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- *Data embargoed until publication of related article, or up to no more than 1 year from data upload.*
Because of a lack of publicly-accessible, accurate, and complete geospatial data for pipelines, we created our own dataset for this analysis using the following procedure. For each county in NC, we manually digitized line segments representing the natural gas transmission pipeline network in Google Earth Pro (GEP) through the following process. First, we viewed the locations of the pipelines one county at a time using the high-resolution imagery on the National Pipeline Mapping System (NPMS). The NPMS shows satellite imagery and pipeline locations at a 1:24,000 spatial scale, but does not allow users to download imagery or pipeline location data. Using the “Add Path” tool in GEP and the NPMS imagery as references, we drew every pipeline segment in each county. We used visible rights-of-way and landmarks in the satellite imagery on GEP and the NPMS as registration points to identify the locations of the pipelines. Then, we exported the produced pipeline locations as KML files. Finally, we aggregated individual line segments into a single shapefile of natural gas transmission pipelines into ArcGIS Pro file format.
After creating a shapefile of natural gas transmission pipelines for NC, we downloaded the social vulnerability index (SVI) for 7,111 NC census block groups in table format from the Harvard Open Environments Dataverse (Bryan, 2022). The SVI is a percentile ranking that represents community ability to recover from adverse events, considering 15 variables grouped into four themes: socioeconomic status, household characteristics, racial and ethnic minority status, and housing type and transportation. SVI ranges from 0 (least vulnerable) to 1 (most vulnerable) (Bryan, 2022).
Finally, we downloaded race and ethnicity data for each block group in NC from the United States Census Bureau. Race and ethnicity data include geographic identity codes (GEOIDs) as well as the number of those identifying as White, Black or African American, American Indian or Alaska Native, Asian, Native Hawai’ian or other Pacific Islander, two or more races, and some other race for each block group in NC. These data are based on self-reported information acquired via the decennial Census. We also downloaded TIGER/Line shapefiles that contain county and census block group boundaries as well as GEOIDs.
We joined social vulnerability data to spatial pipeline data using ArcGIS Pro (“ArcGIS Pro,” 2023). First, we used the “Spatial Join” tool to combine the census block group TIGER/Line shapefile with the pipeline shapefile originally created in Google Earth Pro. Next, we computed pipeline density (ρNG) for each block group as the length of pipeline (km) per unit of land area (km2). Then, we used the “Join by Attributes” tool to match social vulnerability and race data with corresponding block groups in the pipeline shapefile using each block group’s GEOID. The output of these steps was a table that included collated information for each block group in NC (Table 1). Race or social vulnerability data were missing for 467 block groups, comprising 7% of the total number of block groups in NC and 18,139 km2 (15%) of the area of NC. Block groups without data were omitted from further analysis. ... [Read More]
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- Total Size
- 0 files (0 Bytes)
- Data Citation
- Tschoepe, S., Emanuel, R., Moreau, G., & Cada, P. (2025).
Data from: Fueling inequity: Geospatial analyses reveal racial patterns in vulnerability to natural gas pipeline impacts in North Carolina. Duke Research Data Repository. https://doi.org/10.7924/r4bz6fq97
- Location
- North Carolina, North Carolina, United States
- Title
- Data from: Fueling inequity: Geospatial analyses reveal racial patterns in vulnerability to natural gas pipeline impacts in North Carolina
There are no publicly available items in this Dataset.