and Tangier Sounds, as well as the Chesapeake Bay Eastern Shore from Hungars Creek to Onancock Creek.</SPAN></P></LI><LI><P><SPAN>Due to turbid conditions, WorldView 2 satellite imagery acquired from Maxar through the NGA NextView program was used to supplement the aerial imagery for the Corrotoman, Piankatank, and lower Rappahannock Rivers, and Mobjack Bay.</SPAN></P></LI><LI><P><SPAN>WorldView 2 satellite imagery acquired from Maxar through the NGA NextView program was used to supplement the aerial imagery for the Back, Bush, Gunpowder, Middle, Patapsco, and Sassafras Rivers, and the Susquehanna Flats</SPAN></P></LI></UL><P><SPAN>Fifteen years of SAV data where SAV density was greater than 0 were combined and then dissolved to form SAV Habitat polygons. These polygons represent where SAV was located at least once during a period from 2010 to 2024. </SPAN></P></DIV></DIV></DIV>
SAV Habitat represents the area where Submerged Aquatic Vegetation (SAV) presence was surveyed at least once during a 15 year period from 2010 to 2024.
SAV Monitoring Program, Virginia Institute of Marine Science
Virginia Institute of Marine Science
SAV Data Administrator
804/684-7088
1370 Greate RD
Gloucester Point
VA
23062
US
savadmin@vims.edu
Chesapeake Bay
Chincoteague Bay
U.S. Postal State Abbreviations
VA
DE
MD
U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of The United States, and associated areas (Federal Information Processing Standard 5-2):Washington ,D. C., National Institute of Standards and Technology.
51
10
24
U.S. Department of Commerce, 1977, Countries, dependencies, areas of special sovereignty, and their principal administrative divisions (Federal Information Processing Standard 10-3):Washington, D.C., National Institute of Standards and Technology.
US
vegetative surface cover
submerged aquatic vegetation
SAV
ISO 19115 Topic Categories
biota
environment
vegetative surface cover
submerged aquatic vegetation
SAV
biota
environment
Chesapeake Bay
Chincoteague Bay
VA
DE
MD
51
10
24
US
Version 6.2 (Build 9200) ; Esri ArcGIS 10.8.0.12790
true
-77.588763
-74.999616
39.756832
36.653889
ground condition
2024-05-22T00:00:00
2024-10-19T00:00:00
1
-77.464109
-75.266856
38.902175
36.886454
The density attribute for all beds has been reviewed by an experienced photo-interpreter for correctness and consistency with analysis for prior years.
The density attribute for all beds has been reviewed by an experienced photo-interpreter for correctness and consistency with analysis for prior years.
The GIS data has been cross-checked against data tables and ground observations.
The dataset contains all SAV areas that were identified from the areas flown. Some areas that are presumed to contain no SAV were not flown. Some small beds, particularly along narrow tributaries may not have been distinguishable on the aerial photography.
Horizontal positional accuracy is based upon orthorectification of scanned aerial photography using USGS digital orthothophoto quadrangles for horizontal control and USGS 30m DEM data as vertical control. Horizontal RMSE for individual flightlines was held to less than four meters.
Horizontal positional accuracy of the imagery is evaluated as part of the orthorectification process throught the use of at least one check point for every two frames.
2024 SAV Aerial multispectral digital imagery Digital images 5/22/2022 - 10/19/2023
24000
2024 SAV Aerial imagery
2024 SAV Aerial imagery
2024-10-19T00:00:00
Aerialphotographics LLC
document
New 2004 Chesapeake Bay Program Segments adjusted to include land areas
New 2004 Chesapeake Bay Program Segments adjusted to include land areas
New 2004 Chesapeake Bay Program Segments adjusted to include land areas
2008-10-06
Virginia Institute of Marine Science
map
WorldView 2 satellite imagery acquired from Digital Globe through the NGA NextView program. SuperView Neo 1 imagery from SpaceWill. PlanetScope satellite imagery from Planet Labs.
2024 Auxiliary Imagery
2024 Auxiliary Imagery
State boundaries adjusted to include shore areas
State boundaries adjusted to include shore areas
State boundaries adjusted to include shore areas
2008-10-06
Virginia Instute of Marine Science
map
2024 SAV Orthophoto Mosaics Datasets 5/22/24 - 10/19/2024
24000
2023 SAV Orthophoto Mosaics
2023 SAV Orthophoto Mosaics
2023-11-01
Virginia Institute of Marine Science
document
Digital 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 images, National Agriculture Imagery Program (NAIP), Virginia Base Mapping Program (VBMP), MD Six Inch, and ESRI World 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 area combined into mosaic datasets for each flightline which are then combined into a single Bay-wide mosaic dataset.
2025-06-05T00:00:00
The SAV beds are interpreted on-screen from the orthophoto mosaics using ESRI ArcGIS 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 2024 from aerial satellite imagery, 2024 ground survey information, and aerial site surveys. WorldView 2 and 3 satellite imagery acquired from Digital Globe through the NGA NextView program, SuperView Neo 1 imagery from SpaceWill, PlanetScope satellite imagery from Planet Labs was used to augment the aerial imagery in portions of the Bay and tributaries where imagery had not been acquired because of highly turbid water, weather, and security restrictions during the acquisition phase. 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.
2025-12-15T00:00:00
The bay segments were overlayed on the dataset by VIMS staff, dividing any beds that fell into multiple segments.
2025-12-15T00:00:00
The state boundaries were overlayed on the dataset by VIMS staff, dividing any beds that fell into multiple states.
2025-12-15T00:00:00
27474
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beds24
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27474
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YEAR
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0
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0
0
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Esri
Positive real numbers that are automatically generated.
Shape_Area
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Double
8
0
0
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Esri
Positive real numbers that are automatically generated.
Simple
FALSE
27474
TRUE
FALSE