Table 2 Data sources of natural geographic and socio-economic indicators for traditional villages in Suzhou

From: Spatial distribution characteristics and influencing factors of Suzhou traditional villages from the perspective of “Millennium Village”

Data name

Time

Data source

Data format

Description of use

Elevation (m)

2009

Geospatial Data Cloud (https://www.gscloud.cn)

GeoTIFF (30 m-resolution)

Using ArcGIS 10.8’s Spatial Analyst, the original DEM data was clipped via Extract by Mask, and elevation raster values were extracted to village points using Extract Values to Points.

Slope (◦)

2009

Geospatial Data Cloud (https://www.gscloud.cn)

GeoTIFF (30 m-resolution)

Using ArcGIS 10.8’s Spatial Analyst, slope values were extracted from DEM data to village points via the Slope tool.

Slope aspects (◦)

2009

Geospatial Data Cloud (https://www.gscloud.cn)

GeoTIFF (30 m-resolution)

Using ArcGIS 10.8’s Spatial Analyst, aspect values were extracted from DEM data to village points via the Aspect tool.

Annual precipitation (mm)

1960

The Resource and Environmental Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn).

GeoTIFF (1 km-resolution)

Using ArcGIS 10.8’s Spatial Analyst, annual precipitation raster values were extracted to village points via Extract Values to Points.

Annual average temperature (°C)

1960

The Resource and Environmental Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn).

GeoTIFF (1 km-resolution)

Using ArcGIS 10.8’s Spatial Analyst, annual average temperature raster values were extracted to village points via Extract Values to Points.

Distance to river (m)

2019

National Geomatics Center of China (https://www.webmap.cn).

Shapefile

Using ArcGIS 10.8’s Analysis Tools, the Multiple Ring Buffer was used to generate multi-ring buffers, with the number of villages in each buffer counted and their proportions calculated. Using ArcGIS 10.8’s Analysis Tools, the Near tool was used to calculate the straight-line Euclidean distance from villages to rivers, and the average and minimum distances from all villages within each buffer to rivers were statistically analyzed.

Road density

2019

National Geomatics Center of China (https://www.webmap.cn).

Shapefile

Using ArcGIS 10.8’s Spatial Analyst Tools, Line Density was used to generate and quantify road density rasters. Using ArcGIS 10.8’s Spatial Analyst Tools, reclassified density grade raster values were linked to village points via Extract Values to Points.

Population(person/km²)

1995

The Resource and Environmental Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn).

GeoTIFF (1 km-resolution)

Using ArcGIS 10.8’s Spatial Analyst, the original Population data was clipped via Extract by Mask, and population density raster values were extracted to village points using Extract Values to Points.

GDP(10,000 Yuan/km²)

1995

The Resource and Environmental Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn).

GeoTIFF (1 km-resolution)

Using ArcGIS 10.8’s Spatial Analyst, original GDP data were clipped via Extract by Mask, and GDP raster values were extracted to village points using Extract Values to Points.

Urbanization rate (%)

GeoTIFF (1 km-resolution)

Using ArcGIS 10.8’s Spatial Analyst, Euclidean Distance was used to generate Euclidean distance rasters from traditional villages to major administrative units, and the raster values were extracted to village points via Extract Values to Points.