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1. Historical, county-level road network statistics for the conterminous United States (1900 - 2015)

   https://doi.org/10.6084/m9.figshare.19593460.v1  

   Uhl, Johannes H. ; Burghardt, Keith ( January 2022 , figshare)

   This CSV file contains geometric and topological road network statistics for the majority of counties in the conterminous U.S.

   The underlying road network data is the USGS-NTD v2019.

   These road network data from 2019 were clipped to historical settlement extents obtained from the HISDAC-US dataset 

   Road network statistics are multi-temporal, calculated in time slices for the years: 1810-1900, 1880-1920, 1900-1940, 1920-1960, 1940-1980, 1960-2000, 1980-2015

   The historical built-up areas used to model the historical road networks are derived from historical settlement layers from the  Historical settlement data compilation for the U.S. (HISDAC-US, Leyk & Uhl 2018). See Burghardt et al. (2022) for details on the modelling strategy.

   Spatial coverage: all U.S. counties that are covered by the HISDAC-US historical settlement layers. This datasets includes around 2,700 U.S. counties. In the remaining counties, construction year coverage in the underlying ZTRAX data (Zillow Transaction and Assessment Dataset) is low. See Uhl et al. (2021) for details.

   All data created by Johannes H. Uhl, University of Colorado Boulder, USA.

   Code available at https://github.com/johannesuhl/USRoadNetworkEvolution.

   References:

   Burghardt, K., Uhl, J., Lerman, K.,  & Leyk, S. (2022). Road  Network Evolution in the Urban and Rural  United States Since 1900.  Computers, Environment and Urban Systems.

   Leyk, S., & Uhl, J. H. (2018). HISDAC-US, historical settlement  data  compilation for the conterminous United States over 200 years. Scientific data, 5(1), 1-14. DOI:  https://doi.org/10.1038/sdata.2018.175 

   Uhl, J. H., Leyk, S., McShane, C. M., Braswell, A. E., Connor, D.  S.,  & Balk, D. (2021). Fine-grained, spatiotemporal datasets  measuring  200 years of land development in the United States. Earth system science data, 13(1), 119-153. DOI:  https://doi.org/10.5194/essd-13-119-2021 

    

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2. Historical, generalized built-up areas in U.S. core-based statistical areas 1900 - 2015

   https://doi.org/10.6084/m9.figshare.19593409.v2  

   Uhl, Johannes H. ; Burghardt, Keith ( January 2022 , figshare)

   An ESRI Shapfile containing spatially generalized built-up areas for each decade from 1900 to 2010, and for 2015, for each core-based statistical area (CBSA, i.e., metropolitan and micropolitan statistical area) in the conterminous United States. These areas are derived from historical settlement layers from the Historical settlement data compilation for the U.S. (HISDAC-US, Leyk & Uhl 2018). See Burghardt et al. (2022) for details on the data processing.

   
   

   Additionally, there is a CSV file (HISDAC-US_patch_statistics.csv) containing the counts of built-up property records (BUPR), and -locations (BUPL), as well as total building indoor area (BUI) and built-up area (BUA) per CBSA, year, and patch, extraced from the HISDAC-US data (Uhl & Leyk 2018, Uhl et al. 2021). This CSV can be joined to the shapefile (column uid2) by concatenating the columns msaid_year_Id.

   
   

   Spatial coverage: all CBSAs that are covered by the HISDAC-US historical settlement layers.

   This dataset includes around 2,700 U.S. counties. In the remaining counties, construction year coverage in the underlying ZTRAX data (Zillow Transaction and Assessment Dataset) is low. See Uhl et al. (2021) for details.

   All data created by Johannes H. Uhl, University of Colorado Boulder, USA.

   Code available at https://github.com/johannesuhl/USRoadNetworkEvolution.

   References:

   Burghardt, K., Uhl, J., Lerman, K.,  & Leyk, S. (2022). Road Network Evolution in the Urban and Rural  United States Since 1900. Computers, Environment and Urban Systems.

   Leyk, S., & Uhl, J. H. (2018). HISDAC-US, historical settlement data  compilation for the conterminous United States over 200 years. Scientific data, 5(1), 1-14. DOI:  https://doi.org/10.1038/sdata.2018.175 

   Uhl, J. H., Leyk, S., McShane, C. M., Braswell, A. E., Connor, D. S.,  & Balk, D. (2021). Fine-grained, spatiotemporal datasets measuring  200 years of land development in the United States. Earth system science data, 13(1), 119-153. DOI:  https://doi.org/10.5194/essd-13-119-2021 

    

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3. Historical road network statistics for core-based statistical areas in the U.S. (1900 - 2010)

   https://doi.org/10.6084/m9.figshare.19584088.v1  

   Burghardt, Keith ; Uhl, Johannes H. ( January 2022 , figshare)

   
   

   Tabulated statistics of road networks at the level of intersections and for built-up areas for each decade from 1900 to 2010, and for 2015, for each core-based statistical area (CBSA, i.e., metropolitan and micropolitan statistical area) in the conterminous United States. These areas are derived from historical road networks developed by Johannes Uhl. See Burghardt et al. (2022) for details on the data processing. 

   
   

   Spatial coverage: all CBSAs that are covered by the HISDAC-US historical settlement layers.

   This dataset includes around 2,700 U.S. counties. In the remaining counties, construction year coverage in the underlying ZTRAX data (Zillow Transaction and Assessment Dataset) is low. See Uhl et al. (2021) for details.

   All data created by Keith A. Burghardt, USC Information Sciences Institute, USA

   
   

   Codebook: these CBSA statistics are stratified by degree of aggregation.

   - CBSA_stats_diffFrom1950: Change in CBSA-aggregated patch statistics between 1950 and 2015

   - CBSA_stats_by_decade: CBSA-aggregated patch statistics for each decade from 1900-2010 plus 2015

   - CBSA_stats_by_decade: CBSA-aggregated cumulative patch statistics for each decade from 1900-2010 plus 2015. All roads created up to a given decade are used for calculating statistics.

   - Patch_stats_by_decade: Individual patch statistics for each decade from 1900-2010 plus 2015

   - Patch_stats_by_decade: Individual cumulative patch statistics for each decade from 1900-2010 plus 2015. All roads created up to a given decade are used for calculating statistics.

   
   

   The statistics are the following:

   • msaid: CBSA code
   • id: (if patch statistics) arbitrary int unique to each patch within the CBSA that year
   • year: year of statistics
   • pop: population within all CBSA counties
   • patch_bupr: built up property records (BUPR) within a patch (or sum of patches within CBSA)
   • patch_bupl: built up property l (BUPL) within a patch (or sum of patches within CBSA)
   • patch_bua: built up area (BUA) within a patch (or sum of patches within CBSA)
   • all_bupr: Same as above but for all data in 2015 regardless of whether properties were in patches
   • all_bupl: Same as above but for all data in 2015 regardless of whether properties were in patches
   • all_bua: Same as above but for all data in 2015 regardless of whether properties were in patches
   • num_nodes: number of nodes (intersections)
   • num_edges: number of edges (roads between intersections)
   • distance: total road length in km
   • k_mean: mean number of undirected roads per intersection
   • k1: fraction of nodes with degree 1
   • k4plus: fraction of nodes with degree 4+
   • bearing: histogram of different bearings between intersections
   • entropy: entropy of bearing histogram
   • mean_local_gridness: Griddedness used in text
   • mean_local_gridness_max: Same as griddedness used in text but assumes we can have up to 3 quadrilaterals for degree 3 (maximum possible, although intersections will not necessarily create right angles)

   
   

   Code available at https://github.com/johannesuhl/USRoadNetworkEvolution.

   
   

   References:

   Burghardt, K., Uhl, J., Lerman, K.,  & Leyk, S. (2022). Road Network Evolution in the Urban and Rural  United States Since 1900. Computers, Environment and Urban Systems.

    

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4. Focal accuracy estimates and landscape metrics for built-up areas from the GHS-BUILT R2018A in Massachusetts, USA.

   https://doi.org/10.6084/m9.figshare.19785877.v1  

   Uhl, Johannes H. ; Leyk, Stefan ( January 2022 , figshare)

   These files are supplementary data for this publication:

   Uhl JH & Leyk S (2022). "Assessing the relationship between morphology and mapping accuracy of built-up areas derived from global human settlement data (https://doi.org/10.1080/15481603.2022.2131192).

   Each geopackage (GPKG) file contains a set of point locations (in EPSG:3857) attributed with focal accuracy metrics of the GHS-BUILT-R2018A epochs 1975 and 2014, calculated within different levels of spatial support (i.e., focal window size) and for different analytical units (i.e., 30m grid cells, and 3x3 grid cell blocks). Moreover, each location is attributed with focal landscape metrics of built-up areas calculated in the same focal windows using the software Fragstats. These landscape metrics are calculated based on both, GHS built-up areas and reference built-up areas. Reference built-up areas were derived from the Multi-temporal building footprint database for 33 U.S. counties (MTBF-33). These datasets can be used for spatially explicit predictive modeling of the GHS-BUILT R2018A data accuracy using landscape metrics as predictor variables.

   File nomenclature:

   lsm_ref_accuracy_sample_2014_1000.gpkg : landscape metrics calculated from the reference built-up areas, for the epoch 2014, using a quadratic focal window of 1,000m x 1,000m.

   lsm_ghs_accuracy_sample_1975_10000.gpkg : landscape metrics calculated from the ghs built-up areas, for the epoch 1975, using a quadratic focal window of 10,000m x 10,000m.

   
   

   Data processing: Johannes H. Uhl, University of Colorado Boulder (USA), 2020-2022.

   
   

    

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5. Fine-grained, spatiotemporal datasets measuring 200 years of land development in the United States

   https://doi.org/10.5194/essd-13-119-2021  

   Uhl, Johannes H. ; Leyk, Stefan ; McShane, Caitlin M. ; Braswell, Anna E. ; Connor, Dylan S. ; Balk, Deborah ( January 2021 , Earth System Science Data)

   Abstract. The collection, processing, and analysis of remote sensing data since the early 1970s has rapidly improved our understanding of change on the Earth's surface. While satellite-based Earth observation has proven to be of vast scientific value, these data are typically confined to recent decades of observation and often lack important thematic detail. Here, we advance in this arena by constructing new spatially explicit settlement data for the United States that extend back to the early 19th century and are consistently enumerated at fine spatial and temporal granularity (i.e. 250 m spatial and 5-year temporal resolution). We create these time series using a large, novel building-stock database to extract and map retrospective, fine-grained spatial distributions of built-up properties in the conterminous United States from 1810 to 2015. From our data extraction, we analyse and publish a series of gridded geospatial datasets that enable novel retrospective historical analysis of the built environment at an unprecedented spatial and temporal resolution. The datasets are part of the Historical Settlement Data Compilation for the United States (https://dataverse.harvard.edu/dataverse/hisdacus, last access: 25 January 2021) and are available at https://doi.org/10.7910/DVN/YSWMDR (Uhl and Leyk, 2020a), https://doi.org/10.7910/DVN/SJ213V (Uhl and Leyk, 2020b), and https://doi.org/10.7910/DVN/J6CYUJ (Uhl and Leyk, 2020c). 

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