Data for "Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways"

McManamay, Ryan; Vernon, Chris; Thurber, Travis; Gao, Jing; O'Neill, Brian

doi:10.57931/2318472

Title: Data for "Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways"

Dataset
Other Related Research

Abstract

Datasets supporting findings and visualizations behind McManamay et al. (2024) Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways. Environmental Research Letters, DOI: 10.1088/1748-9326/ad2eec Using a spatial modeling experiment at high resolution (1-km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5. The numerical experiment, inputs and outputs are fully described in McManamay et al. (2024). The datasets summarize SELECT model simulations within urban areas and rural areas of the conterminous United States. For code to reproduce the results, please refer to https://github.com/IMMM-SFA/mcmanamay_etal_2024_erl Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions: Urban_Land_delta_UA_County.csv: Urban land area for original (default) population, updated population, and urban land delta (difference between the two) according to Shared Socioeconomic Pathways (SSPs) and year. Urban land is summarized for U.S. counties (FIPS code) and urban areas (GEOID) as unique areas within various counties. JO_Gao_pop_ufdelta.csv: Comparison of population differences and urban land differences between the origial (default) and updatedmore »« less

Authors:

;

; Thurber, Travis; Gao, Jing; O'Neill, Brian

Baylor University; Pacific Northwest National Laboratory
Pacific Northwest National Laboratory
University of Delaware

Publication Date:: Sun Mar 03 23:00:00 EST 2024

Research Org.:: MultiSector Dynamics - Living, Intuitive, Value-adding, Environment

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Subject:: Land; Population; Urban

OSTI Identifier:: 2318472

DOI:: https://doi.org/10.57931/2318472

Citation Formats


                    McManamay, Ryan, Vernon, Chris, Thurber, Travis, Gao, Jing, and O'Neill, Brian. Data for "Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways".  United States: N. p., 2024. 
        Web.  doi:10.57931/2318472.

Copy to clipboard


                    McManamay, Ryan, Vernon, Chris, Thurber, Travis, Gao, Jing, & O'Neill, Brian. Data for "Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways".  United States.  doi:https://doi.org/10.57931/2318472

Copy to clipboard


                    McManamay, Ryan, Vernon, Chris, Thurber, Travis, Gao, Jing, and O'Neill, Brian. 2024.  
"Data for "Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways"".  United States.  doi:https://doi.org/10.57931/2318472.  https://www.osti.gov/servlets/purl/2318472. Pub date:Sun Mar 03 23:00:00 EST 2024

Copy to clipboard


                    
@article{osti_2318472,

  title        = {Data for "Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways"},

  author       = {McManamay, Ryan and Vernon, Chris and Thurber, Travis and Gao, Jing and O'Neill, Brian},

  abstractNote = {Datasets supporting findings and visualizations behind McManamay et al. (2024) Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways. Environmental Research Letters, DOI: 10.1088/1748-9326/ad2eec Using a spatial modeling experiment at high resolution (1-km), this study compared how two alternative US population projections,  varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5.   The numerical experiment, inputs and outputs are fully described in McManamay et al. (2024). The datasets summarize SELECT model simulations within urban areas and rural areas of the conterminous United States.  For code to reproduce the results, please refer to https://github.com/IMMM-SFA/mcmanamay_etal_2024_erl Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions: Urban_Land_delta_UA_County.csv:   Urban land area for original (default) population, updated population, and urban land delta (difference between the two) according to Shared Socioeconomic Pathways (SSPs) and year.  Urban land is summarized for U.S. counties (FIPS code) and urban areas (GEOID) as unique areas within various counties. JO_Gao_pop_ufdelta.csv:  Comparison of population differences and urban land differences between the origial (default) and updated population projections.  City_Case_studies.csv:  Differences in urban land areas arising from different population projections summarized for selected cities (Atlanta, Los Angeles, Houston, and New York) and their surrounding rural areas UA_county_FID.zip:   Zipped folder of .tiff file depicting unique combination of urban areas and US counties used for summarizing urban land differences in urban and rural areas based on different population projections. ULD_clusters.zip:   Zipped folder of .csv files depicting normalized changes in urban land delta (difference in urban land arising from population projections) and the respective  Ward's hierarchical clusters, which group urban and rural areas based on similarities in temporal trends.   Urban_Percent_change_2100.zip:  Zipped folder of .csv files depicting percent changes in urban land area for year 2100 based on differences in the original (default) population and updated population.  Each file is for SSPs and urban or rural areas.  },

  doi          = {10.57931/2318472},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sun Mar 03 23:00:00 EST 2024},

  month        = {Sun Mar 03 23:00:00 EST 2024}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.57931/2318472

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

Divergent urban land trajectories under alternative population projections within the Shared Socioeconomic Pathways

Journal Article McManamay, Ryan A. ; Raad, Alen ; Vernon, Christopher R. ; ... - Environmental Research Letters

Population change is a main driver behind global environmental change, including urban land expansion. In future scenario modeling, assumptions regarding how populations will change locally, despite identical global constraints of Shared Socioeconomic Pathways (SSPs), can have dramatic effects on subsequent regional urbanization. Using a spatial modeling experiment at high resolution (1 km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5. The population projections included: (1) newer downscaled state-specificmore »« less
High-resolution (30-m) urban land cover projections for Los Angeles California Urban Area: 2010 to 2100 under SSP3 and SSP5 [Updated simulations based on population-driven urban intensity transitions]

Dataset McManamay, Ryan ; Vernon, Chris

These data (v3) are updated from previous versions (1 and 2) in that they include consider the effects of population on transitions in urban land intensity. This leads to more reasonable differences in urban land projections under variant SSPs. For the present dataset, both SSP3 and SSP5 are provided. These data represent simulations of future land use and land cover (LULCC) for Los Angeles urban area (U.S. Census Bureau defined area) as raster tiff images at a 30-m pixel resolution and at decadal time steps from 2010 to 2100. LULCC classes in this product follow the National Land Cover Datasetmore »« less
Extending Shared Socioeconomic Pathways to Future Water Supply In-frastructure Scenarios: A Case Study of San Antonio, TX

Dataset Okoye, Perpetua I. ; McManamay, Ryan A.

Datasets supporting findings and visualization behind Okoye and McManamay (2025) Extending Shared Socioeconomic Pathways to Future Water Supply Infrastructure Scenarios: A Case Study of San Antonio, TX. Environmental Research Communications, DOI: 10.57931/2563186 These datasets contains the results of a site selection analysis for municipal water supply planning across multiple Shared Socioeconomic Pathways (SSPs 1–5) and hard scenario classification of water systems in San Antonio, TX. It includes data at the resolution of individual surface water supply sources (COMIDs) and integrates a wide range of hydrologic, socioeconomic, infrastructural, and scenario-based planning variables. Please refer to the README file provided in Filesmore »« less
Global land use for 2015-2100 at 0.05° resolution under diverse socioeconomic and climate scenarios (in EN)

Dataset Chen, Min ; Vernon, Chris R ; Graham, Neal T ; ...

Global future land use (LU) is an important input for Earth system models for projecting Earth system dynamics and is critical for many modeling studies on future global change. Here we generated a new global gridded LU dataset using the Global Change Analysis Model (GCAM) and a land use spatial downscaling model, named Demeter, under the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios. Compared to existing similar datasets, the presented dataset has a higher spatial resolution (0.05°×0.05°) and spreads under a more comprehensive set of SSP-RCP scenarios (in total 15 scenarios), and considers uncertainties frommore »« less
High-resolution (30-m) urban land cover projections for Los Angeles California Urban Area: 2010 to 2100 under SSP5

Dataset McManamay, Ryan ; Vernon, Chris

These data represent simulations of future land use and land cover (LULCC) for Los Angeles urban area (U.S. Census Bureau defined area) as raster tiff images at a 30-m pixel resolution and at decadal time steps from 2010 to 2100. LULCC classes in this product follow the National Land Cover Dataset (NLCD) classification. NLCD 21-24 correspond to open developed, low developed, medium developed, and high developed urban land classes, respectively. Only urban land cover classes (NLCD class 21, 22, 23, and 24) are dynamic over time; however, all NLCD classes are included in the final product. Therefore, NLCD classes thatmore »« less

Similar Records