Fig 1.
Flow chart of the study.
Fig 2.
Land use map in Suzhou (2010 and 2022) based on GlobeLand30 classification.
(Republished from Ministry of Natural Resources of China, http://bzdt.ch.mnr.gov.cn).
Table 1.
Data sources and descriptions.
Table 2.
Example of manual identification.
Table 3.
DNN model input indicators for urban-fringe-rural classification.
Table 4.
Methodologies and principles for assessing ecosystem services (ESs).
Table 5.
Coupling coordination types.
Fig 3.
Spatiotemporal patterns of urban–fringe–rural structure in Suzhou.
(Republished from Ministry of Natural Resources of China, http://bzdt.ch.mnr.gov.cn).
Table 6.
Transfer matrix of urban–fringe–rural spatial structure in Suzhou, 2010–2022.
Fig 4.
Spatial patterns and changes of ESs in Suzhou from 2010 to 2022. (Republished from Ministry of Natural Resources of China, http://bzdt.ch.mnr.gov.cn).
Fig 5.
ESs Changes in urban, fringe, and rural areas from 2010 to 2022.
(Republished from Ministry of Natural Resources of China, http://bzdt.ch.mnr.gov.cn).
Fig 6.
Correlation coefficients of ESs pairs.
* FP—Food production; CS—Carbon storage; WY—Water yield; HQ—Habitat quality; SC—Soil conservation; TN—Nitrogen output; TP—Phosphorus output; LA—Landscape aesthetics.
Fig 7.
Multiple ESs interaction relationships under CCDM and trend direction analysis.
(Republished from Ministry of Natural Resources of China, http://bzdt.ch.mnr.gov.cn).
Fig 8.
Spatiotemporal patterns of interactions among multiple ESs.
(Republished from Ministry of Natural Resources of China, http://bzdt.ch.mnr.gov.cn). Composition and relative magnitude of ESs in the village scale. Longer segments represent higher ES supply. * FP—Food production; CS—Carbon storage; WY—Water yield; HQ—Habitat quality; SC—Soil conservation; TN—Nitrogen output; TP—Phosphorus output; LA—Landscape aesthetics.
Fig 9.
Structure diagram of dynamic urban–fringe–rural areas.
(Republished from Ministry of Natural Resources of China, http://bzdt.ch.mnr.gov.cn).