Identification of densely populated-informal settlements and their role in Chinese urban sustainability assessment

Figures & data

Figure 1. Specific study areas in three Chinese cities: (a) Beijing, (b) Shanghai, and (c) Guangzhou.

Notes: Urban and rural land, industrial and mining land, residential land area data were extracted from the 2020 China Land-Use Remote Sensing Monitoring data, published by the Resource and Environmental Science and Data Center of the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (https://www.resdc.cn/data.aspx?DATAID=335), with a spatial resolution of 30 m.

Table 1. Experimental data sets.

No.	Dataset	Year	Spatial resolution	URL
1	Gaofen-2	2019	0.8 m	http://www.cresda.com/CN/index.shtml
2	Luojia-1	2018	130 m	http://59.175.109.173:8888/
3	Sentinel-2	2019	10 m	https://scihub.copernicus.eu/
4	RTUD	2019	1,000 m	https://heat.qq.com/index.php
5	Road network data	2019	—	http://www.openstreetmap.org/
6	WorldPop dataset	2019	100 m	https://www.worldpop.org/
7	China Land-Use Remote Sensing Monitoring Data	2019	30 m	https://www.resdc.cn/-data.aspx?DATAID=335

Figure 2. Paper structure.

Figure 3. Accuracy of different models.

Figure 4. Informal settlement identification based on multi-source geographic information data.

Figure 5. Architecture of the VGG16 network.

Figure 6. Characteristics of informal settlements in Gaofen images. (a) dilapidated houses. (b) high-density distribution. (c) Disorderly distribution.

Figure 7. Spatial distribution of densely populated-informal settlements (DPISs) in the study areas: (a) Beijing, (b) Shanghai, and (c) Guangzhou. The background of the map is from Gaode map (https://www.amap.com/).

Figure 8. Densely populated-informal settlements and formal settlement (FS) images obtained from Gaofen-2 satellite images.

Figure 9. Areas, total population, and density statistics of DPISs in the study area.

Figure 10. Urban land-use changes and DPIS distribution in the study areas from 1980 − 2020: (a) Beijing, (b) Shanghai, and (c) Guangzhou.

Figure 11. Comparison of land-use changes in DPISs in three cities: Beijing, Shanghai, and Guangzhou.

Figure 12. Distribution of normalized difference vegetation index (NDVI), night lighting, and real-time Tencent user density (RTUD) in different types of settlements in (a) Beijing, (b) Shanghai, and (c) Guangzhou.

Figure 13. Field investigation photo records and Baidu Street Views of DPISs in 2019. (a) and (b) Wanping city, Beijing. (c) and (d) Shikumen, Shanghai. (e) and (f) South side of Huangpu District, Guangzhou.

Table 2. Characteristics of settlements defined in sustainable development Goal (SDG) 11.1 and densely populated‒informal settlements (DPISs).

Characteristics	Settlements in SDG 11.1			DPIS
	Slums	Informal settlements	Inadequate living space
Lack of quality drinking water	√	√	-	×
Lack of improved sanitation	√	√	-	○
Crowded living space	√	-	-	√
Residential structures of questionable quality	√	√	-	○
Lack of legal residency rights	√	√	√	○
Lack of affordability	-	-	√	○
Lack of demand for special populations	-	-	√	○
Lack of livability	-	-	√	√
Lack of adequate infrastructure	-	-	√	√
Lack of adequate culture	-	-	√	○

Notes: “√” indicates compliance, “×” indicates noncompliance, “○” indicates partial compliance, and “-” indicates that this characteristic is not included.