Spatiotemporal analysis of the impact of urban landscape forms on PM_2.5 in China from 2001 to 2020

Figures & data

Figure 1. Experimental flowchart.

Figure 2. Study area location.

Table 1. Data summary.

Index	Formula	Description	Interpretation
Proportion of landscape (PLAND)	$PLAND={\displaystyle \frac{{\sum }_{j=1}^n{a}_{ij}}{A}\times 100}$	aij indicates the area (m^2) of the jth patch in the ith category of landscape type, and A is the total area of the landscape (hm^2).	PLAND indicates the ratio of a particular patch to all patches in the area. The value of PLAND represents how much of the plaque is weighted.
Fractal dimension (FRACT)	$FRACT={\displaystyle \frac{2\ln (0.25P_{ij})}{\ln a_{ij}}}$	where pij is the landscape perimeter (m), and aij is the landscape area (m^2).	FRACT indicates landscape complexity by patch shape, with higher FRACT values indicating more complex shapes.
Shannon’s Diversity (SHDI)	$SHDI=-\sum _{i=1}^m(P_i\times \ln P_i)$	m is the number of landscape types and Pi is the ratio of the area of landscape type i to all landscape.	The SHDI indicates the categorical diversity of patches in the region.

Figure 3. Spatial distribution (a-e) and temporal trend (f) of PLAND-UGI regression coefficients.

Figure 4. Spatial distribution (a-e) and temporal trend (f) of PLAND-Impervious regression coefficients.

Figure 5. Spatial distribution (a-e) and temporal trend (f) of FRACT-UGI regression coefficients.

Figure 6. Spatial distribution (a-e) and temporal trend (f) of FRACT-Impervious regression coefficients.

Figure 7. Spatial distribution (a-e) and temporal trend (f) of SHDI regression coefficients.

Figure 8. Contribution of urban landscape composition indices to PM_2.5 concentrations during 2001–2020.

Figure 9. Marginal effects of urban landscape on PM_2.5 concentration.

Data availability statement

Relevant data used for this study are available from the corresponding authors upon request.