Carbon storage simulation and analysis in Beijing-Tianjin-Hebei region based on CA-plus model under dual-carbon background

Figures & data

Figure 1. Location and topography of the study area.

Table 1. Carbon density of different vegetation types.

Vegetation type	Carbon density (t/ha)
Mountain deciduous coniferous forest	52.3
Evergreen coniferous forest	22.4
Evergreen hard-leaved broad-leaved forest	58.8
Machaka	7.7
Low semi-shrub desert	1.2
Grass land	2.1
Lake/Ocean	0
Cultivated land	5.7
Bare soil	0

Table 2. Data introduction.

Data type	Data sources	Data description	Data processing
Land use data	Resource and Environmental Science Data Centre	1990–2020, 1 km	Reclassification
1:1 million vegetation type data	National Tibetan Plateau Science Data Center	2001, 1 km	Reclassification
Carbon density table of vegetation types	–	–	–
National population data	Resource and Environmental Science Data Centre	2019, 1 km	Mask extraction
National GDP data		2019, 1 km	Mask extraction
National basic geographic data		2020, 1:100,000	Euclidean distance
			Euclidean distance
DEM	Geospatial data cloud	2020, 90 m	Reclassification
Slope		2020, 90 m	Reclassification

Figure 3. Spatial distribution of carbon storage from 1990 to 2020. (a) 1990; (b) 2000; (c) 2010; (d) 2020.

Figure 4. Change of carbon storage in different regions. (a) 2000–2010; (b) 2010–2020.

Figure 6. Change of carbon storage in 2030-2060 under multiple scenarios.

Figure 7. Change of carbon storage under the inertial development scenario. (a) 2020–2040; (b) 2040–2060.

Figure 8. Change of carbon storage under the ecological protection scenario. (a) 2020–2040; (b) 2040–2060.

Figure 9. Change of carbon storage under the farmland protection scenario. (a) 2020–2040; (b) 2040–2060.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Guo B, upon reasonable request.