Taylor H. Rowley
Eammon S. Jensen
Silvia Terziotti
Ana Maria Garcia
Jonathan W. Musser
20220712
Lidar-Derived Ditches in Eastern North Carolina with Transportation attributes, 2014-2015
raster digital data
https://doi.org/10.5066/P9IGSRCV
Jonathan W. Musser
Taylor H. Rowley
Eammon S. Jensen
Silvia Terziotti
Ana Maria Garcia
20220711
Indicators of Hydrologic Alteration in North Carolina Catchments: Small Ponds and Artificial Drainage
digital data
https://doi.org/10.5066/P9IGSRCV
Artificial drainage has major ecosystem impacts through the development of extensive ditch networks that reduce storage and induce large-scale vegetation changes. This has been a widespread practice of water table management for agriculture in Eastern North Carolina. However, these features are challenging to identify, and (because of their structure) have been determined by non-natural factors. A dataset of open ditches was processed by calculating terrain openness (also called positive openness): a value based on a line-of-sight approach to measure the surrounding eight zenith angles as viewed above the landscape surface. The result from calculating openness with high resolution digital elevation models (DEMs or Lidar) was then refined by masking natural water ways (stream valleys) and channels that are associated with transportation and urban areas. The resulting raster dataset presented here represents areas without ditches (cell value of 0), a ditch not along a transportation corridor (1), the transportation corridor (100), and ditches along a transportation corridor (101).
This dataset was created to help prioritize restoration activities throughout the state of North Carolina.
2014
2015
ground condition
None planned
-79.7506
-75.4281
36.5890
33.8051
ISO 19115 Topic Category
geoscientificInformation
USGS Thesaurus
Lidar
Spatial analysis
Geospatial analysis
Hydrology
Geomorphology
Water cycle
Other keywords
Ditches
Artificial drainage
Canals
Agriculture
USGS Metadata Identifier
USGS:6172b873d34ea36449a88182
Common geographic areas
North Carolina
Beaufort
Bertie
Bladen
Brunswick
Camden
Carteret
Chowan
Columbus
Craven
Cumberland
Currituck
Dare
Duplin
Edgecombe
Franklin
Gates
Greene
Halifax
Harnett
Hertford
Hoke
Hyde
Johnston
Jones
Lenoir
Martin
Montgomery
Moore
Nash
New Hanover
Northampton
Onslow
Pamlico
Pasquotank
Pender
Perquimans
Pitt
Richmond
Robeson
Sampson
Scotland
Tyrrell
Wake
Washington
Wayne
Wilson
None. Please see 'Distribution Info' for details.
Although these data have been used by the U.S. Geological Survey, U.S. Department of the Interior, no warranty expressed or implied is made by the U.S. Geological Survey as to the accuracy of the data. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of this data, software, or related materials. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. This dataset may be redistributed if it is not edited and is properly referenced. Although USGS intends to make this server available 24 hours a day, seven days a week, timely delivery of data and products from this server through the Internet is not guaranteed.
Silvia Terziotti
U.S. Geological Survey, CORE SCIENCE SYSTEMS
National Map Liaison
mailing address
3916 Sunset Ridge Rd
Raleigh
NC
27607
US
919-571-4090
919-571-4041
seterzio@usgs.gov
North Carolina Department of Environmental Quality, Department of Mitigation Services, National Hydrography Dataset (NHD) Plus High Resolution, and the 2016 National Land Cover Dataset (NLCD), and Office of Coastal Management Partners for the North Carolina Statewide Lidar DEM 2014, Phase 2.
A computer with Windows 10 used a combination of ArcGIS 10.4, 10.7, and ArcGIS Pro 2.6 to produce this dataset. The file name is NCDitchesRaster.tif and is 350 MB.
No formal attribute accuracy tests were conducted.
Several limitations to the dataset are included in a README file in the data release. These limitations include, firstly, that wide (>35 ft.) canal and ditch features were likely excluded from the final dataset because the positive openness method does not capture flat areas. Additionally, stream valleys and lakes and ponds were used to mask data because those areas included large amounts of noise. Masking sometimes left cells that are marked as a canal or ditch, but are in reality an edge of a lake or pond feature. Additionally, inconsistencies with how the original lidar files were processed has led to some areas having more noise within forested/wetland areas than other areas. For more information on the data limitations, please see the attached README file.
Dataset is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
A formal accuracy assessment of the horizontal positional information in the dataset has not been conducted.
A formal accuracy assessment of the vertical positional information in the dataset has not been conducted.
Žiga Kokalj
Klemen Zakšek
Krištof Oštir
20150102
Application of sky-view factor for the visualisation of historic landscape features in lidar-derived relief models
publication
Antiquity
vol. 85, issue 327
n/a
Cambridge University Press (CUP)
pg. 263-273
https://doi.org/10.1017/S0003598X00067594
Digital
20140101
20151231
publication date
Positive Openness (RVT Toolbox)
The use of the RVT toolbox to calculate positive openness on the lidar-derived DEMs.
North Carolina Department of Transportation
20200901
Road Characteristic Arcs and Rail Division Data
vector digital data
https://connect.ncdot.gov/resources/gis/pages/gis-data-layers.aspx
Digital
20200901
publication date
NCDOT 2020
The transportation network, including roads and railroads, were converted to a raster and used as a mask on the ditches dataset.
U.S. Geological Survey
20191017
National Hydrography Dataset Plus High Resolution
vector digital data
https://pubs.er.usgs.gov/publication/ofr20191096
Digital
20191017
publication date
NHD 2019
This dataset was used to remove ditch features that overlapped with any waterbody features identified from the NHDPlus HR data.
Multi-Resolution Land Characteristics Consortium
20190901
National Land Cover Dataset, 2016
tabular digital data
https://www.mrlc.gov/data/nlcd-2016-land-cover-conus
Digital
20160101
publication date
NLCD 2016
Class 11 was used to mask out waterbody features from the ditches dataset. Developed classes were used to create the urban layer mask to remove urban areas from the ditches dataset.
Office for Coastal Management Partners
20160815
North Carolina Statewide Lidar DEM 2014 Phase 2
tabular digital data
https://www.fisheries.noaa.gov/inport/item/49412
Digital
20140130
20150313
publication date
OCMP, 2016
The DEMs were used to calculate positive openness for each county in the study area.
U.S. Census Bureau
20110101
U.S. Census Bureau Population Density, 2010
vector digital data
https://www.census.gov/data/datasets/time-series/demo/popest/2010s-counties-total.html
Digital
20100101
20101231
publication date
USCB, 2011
Population bulk density/1000 square mile blocks were used in tandem with 2016 NLCD developed classes to create an urban mask to remove ditches within urban areas.
Žiga Kokalj, PhD
Klemen Zakšek, PhD
Peter Pehani,
Klemen Čotar
Maja Somrak
20130902
Relief Visualization Toolbox (RVT)
toolbox
https://iaps.zrc-sazu.si/en/rvt#v
Toolbox
20130902
publication date
Relief Visualization Toolbox
Digital Toolbox for calculation openness
Acquire North Carolina QL2 Lidar at 5 ft resolution by county (OCMP, 2016). Run positive openness on 5 ft DEMs by county using the Relief Visualization Toolbox (https://iaps.zrc-sazu.si/en/rvt#v, Kokalji et al., 2011; Zakšek et al., 2011). The number of search directions was set to 8 with a search radius of 12 pixels, and medium noise removal. Counties within the study area include: Beaufort, Bertie, Bladen, Brunswick, Camden, Carteret, Chowan, Columbus, Craven, Cumberland, Currituck, Dare, Duplin, Edgecombe, Franklin, Gates, Greene, Halifax, Harnett, Hertford, Hoke, Hyde, Johnston, Jones, Lenoir, Martin, Montgomery, Moore, Nash, New Hanover, Northampton, Onslow, Pamlico, Pasquotank, Pender, Perquimans, Pitt, Richmond, Robeson, Sampson, Scotland, Tyrrell, Wake, Washington, Wayne, and Wilson.
20200731
Acquire North Carolina QL2 Lidar at 10 ft. resolution by county and run a low-pass filter using the ArcGIS toolbox "Filter" (OCMP, 2016). After the filter was applied, the ArcGIS toolbox "Slope" was used to calculate percent rise for the DEM. A threshold of 6% was determined through visual inspection of several locations across the study area. All areas less than 6% were preserved and the dataset was used as a mask to target and remove stream valley areas from the positive openness dataset calculated in the previous step. The tool "Extract" was used to mask the areas and create the new positive openness dataset. This step was repeated for all counties.
20200831
Classify the new positive openness datasets using standard deviation. Take the upper limit of the second lowest standard deviation classification as the threshold value. Use the "Con" toolbox in ArcGIS to create a new dataset where values less than or equal to the threshold are set to 1 and values greater than the threshold are set to No Data.
20200831
On the new binary dataset, use the toolbox "Region Group" to group cells using 8 neighbors. Once complete, use the "Con" toolbox to rid of groups less than or equal to 4 cells. This step helps to remove additional noise. Repeat this step for all counties. Once all counties are complete, merge them into a single raster. This is now the dataset of ditches in North Carolina that will be further refined by the subsequent steps.
20200915
Urban Mask Creation - Create a mask for urban areas to be removed from the ditches dataset. Use a combination of the US census population bulk density/1000 square mile and the 2016 National Land Cover Dataset developed areas (USCB, 2011; NLCD 2016). Aggregate both rasters to 10 ft. resolution and merge to create a mask.
20201031
Transportation Mask Creation - The transportation network was downloaded from the North Carolina Department of Transportation as a vector dataset (NCDOT, 2020). Roads were clipped to the study area and classified as primary or secondary based on the attribute, "FuncClass". Primary roads were classified using FuncClass 1-4, and secondary roads were classifies using FuncClass 5-7. Primary roads were buffered by 75 ft. and secondary roads were buffered by 50 ft. After buffered, both were converted to a raster at 5 ft. resolution where transportation was given a value of 1, and no transportation was given a value of 0. Additionally, railroads were added to the transportation mask by downloading the layer from the North Carolina Department of Transportation (NCDOT, 2020). Railroads were clipped to the study area and were buffered by 50 ft. The polygons were converted to a raster at 5 ft. resolution and merged with the transportation layer. This mask is used to identify ditches within the transportation buffer and identify them as such.
20201031
National Hydrography Dataset (NHD) comparison - NHD canal/ditch features were obtained from the NHDPlus High Resolution dataset and extracted within the study area from the NHD flowline and NHD area as FType = 336 (NHD, 2019). Once extracted the canal/ditch features were converted to a raster at 5 ft. resolution. The flow line and area rasters were then merged to create a continuous dataset for the study area.
20201031
Create a Lakes and Ponds Mask - Use the NHDPlus High Resolution waterbodies and the 2016 National Land Cover Dataset class 11 to create a mask of waterbodies (NLCD, 2016; NHD, 2019). This mask is used to reduce noise in the ditches raster by removing any ditch features that may have been identified within a waterbody.
20201115
All raster datasets were aggregated to 10 ft. resolution from 5 ft. using the "Aggregate" toolbox in ArcGIS. The processing for the ditches layer was originally done at 5ft. resolution to pick up many more features that would have been missed at 10 ft., but keeping the dataset a 5 ft. decreases the usability of the data, thus it was aggregated.
20201215
Use the lake/pond mask and the urban mask to remove any ditch features within these areas to reduce noise within the final ditch raster. Once removed, the final ditch layer and the transportation mask were combined using raster addition to create a final raster with 4 classes; 0 represents cells with no ditches, 1 represents cells that are ditches not along a road, 100 represents cells that are the transportation buffer, and 101 represents cells that are ditches within the transportation buffer.
20201215
Raster
Grid Cell
99510
126970
1
NAD 1983 StatePlane North Carolina FIPS 3200 Feet
34.33333333333334
36.16666666666666
-79.0
33.75
2000000.002616666
0.0
coordinate pair
0.000000027498425758665238
0.000000027498425758665238
meters
D North American 1983
GRS 1980
6378137.0
298.257222101
NCDitchesRaster.tif
A raster dataset (Tagged Image Format) illustrating ditch locations within a transportation buffer, not within a transportation buffer, and the transportation buffer.
Producer Defined
Value
A numeric value indicating which class a ditch is within.
Producer Defined
NoData
Not part of the study area
Producer defined
0
Not a ditch
Producer defined
1
Ditch, not along transportation
Producer defined
100
Transportation buffer, not a ditch
Producer defined
101
Ditch within the transportation buffer
Producer defined
U.S. Geological Survey
GS ScienceBase
mailing address
Denver Federal Center, Building 810, Mail Stop 302
Denver
CO
80225
United States
1-888-275-8747
sciencebase@usgs.gov
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
Digital Data
https://doi.org/10.5066/P9IGSRCV
None
20220712
Jonathan W Musser
U.S. Geological Survey, Southeast Region
Hydrologist
mailing address
1770 Corporate Drive Suite 500
Norcross
GA
30093
US
678-924-6675
678-924-6710
jwmusser@usgs.gov
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998