Fig 1.
Interaction between the influencing factors of resource and environmental carrying capacity.
Fig 2.
The spatial location of the Loess Plateau region and its representative cities.
The base map outline was obtained by using ArcGIS 10.2 based on the Service Center of Standard Map (http://bzdt.ch.mnr.gov.cn/) and the number of the permission is GS (2020) 4621. The spatial extent of the Loess Plateau was obtained from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (http://www.resdc.cn/).
Table 1.
Classification of natural areas in the Loess Plateau.
Table 2.
Indicator systems of resource and environmental carrying capacity.
Fig 3.
The calculation results of resource and environmental carrying capacity in 24 cities from 2013 to 2018.
Note: The growth rate of the carrying capacity of each city decreases clockwise at 12 o’clock. Same as below.
Table 3.
The growth rate of the carrying capacity of each subsystem in 24 cities from 2013 to 2018 (%).
Fig 4.
The calculation results of each subsystem carrying capacity in 24 cities from 2013 to 2018.
(a) Economic carrying capacity; (b) Social carrying capacity; (c) Resource carrying capacity; (d) Environmental carrying capacity.
Fig 5.
Average resource and environmental carrying capacity in 24 cities from 2013 to 2018.
Fig 6.
Performances of the resource and environmental carrying capacity of 24 cities in 2013, 2015, and 2018.
Fig 7.
Temporal and spatial pattern of resource and environmental carrying capacity index.
The image was obtained by using ArcGIS 10.2 through the open-access data process. The spatial extent of the Loess Plateau was obtained from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (http://www.resdc.cn/).
Fig 8.
Temporal and spatial pattern of carrying capacity (left: economic carrying capacity; right: social carrying capacity).
The image was obtained by using ArcGIS 10.2 through the open-access data process. The spatial extent of the Loess Plateau was obtained from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (http://www.resdc.cn/).
Fig 9.
Temporal and spatial pattern of carrying capacity (left: resource carrying capacity; right: environmental carrying capacity).
The image was obtained by using ArcGIS 10.2 through the open-access data process. The spatial extent of the Loess Plateau was obtained from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (http://www.resdc.cn/).
Fig 10.
Obstacle indicators for resource and environmental carrying capacity in 20 cities in 2018 (top five).
Table 4.
Obstacle indicators for cities with negative resource and environmental carrying capacity growth from 2013 to 2018 (top five).
Fig 11.
Conceptual framework for resource and environmental carrying capacity impact mechanism.