Table 1 Basic and driving factor data of research.
Type | Name | Data time | Spatial resolution | Data source | Data processing and use |
|---|---|---|---|---|---|
Basic data | Yulin city land use data | 1995, 2005, 2015 | 30 m | Resource and environmental science data center of the Chinese academy of sciences | ArcGIS was used to reclassify the land use data of the third period into six categories. Data used to simulate and predict future land use changes |
Administrative boundaries of Yulin City | 2015 | – | |||
Natural drivers | DEM | 2015 | 30 m | Geospatial Data Cloud | |
Slope | 2015 | 30 m | |||
Soil type | 2015 | 30 m | Resource and environmental science Data center of the Chinese academy of sciences | ||
Temperature | 1995, 2005, 2015 | 30 m | |||
Precipitation | 1995, 2005, 2015 | 30 m | |||
Socio-economic drivers | Yulin GDP spatial distribution grid data | 1995, 2005, 2015 | 1 km | Use ArcGIS raster data conversion tools to convert GDP and population data to 30-m resolution | |
Yulin Population Spatial Grid DistributionData | 1995, 2005, 2015 | 1 km | |||
Traffic location driveers | Distance to administrative centers | 2015 | – | National geographic information resources directory service system | ArcMap10.5 was used to perform Euclidean distance analysis on the data, which was used by the PLUS model to predict future land use changes |
Distance to river | |||||
Distance to railway | |||||
Distance to highway | |||||
Distance from primary road | |||||
Distance from secondary road | |||||
Distance from tertiary road |
