Integrated Report 2022 (references)

The NC Department of Environmental Quality’s Integrated Water Quality Report checks to see if North Carolina’s waterways meet federal and state standards every two years. It incorporates information from multiple data sources, such as local monitoring programs and voluntary work, to group bodies of water into five categories:

Category 1: Waters meet all standards.

Category 2: Waters meet some standards.

Category 3: Waters lacking enough data.

Category 4: Impaired waters with a plan.

Category 5: Impaired water and need a plan.

The data varies in quality and coverage, and not all water bodies are monitored equally, leading to some limitations in assessing smaller or remote areas.

https://www.deq.nc.gov/about/divisions/water-resources/water-planning/modeling-assessment/water-quality-data-assessment

https://ncdenr.maps.arcgis.com/apps/instant/sidebar/index.html?appid=06dda86e607b4ac6861b19b905c82a8f

https://ncdenr.maps.arcgis.com/apps/mapviewer/index.html?layers=37696e11dac34786bdc94db84d54ff70

NC DEQ AFO ANIMAL FEEDING OPERATION:

The AFO (Animal Feeding Operations) program at NC DEQ manages permit applications for big farm operations, such as those raising hogs, chickens and cows. These farms have to comply with regulations on the disposal of waste for water quality reasons. The permits are reviewed every five years to make sure that they’re up to date. Program data are collected through inspections and reports, but they don’t always provide an accurate picture of the environmental impact, and tracking varies by farm. Its limitations are inconsistencies of data and incomplete monitoring of waste management at every site.

https://www.deq.nc.gov/about/divisions/water-resources/permitting/animal-feeding-operations

NC Surface Water Supply Watersheds

In NC DEQ’s Surface Water Supply Watersheds maps, waterbodies are assigned to uses such as drinking water, swimming or fishing. These categories set the boundaries for water quality management to safeguard public health and ecosystems. They are based on water monitoring systems and scientific research, but the uncertainties are fluctuating water quality and monitoring performance. These classifications might have to be updated as water use varies.

https://www.deq.nc.gov/about/divisions/water-resources/water-planning/classification-standards/classifications

NPDES Wastewater Discharge Permits

NPDES Wastewater Discharge Permits regulate treatment facilities’ discharge of treated wastewater into rivers and lakes to protect water quality. The permits cap the concentration of contaminants according to the water in place. They are the result of daily monitoring and assessments, though sometimes facilities can vary how these are tracked and reported which can impact the consistency of enforcement.

https://www.deq.nc.gov/about/divisions/water-resources/permitting/npdes-wastewater

DWR FISH TISSUE MONITORING DATA

The DWR Fish Tissue Monitoring Program inspects North Carolina waterways for heavy metals, pesticides and PCBs (Polychlorinated Biphenyls). PCBs are industrial chemicals that build up in fish, and they are harmful if consumed. It’s data that are used to issue fish-consumption advisories to help keep people safe. They collect samples by electrofishing (which consists of fish that humans eat). Constraints: data are not collected in every watershed, and older data don’t necessarily reflect recent pollution.

https://www.deq.nc.gov/about/divisions/water-resources/water-sciences/biological-assessment-branch/dwr-fish-tissue-monitoring-data

November 2022 VersionThis dataset represents the "Observed Distribution" for coho salmon in California by using observations made only between 1990 and the present. It was developed for the express purpose of assisting with species recovery planning efforts. The process for developing this dataset was to collect as many observations of the species as possible and derive the stream-based geographic distribution for the species based solely on these positive observations.For the purpose of this dataset an observation is defined as a report of a sighting or other evidence of the presence of the species at a given place and time. As such, observations are modeled by year observed as point locations in the GIS. All such observations were collected with information regarding who reported the observation, their agency/organization/affiliation, the date that they observed the species, who compiled the information, etc. This information is maintained in the developers file geodatabase (©Environmental Science Research Institute (ESRI) 2016).To develop this distribution dataset, the species observations were applied to California Streams, a CDFW derivative of USGS National Hydrography Dataset (NHD) High Resolution hydrography. For each observation, a path was traced down the hydrography from the point of observation to the ocean, thereby deriving the shortest migration route from the point of observation to the sea. By appending all of these migration paths together, the "Observed Distribution" for the species is developed.It is important to note that this layer does not attempt to model the entire possible distribution of the species. Rather, it only represents the known distribution based on where the species has been observed and reported. While some observations indeed represent the upstream extent of the species (e.g., an observation made at a hard barrier), the majority of observations only indicate where the species was sampled for or otherwise observed. Because of this, this dataset likely underestimates the absolute geographic distribution of the species.It is also important to note that the species may not be found on an annual basis in all indicated reaches due to natural variations in run size, water conditions, and other environmental factors. As such, the information in this dataset should not be used to verify that the species are currently present in a given stream. Conversely, the absence of distribution linework for a given stream does not necessarily indicate that the species does not occur in that stream. The observation data were compiled from a variety of disparate sources including but not limited to CDFW, USFS, NMFS, timber companies, and the public. Forms of documentation include CDFW administrative reports, personal communications with biologists, observation reports, and literature reviews. The source of each feature (to the best available knowledge) is included in the data attributes for the observations in the geodatabase, but not for the resulting linework. The spatial data has been referenced to California Streams, a CDFW derivative of USGS National Hydrography Dataset (NHD) High Resolution hydrography.Usage of this dataset:Examples of appropriate uses include:- species recovery planning- Evaluation of future survey sites for the species- Validating species distribution modelsExamples of inappropriate uses include:- Assuming absence of a line feature means that the species are not present in that stream.- Using this data to make parcel or ground level land use management decisions.- Using this dataset to prove or support non-existence of the species at any spatial scale.- Assuming that the line feature represents the maximum possible extent of species distribution.All users of this data should seek the assistance of qualified professionals such as surveyors, hydrologists, or fishery biologists as needed to ensure that such users possess complete, precise, and up to date information on species distribution and water body location.Any copy of this dataset is considered to be a snapshot of the species distribution at the time of release. It is impingent upon the user to ensure that they have the most recent version prior to making management or planning decisions.Please refer to "Use Constraints" section below.

Use this country model layer when performing analysis within a single country. This layer displays a single global land cover map that is modeled by country for the year 2050 at a pixel resolution of 300m. ESA CCI land cover from the years 2010 and 2018 were used to create these predictions. Variable mapped: Projected land cover in 2050. Data Projection: Cylindrical Equal Area Mosaic Projection: Cylindrical Equal Area Extent: Global Cell Size: 300m Source Type: Thematic Visible Scale: 1:50,000 and smaller Source: Clark University Publication date: April 2021What you can do with this layer? This layer may be added to online maps and compared with the ESA CCI Land Cover from any year from 1992 to 2018. To do this, add Global Land Cover 1992-2018 to your map and choose the processing template (image display) from that layer called “Simplified Renderer.” This layer can also be used in analysis in ecological planning to find specific areas that may need to be set aside before they are converted to human use. Links to the six Clark University land cover 2050 layers in ArcGIS Living Atlas of the World:There are three scales (country, regional, and world) for the land cover and vulnerability models. They’re all slightly different since the country model can be more fine-tuned to the drivers in that particular area. Regional (continental) and global have more spatially consistent model weights. Which should you use? If you’re analyzing one country or want to make accurate comparisons between countries, use the country level. If mapping larger patterns, use the global or regional extent (depending on your area of interest). Land Cover 2050 WorldLand Cover 2050 RegionalLand Cover 2050 CountryLand Cover Vulnerability Change 2050 WorldLand Cover Vulnerability Change 2050 RegionalLand Cover Vulnerability Change 2050 CountryWhat these layers model (and what they don’t model) The model focuses on human-based land cover changes and projects the extent of these changes to the year 2050. It seeks to find where agricultural and urban land cover will cover the planet in that year, and what areas are most vulnerable to change due to the expansion of the human footprint. It does not predict changes to other land cover types such as forests or other natural vegetation during that time period unless it is replaced by agriculture or urban land cover. It also doesn’t predict sea level rise unless the model detected a pattern in changes in bodies of water between 2010 and 2018. A few 300m pixels might have changed due to sea level rise during that timeframe, but not many. The model predicts land cover changes based upon patterns it found in the period 2010-2018. But it cannot predict future land use. This is partly because current land use is not necessarily a model input. In this model, land set aside as a result of political decisions, for example military bases or nature reserves, may be found to be filled in with urban or agricultural areas in 2050. This is because the model is blind to the political decisions that affect land use. Quantitative Variables used to create Models Biomass Crop Suitability Distance to Airports Distance to Cropland 2010 Distance to Primary Roads Distance to Railroads Distance to Secondary Roads Distance to Settled Areas Distance to Urban 2010 Elevation GDP Human Influence Index Population Density Precipitation Regions Slope Temperature Qualitative Variables used to create Models Biomes Ecoregions Irrigated Crops Protected Areas Provinces Rainfed Crops Soil Classification Soil Depth Soil Drainage Soil pH Soil Texture Were small countries modeled?Clark University modeled some small countries that had a few transitions. Only five countries were modeled with this procedure: Bhutan, North Macedonia, Palau, Singapore and Vanuatu.As a rule of thumb, the MLP neural network in the Land Change Modeler requires at least 100 pixels of change for model calibration. Several countries experienced less than 100 pixels of change between 2010 & 2018 and therefore required an alternate modeling methodology. These countries are Bhutan, North Macedonia, Palau, Singapore and Vanuatu. To overcome the lack of samples, these select countries were resampled from 300 meters to 150 meters, effectively multiplying the number of pixels by four. As a result, we were able to empirically model countries which originally had as few as 25 pixels of change. Once a selected country was resampled to 150 meter resolution, three transition potential images were calibrated and averaged to produce one final transition potential image per transition. Clark Labs chose to create averaged transition potential images to limit artifacts of model overfitting. Though each model contained at least 100 samples of "change", this is still relatively little for a neural network-based model and could lead to anomalous outcomes. The averaged transition potentials were used to extrapolate change and produce a final hard prediction and risk map of natural land cover conversion to Cropland and Artificial Surfaces in 2050. 39 Small Countries Not ModeledThere were 39 countries that were not modeled because the transitions, if any, from natural to anthropogenic were very small. In this case the land cover for 2050 for these countries are the same as the 2018 maps and their vulnerability was given a value of 0. Here were the countries not modeled:AndorraAntigua and BarbudaBarbadosCape VerdeComorosCook IslandsDjiboutiDominicaFaroe IslandsFrench GuyanaFrench PolynesiaGibraltarGrenadaGuamGuyanaIcelandJan MayenKiribatiLiechtensteinLuxembourgMaldivesMaltaMarshall IslandsMicronesia, Federated States ofMoldovaMonacoNauruSaint Kitts and NevisSaint LuciaSaint Vincent and the GrenadinesSamoaSan MarinoSeychellesSurinameSvalbardThe BahamasTongaTuvaluVatican CityIndex to land cover values in this dataset: The Clark University Land Cover 2050 projections display a ten-class land cover generalized from ESA Climate Change Initiative Land Cover. 1 Mostly Cropland 2 Grassland, Scrub, or Shrub 3 Mostly Deciduous Forest 4 Mostly Needleleaf/Evergreen Forest 5 Sparse Vegetation 6 Bare Area 7 Swampy or Often Flooded Vegetation 8 Artificial Surface or Urban Area 9 Surface Water 10 Permanent Snow and Ice

"The hydro layer was digitized from the 2002 Virginia Base Mapping Program (VBMP) imagery. This hydro layer includes rivers, streams, ponds, lakes, and other bodies of water. Attribution of this data set is limited. It does not indicate the directional flow of water. The supplemental METADATA file included with the data contains an image below the Hydrography section that shows the hydro layer (left side of illustration) and the hydro layer superimposed on top of aerial photography (right side of the illustration). Also note that only visible water resources were digitized. (Water passing below underpasses were not digitized). This data set is the most spatially accurate available, but it does not conform to National Hydrography Dataset (NHD) specifications (due to limitations associated with attribution, water flow, segmentation, and connectivity). Intermittent streams are likely not contained in this file. Data was only collected in canals and ditches where water was visible (using aerial photography from spring 2002. It should be noted that 2002 was an exceptionally dry spring in Virginia). Ancillary data included in this dataset or from other sources (including the Digital Elevation Model (DEM), contour lines, and even the Digital Raster Graphic [DRG] can be integrated with this file to support the delineation of flow direction. Spatial hydrologic features include:Streams and Rivers – Only streams with visible water will be collected. Streams will be single line up to 8 feet wide for 100 scale, or 30 feet wide for 200 and 400 scale. Double lines, representing left and right bank, will be collected where those dimensions are exceeded. Lakes and Ponds – Lakes and ponds will not be differentiated. Only lakes and ponds with visible water will be collected. The minimum dimension for collection is 100 feet in length or width. Canals and Ditches – Canals and ditches will not be differentiated. Only canals and ditches with visible water will be collected. Canals and ditches will be single line up to 8 feet wide for 100 scale, or 30 feet wide for 200 and 400 scale. Where those dimensions are exceeded, two lines will be placed, one to represent each bank. Swamps and Marshes – Swamps and marshes will not be differentiated. Only clearly identifiable swamps and marshes will be collected. The minimum dimension for collection is 1,000 feet in length or width. Shorelines – Shorelines for the Atlantic Ocean and Chesapeake Bay will be collected at the visible land/water interface. If the shoreline is bordered by tidal marsh, the shoreline will be collected at the land/marsh interface, not the marsh/ water interface. Tidal marshes will be collected in Layer 4. For more information on this data refer to the supplemental metadata pdf found at: https://secure-archive.gis.vt.edu/gisdata/public/UnitedStates/Virginia/VCE_2002_metadata/METADATA.pdfThis data has been curated by the Virginia Cooperative Extension at Virginia Tech and Virginia Tech University Libraries. This data is meant for general use only. Virginia Tech’s University Library is acting as a steward for this data and any questions about its use should refer to our Terms of Use Page."

"The hydro layer was digitized from the 2002 Virginia Base Mapping Program (VBMP) imagery. This hydro layer includes rivers, streams, ponds, lakes, and other bodies of water. Attribution of this data set is limited. It does not indicate the directional flow of water. The image below shows the hydro layer (refer to left side of illustration in supplemental METADATA file for Hydrography) and the hydro layer superimposed on top of aerial photography (refer to right side of the illustration in supplemental METADATA file for Hydrography). Also note that only visible water resources were digitized. (Water passing below underpasses was not digitized). This data set is the most spatially accurate available, but it does not conform to National Hydrography Dataset (NHD) specifications (due to limitations associated with attribution, water flow, segmentation, and connectivity). Intermittent streams are likely not contained in this file. Data was only collected in canals and ditches where water was visible (using aerial photography from spring 2002 . It should be noted that 2002 was an exceptionally dry spring in Virginia).Ancillary data sets contained on this CD or from other sources (including the Digital Elevation Model (DEM), contour lines, and even the Digital Raster Graphic [DRG] can be integrated with this file to support the delineation of flow direction. Spatial hydrologic features include:Streams and Rivers – Only streams with visible water will be collected. Streams will be single line up to 8 feet wide for 100 scale, or 30 feet wide for 200 and 400 scale. Double lines, representing left and right bank, will be collected where those dimensions are exceeded. Lakes and Ponds – Lakes and ponds will not be differentiated. Only lakes and ponds with visible water will be collected. The minimum dimension for collection is 100 feet in length or width. Canals and Ditches – Canals and ditches will not be differentiated. Only canals and ditches with visible water will be collected. Canals and ditches will be single line up to 8 feet wide for 100 scale, or 30 feet wide for 200 and 400 scale. Where those dimensions are exceeded, two lines will be placed, one to represent each bank. Swamps and Marshes – Swamps and marshes will not be differentiated. Only clearly identifiable swamps and marshes will be collected. The minimum dimension for collection is 1,000 feet in length or width. Shorelines – Shorelines for the Atlantic Ocean and Chesapeake Bay will be collected at the visible land/water interface. If the shoreline is bordered by tidal marsh, the shoreline will be collected at the land/marsh interface, not the marsh/water interface. Tidal marshes will be collected in Layer 4. For more information on this data refer to the supplemental metadata pdf found at: https://secure-archive.gis.vt.edu/gisdata/public/UnitedStates/Virginia/VCE_2002_metadata/METADATA.pdfThis data has been curated by the Virginia Cooperative Extension at Virginia Tech and Virginia Tech University Libraries. This data is meant for general use only. Virginia Tech’s University Library is acting as a steward for this data and any questions about its use should refer to our Terms of Use Page."

Forest Inventory is the foundation of forest management planning in which AACs are based on. Features contained in this layer represents the classification and delineation of different landscape features, especially forest types. The current system uses softcopy technology containing high quality imagery to update and re-define the existing Forest Inventory Landbase.This layer is administered by the Forest Ecosystem Management Division, Department of Fisheries, Forestry and Agriculture. Information referenced within this dataset represents the most current information available.Feature and Attribute DescriptionsStreamsThese are single-line features. A watercourse that appears less than 2mm in width on a 1:12,500 scale photo is classified as a single-line stream.Stream Attribute DomainCode*Code DescriptionDescription1Definite StreamA stream that flows continuously throughout the year, regardless of weather or seasonal changes. It is typically fed by a consistent water source, such as groundwater or a spring, ensuring uninterrupted flow. 2Intermittent StreamA stream that flows only during certain times of the year, such as during rainy seasons or periods of snowmelt. These streams may dry up during extended dry periods when there is insufficient water supply. 3Indeterminate StreamA stream whose flow pattern is not well-defined or predictable. Ot may not have a consistent or seasonal flow and could vary depending on various environmental or climatic factors. Waterbody HazardThese are any watercourse hazards (i.e. rapids, falls).Waterbody Hazard Attribute DomainCode*Code DescriptionDescription1RapidsRapids are fast-flowing sections of a river or stream characterized by turbulent water. 2FallsWaterfalls, or falls, happen when a river or stream drops abruptly over a cliff or steep incline, creating a cascading flow of water.Waterbody (Line)These are waterbody shorelines.Waterbody Line Attribute DomainCode*Code DescriptionDescription1Lake/PondThe shoreline of a lake or pond is the boundary where the water meets the surrounding land. 2RiverThe shoreline of a river refers to the banks that border its flow. 3CoastlineA coastline is the interface between land and the ocean or a sea.4Virtual LineA virtual line in the context of waterbodies could refer to an abstract or conceptual boundary, often used in mapping or analysis. WaterbodyWaterbodies, including rivers. Waterbodies include saltwater and freshwater ponds and lakes. Waterbody Attribute DomainCode*Code DescriptionDescription1Lake/PondThe shoreline of a lake or pond is the boundary where the water meets the surrounding land. 2RiverThe shoreline of a river refers to the banks that border its flow. The Forest is classified on the following criteria below:Species CompositionSpecies comprising to ≥ 25% of the total basal area are to be listed. No more than 3 species may be used to define a stand type. Species Code Species Symbol Species Composition

Balsam Fir bF One Species (e.g., bF): indicates that > 75% of the basal area in the stand is comprised of a single species.

Black Spruce bS

Balsam Popular bP

European Larch eL

Jack Pine jP

Japanese Birch jB Two Species (e.g., bFwB): indicates that at least 50% of the basal area in the stand is comprised of the first identified species and 25-49% of the basal area is comprised of the second identified species. Any other species present are considered minor components.

Japanese Larch jL

Lodgepole Pine IP

Red Maple rM

Red Pine rP

Scots Pine sP

Sitka Spruce sS Three Species (e.g., bFbSwB): indicates that each species comprises at least 25% of the basal area and the species are listed in order of predominance; the first species comprises up to 50% and the other species 25-33%

Trembling Aspen tL

White Birch wB

White Pine wP

White Spruce wS

Yellow Birch yB Species codes, symbols and composition standards for major tree species in Newfoundland and Labrador.Age ClassBased on the total age of dominant or co-dominant trees the forest is separated according to the following age classes. Codes for Insular Newfoundland Codes for Labrador

Age Class Code Age Class Code

1-20 (Regenerating) 1 1-20 (Regenerating) 1

21-40 (Immature) 2 21-40 (Immature) 2

41-60 (Semi-mature) 3 41-60 (Immature) 3

61-80 (Mature) 4 61-80 (Semi-mature) 4

81-100 (Over-mature) 5 81-100 (Semi-mature) 5

101-120 (Over-mature) 6 101-120 (Mature) 6

121+ (Over-mature) 7 121-140 (Mature) 7

Uneven-aged 9 141-160 (Over-mature) 8

161+ (Over-mature) 9 Age classes for productive forest stands in Newfoundland and Labrador.Height ClassHeight class designation is based on the height of dominant or co-dominant trees.Height ClassHeight Code0 - 3.5 meters13.6 - 6.5 meters26.6 - 9.5 meters39.6 - 12.5 meters412.6 - 15.5 meters515.6 - 18.5 meters618.6 - 21.5 meters721.6 +8Height class codes for productive forest stands.Crown ClosureStands are described according to the degree of stocking. Ideally basal area can be used as an expression of stocking; however, it cannot be measured directly through aerial photography. Crown density percentage can be estimated by a visual comparison with crown density scales. The Crown Density classes used in photo interpretation are:Age ClassCrown Closure ClassCrown Closure CodeRegenerationPercent stocking cannot bedefined from interpretation0RegenerationImmatureMatureOver-Mature> 75%151 - 75%226 - 50%3Disturbed and notsufficiently restockedstands≤ 25%Crown closure classes for productive forest stands.Disturbed StandsA disturbance code is used to indicate land capable of producing crops but not now producing due to logging, fire, insect attack, wind, or other disturbances. Also, any remaining tree cover must have a crown density of ≤ 25%. Lands immediately following logging which do not have a new crop established are identified in this category. The following codes are used:DescriptionCodeLoggingXFireYInsectZWindWFloodingFDisturbance codes for productive forest stands and non-productive forest stands.Site ClassAll forest land is separated into one of four site classes to represent different degrees of potential productivity (mean annual increment).Site ClassMap SymbolSite-IndexClassMeanAnnualIncrementCLI ClassHighH> 16.7 m3.5 m³/ha3 (2*)GoodG13.7 - 16.7 m2.8 m³/ha4MediumM10.7 - 13.7 m1.4 m³/ha5PoorP< 10.70.7 m³/ha6Site classes and map symbols for productive stands.Non-Commercial Forest LandNon-commercial forest land is broken down into two categories, Forest Cover and Forest Site.Stocked Non-CommercialForest Cover TypeStocked Non-CommercialForest Site CodeCodeClassCodeClassCSConiferous ScrubWWetDSDeciduous ScrubDDryRRockNon-Commercial Forest land codes for Forest Cover and Forest Type.Non-ForestThis is land that is withdrawn from wood production or not capable of producing forest crops at a rotation age of 60 years.Non-Forest Attribute DomainCode*Code DescriptionDescription1SandBarren land, other than rock or soil, which does not support vegetation (≤10% woody vegetation); normally occurs between water bodies and vegetated areas.2Soil BarrenBarren land, other than rock or sand, which does not support tree vegetation; usually due to adverse climatic or soil factors (≤10% tree cover).3Rock BarrenBarren rock land without sufficient soil for tree establishment (≤10% tree cover).4AgricultureLand cleared for agriculture purposes.5Cleared LandLand where vegetation has been removed.6Right-Of-Way (Road)Land cleared for a road.7Right-Of-Way (Transmission Line)Land cleared for a Transmission Line.8ResidentialLand cleared for residential use, commercial purposes or cabin development areas.9Small IslandSmall Island (<0.5 ha) in waterbodies that do not need to be classified any further than Small Island.10BogWet areas of bog or marsh that may include patches of open water. Wetness may be seasonal or close to the surface to prohibiting tree growth.11Web BogWet areas of bog or marsh with a large number of open water patches.12Treed BogWet areas of bog or marsh with ≤10% tree cover.

"The hydro layer was digitized from the 2002 Virginia Base Mapping Program (VBMP) imagery. This hydro layer includes rivers, streams, ponds, lakes, and other bodies of water. Attribution of this data set is limited. It does not indicate the directional flow of water. The image below shows the hydro layer (refer to left side of illustration in supplemental METADATA file for Hydrography) and the hydro layer superimposed on top of aerial photography (refer to right side of the illustration in supplemental METADATA file for Hydrography). Also note that only visible water resources were digitized. (Water passing below underpasses was not digitized). This data set is the most spatially accurate available, but it does not conform to National Hydrography Dataset (NHD) specifications (due to limitations associated with attribution, water flow, segmentation, and connectivity). Intermittent streams are likely not contained in this file. Data was only collected in canals and ditches where water was visible (using aerial photography from spring 2002 . It should be noted that 2002 was an exceptionally dry spring in Virginia).Ancillary data sets contained on this CD or from other sources (including the Digital Elevation Model (DEM), contour lines, and even the Digital Raster Graphic [DRG] can be integrated with this file to support the delineation of flow direction. Spatial hydrologic features include:Streams and Rivers – Only streams with visible water will be collected. Streams will be single line up to 8 feet wide for 100 scale, or 30 feet wide for 200 and 400 scale. Double lines, representing left and right bank, will be collected where those dimensions are exceeded. Lakes and Ponds – Lakes and ponds will not be differentiated. Only lakes and ponds with visible water will be collected. The minimum dimension for collection is 100 feet in length or width. Canals and Ditches – Canals and ditches will not be differentiated. Only canals and ditches with visible water will be collected. Canals and ditches will be single line up to 8 feet wide for 100 scale, or 30 feet wide for 200 and 400 scale. Where those dimensions are exceeded, two lines will be placed, one to represent each bank. Swamps and Marshes – Swamps and marshes will not be differentiated. Only clearly identifiable swamps and marshes will be collected. The minimum dimension for collection is 1,000 feet in length or width. Shorelines – Shorelines for the Atlantic Ocean and Chesapeake Bay will be collected at the visible land/water interface. If the shoreline is bordered by tidal marsh, the shoreline will be collected at the land/marsh interface, not the marsh/water interface. Tidal marshes will be collected in Layer 4. For more information on this data refer to the supplemental metadata pdf found at: https://secure-archive.gis.vt.edu/gisdata/public/UnitedStates/Virginia/VCE_2002_metadata/METADATA.pdfThis data has been curated by the Virginia Cooperative Extension at Virginia Tech and Virginia Tech University Libraries. This data is meant for general use only. Virginia Tech’s University Library is acting as a steward for this data and any questions about its use should refer to our Terms of Use Page."