Spatially explicit global gross cell product (GCP) data set consistent with the Shared Socioeconomic Pathways
In this project, we presented a set of comparable spatially explicit global gross cell product (GCP) for both historical period (2005 as representative) and for future projections from 2030 to 2100 at a ten-year interval for all five SSPs. The DMSP-OLS nighttime light (NTL) images and the LandScan G...
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ftdatacite:10.5281/zenodo.5004249 2023-05-15T13:58:51+02:00 Spatially explicit global gross cell product (GCP) data set consistent with the Shared Socioeconomic Pathways Wang, Tingting Sun, Fubao 2020 https://dx.doi.org/10.5281/zenodo.5004249 https://zenodo.org/record/5004249 unknown Zenodo https://dx.doi.org/10.5281/zenodo.4350026 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY GDP SSP downscaling dataset Dataset 2020 ftdatacite https://doi.org/10.5281/zenodo.5004249 https://doi.org/10.5281/zenodo.4350026 2021-11-05T12:55:41Z In this project, we presented a set of comparable spatially explicit global gross cell product (GCP) for both historical period (2005 as representative) and for future projections from 2030 to 2100 at a ten-year interval for all five SSPs. The DMSP-OLS nighttime light (NTL) images and the LandScan Global Population database were used to generate LitPop map, which reduces the limitations of saturation problem of using NTL images alone or the assumption of even GDP per capita within an administrative boundary of gridded data set in GDP disaggregation. We used the LitPop maps to disaggregate national GDP and gross regional product (GRP, in 2005 PPP USD) across the globe in 2005, and to downscale national and supranational GDP projections from five SSPs to spatial resolutions of 30 arc-seconds (~1 km at equator). We then upscaled this GCP data set to 0.25 degree and provided here. There are 41 tif files (2005 and 2030 - 2100 at a ten-year interval for five SSPs) for each spatial resolution. The GCP are distributed over land with value of zero filled in the Antarctica, oceans and some desert or wilderness areas (non-illuminated and depopulated zones). The spatial extents are 60S - 90N and 180E - 180W in standard WGS84 coordinate system. These spatial explicit GCP data set offers the necessity and availability of using GCP projections of high resolution, especially in exposure, vulnerability, and resilience analysis for scenario-based climate change research for all five SSPs. : {"references": ["Geiger, T.: Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850\u20132005) harmonized with future projections according to the Shared Socio-economic Pathways (2006\u20132100), Earth System Science Data, 10, 847\u2013856, 2018.", "Dellink, R., Chateau, J., Lanzi, E., and Magn\u00e9, B.: Long-term economic growth projections in the Shared Socioeconomic Pathways, Global Environmental Change, 42. 200-214, 2015.", "Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O'neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., and Fricko, O.: The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview, Global Environmental Change, 42, 153-168, 2017."]} Dataset Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology) Calvin ENVELOPE(165.100,165.100,-71.283,-71.283) Chateau ENVELOPE(-55.898,-55.898,51.983,51.983) Geiger ENVELOPE(-62.900,-62.900,-64.300,-64.300) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
GDP SSP downscaling |
spellingShingle |
GDP SSP downscaling Wang, Tingting Sun, Fubao Spatially explicit global gross cell product (GCP) data set consistent with the Shared Socioeconomic Pathways |
topic_facet |
GDP SSP downscaling |
description |
In this project, we presented a set of comparable spatially explicit global gross cell product (GCP) for both historical period (2005 as representative) and for future projections from 2030 to 2100 at a ten-year interval for all five SSPs. The DMSP-OLS nighttime light (NTL) images and the LandScan Global Population database were used to generate LitPop map, which reduces the limitations of saturation problem of using NTL images alone or the assumption of even GDP per capita within an administrative boundary of gridded data set in GDP disaggregation. We used the LitPop maps to disaggregate national GDP and gross regional product (GRP, in 2005 PPP USD) across the globe in 2005, and to downscale national and supranational GDP projections from five SSPs to spatial resolutions of 30 arc-seconds (~1 km at equator). We then upscaled this GCP data set to 0.25 degree and provided here. There are 41 tif files (2005 and 2030 - 2100 at a ten-year interval for five SSPs) for each spatial resolution. The GCP are distributed over land with value of zero filled in the Antarctica, oceans and some desert or wilderness areas (non-illuminated and depopulated zones). The spatial extents are 60S - 90N and 180E - 180W in standard WGS84 coordinate system. These spatial explicit GCP data set offers the necessity and availability of using GCP projections of high resolution, especially in exposure, vulnerability, and resilience analysis for scenario-based climate change research for all five SSPs. : {"references": ["Geiger, T.: Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850\u20132005) harmonized with future projections according to the Shared Socio-economic Pathways (2006\u20132100), Earth System Science Data, 10, 847\u2013856, 2018.", "Dellink, R., Chateau, J., Lanzi, E., and Magn\u00e9, B.: Long-term economic growth projections in the Shared Socioeconomic Pathways, Global Environmental Change, 42. 200-214, 2015.", "Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O'neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., and Fricko, O.: The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview, Global Environmental Change, 42, 153-168, 2017."]} |
format |
Dataset |
author |
Wang, Tingting Sun, Fubao |
author_facet |
Wang, Tingting Sun, Fubao |
author_sort |
Wang, Tingting |
title |
Spatially explicit global gross cell product (GCP) data set consistent with the Shared Socioeconomic Pathways |
title_short |
Spatially explicit global gross cell product (GCP) data set consistent with the Shared Socioeconomic Pathways |
title_full |
Spatially explicit global gross cell product (GCP) data set consistent with the Shared Socioeconomic Pathways |
title_fullStr |
Spatially explicit global gross cell product (GCP) data set consistent with the Shared Socioeconomic Pathways |
title_full_unstemmed |
Spatially explicit global gross cell product (GCP) data set consistent with the Shared Socioeconomic Pathways |
title_sort |
spatially explicit global gross cell product (gcp) data set consistent with the shared socioeconomic pathways |
publisher |
Zenodo |
publishDate |
2020 |
url |
https://dx.doi.org/10.5281/zenodo.5004249 https://zenodo.org/record/5004249 |
long_lat |
ENVELOPE(165.100,165.100,-71.283,-71.283) ENVELOPE(-55.898,-55.898,51.983,51.983) ENVELOPE(-62.900,-62.900,-64.300,-64.300) |
geographic |
Calvin Chateau Geiger |
geographic_facet |
Calvin Chateau Geiger |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://dx.doi.org/10.5281/zenodo.4350026 |
op_rights |
Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5281/zenodo.5004249 https://doi.org/10.5281/zenodo.4350026 |
_version_ |
1766267221109112832 |