Figure/Table detail

Multi-scenario land use prediction and layout optimization in Nanjing Metropolitan Area based on the PLUS model
CAO Ji, CAO Weidong, CAO Yuhong, WANG Xuewei, ZHANG Yizhen, MA Jinji
Journal of Geographical Sciences, 2024, 34(7): 1415-1436.   DOI: 10.1007/s11442-024-2254-7

Data
classification
Data name Data type Data accuracy Data sources
Natural
environment
data
Land use data Raster 30 m × 30 m Earth System Science Data
(https://doi.org/10.5281/zenodo.5816591)
Soil type Raster 1 km × 1 km Resource and Environmental Data Sharing Center, Chinese Academy of Sciences
(https://www.resdc.cn/)
Average annual temperature Raster 1 km × 1 km
Annual precipitation Raster 1 km × 1 km
DEM Raster 90 m × 90 m
NPP Raster 0.5 km × 0.5 km MODIS images (http://www.noaa.gov/)
NDVI Raster 1 km × 1 km MYDND1M China 500 M (http://www.noaa.gov/)
PM2.5 Raster 1 km × 1 km https://doi.org/10.5281/zenodo.6372847
Socio-
economic data
Nighttime lighting data Raster 1 km × 1 km NOAA (https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html)
GDP Raster 1 km × 1 km Resource and Environmental Data Sharing Center, Chinese Academy of Sciences (https://www.resdc.cn/)
Industrial density Raster 1 km × 1 km
Nighttime light Raster 1 km × 1 km NOAA(https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html)
Population density (Pop) Raster 1 km × 1 km Worldpop
(https://www.worldpop.org/)
Distance to main roads Vector OpenStreetMap
(https://www.openstreetmap.org)
Distance to railways Vector
Distance to administrative
centers
Vector
Table 1 Data sources
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