*3.1. GIS Spatial Analysis: Location, FAR, Accessibility, and Housing Conditions*

Resettlement communities are where the government relocated the farmers who lived in the demolished villages. Suzhou's urbanization process demolished many rural villages, and the inhabitants resettled in urban communities built cheaply and quickly for this purpose [80–84].

The research has identified 176 resettlement communities in a 50 km diameter area centered in Suzhou old town and involving the central 6 districts of Suzhou (Gusu, Xiangcheng, Suzhou Industrial Park, Wuzhong, Wujiang, and Suzhou New District) (Figure 1). They were built in the late 1980s, occupy more than 2200 ha, and consist of almost 360,000 residential units with approximately 1 million people. Still, their population is floating as these communities include a large percentage of immigrants. The average number of units is around 2000; the largest community has 14,000 units, and the smallest has 112 units.

**Figure 1.** Resettlement communities' location in Suzhou.

Official data about the resettlement communities are not available. A general survey of the resettlement communities was conducted with site visits and GIS analysis of the built stock, the green spaces, and the mobility system using satellite images from 3 platforms [85,86]: Google Earth, Baidu maps, and Suzhou map 512, which is the official

website of the Suzhou Natural Resources and Planning Bureau. This analysis defined the essential land-use parameters of every community: the area of the occupied land, the building coverage, the green coverage, and the gross floor area (GFA).

The data available online on the webpages of the real estate agencies managing the communities stock allowed us to identify the construction year, the total number of residential units, the minimum and the maximum units' dimensions, the GFA, and the number of floors of the different buildings (Tables 3 and 4). According to these data, the FAR was calculated in every community.

**Table 3.** A detailed description of the data source used in the research.


#### **Table 4.** Measurement method and analysis equation.


The basic spatial data were analyzed with the POI (point of interest) and AOI (area of interest) data. Community basic data refer to the list of resettlement communities, community construction years, average housing prices, number of building floors, and real-life photos obtained from the Anjuke lnc. (a second-hand housing trading website) and the Renting website. POI and AOI data were sourced from the open platform of Goddard, and the POI points in the Suzhou area were crawled from the API interface. There are 20 categories of POI on the map of Goddard, such as catering, shopping, life, sports, leisure, medical care, accommodation, public facilities, etc. Each significant category also has secondary and tertiary subdivisions. AOI refers to POIs with planar and regional characteristics, including but not limited to industrial parks, school campuses, commercial districts, residential communities, scenic spots, train stations, airports, and other types of POIs.

The calculation formula (Table 4) mainly includes three aspects: FAR, community accessibility and housing conditions. The calculation formula for FAR is based on the number of layers and AOI calculations verified by satellite images. Community accessibility is, on the one hand, the road reachability calculated by spatial design network analysis (sDNA), and on the other hand, the calculated public transport allocation level around the community. Road accessibility and public transport were added at the data level, and the final results were presented in five categories using the natural discontinuity method throughout the entire research scope. The housing conditions evaluation includes metrics such as housing price, number of households, and greening rate. The housing price, number of houses, and green rate were added at the data level, and the final results were

presented in five categories using the natural discontinuity method throughout the entire research scope. In addition, we also calculated the combination of three indicators: FAR, housing price, and accessibility, and the results were visually overlaid by three indicators, presenting different results based on different colors.
