Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways

We developed and presented a set of comparable spatially explicit global gridded gross domestic product (GDP) 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 over 800 provincial gross regional product (GRP, in 2005 PPP USD) across the globe in 2005 and to downscaled to a spatial resolution of 30 arc-seconds (~1 km at equator). National and supranational GDP growth rate projections in 2030-2100 under five SSPs were then downscaled to 1-km grids based on the LitPop approach, which used NPP-VIIRS product as fixed NTL image in 2015 and the population projections of 0.125 arc-degreee (Jones and O'Neill, 2016), which are downscaled to 1-km based on LandScan population distribution pattern in 2015. We then upscaled this gridded GDP dataset to 0.25 arc-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 gridded GDP 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. For more details, please refer to the corresponding article: Global gridded GDP data set consistent with the shared socioeconomic pathways by Wang and Sun (2022).