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Global One-Eighth Degree Urban Land Extent Projection and Base Year Grids by SSP Scenarios, v1 (
2000 – 2100)
- To provide global SSP-consistent spatial urban land projections and base year grids based on the Shared Socioeconomic Pathways (SSPs) data at a resolution of one-eighth degree (7.5 arc-minutes) for climate, socioeconomic, environmental, and other related research.
- The Global One-Eighth Degree Urban Land Extent Projection and Base Year Grids by SSP Scenarios, 2000-2100 consists of global SSP-consistent spatial urban land fraction data for the base year 2000 and projections at ten-year intervals for 2010-2100 at a resolution of one-eighth degree (7.5 arc-minutes). Spatial urban land projections are key inputs for the analysis of land use, energy use, and emissions, as well as for the assessment of climate change vulnerability, impacts and adaptation. This data set presents a set of global, spatially explicit urban land scenarios that are consistent with the Shared Socioeconomic Pathways (SSPs) to produce an empirically-grounded set of urban land spatial distributions over the 21st century. A data-science approach is used exploiting 15 diverse data sets, including a newly available 40-year global time series of fine-spatial-resolution remote sensing observations from the Landsat satellite series. The SSPs are developed to support future climate and global change research, the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), along with Special Reports.
- Recommended Citation(s)*:
Gao, J. and B. C. O'Neill. 2021. Global One-Eighth Degree Urban Land Extent Projection and Base Year Grids by SSP Scenarios, 2000-2100. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/nj0x-8y67. Accessed DAY MONTH YEAR.
ENW (EndNote & RefWorks)†
Gao, J. and B. C. O'Neill. 2020. Mapping Global Urban Land for the 21st Century with Data-driven Simulations and Shared Socioeconomic Pathways. Nature Communications 11:2302. https://doi.org/10.1038/s41467-020-15788-7.
ENW (EndNote & RefWorks)†
* When authors make use of data they should cite both the data set and the scientific publication, if available. Such a practice gives credit to data set producers and advances principles of transparency and reproducibility. Please visit the data citations page for details. Users who would like to choose to format the citation(s) for this dataset using a myriad of alternate styles can copy the DOI number and paste it into Crosscite's website.
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- Available Formats:
- raster, map