Green space coverage versus air pollution: a cloud-based remote sensing data analysis in Sichuan, Western China

Figures & data

Table 1. List of four different datasets used in this research.

Data	Use in this study	Data source
Landsat-8	GSC	https://developers.google.com/earthengine/datasets/
Sentinel-5p	NO2	GEE ID = COPERNICUS/S5P/OFFL/L3_NO2
MODIS	PM 2.5	https://weijing-rs.github.io/product.html
Weather station	NO2 and PM2.5	http://www.cnemc.cn/

Figure 1. (a) Location of Sichuan Province in China. (b) Map of High Human Activity (HHA) and Low Human Activity (LHA) zones used in this study, along with the boundaries of Sichuan cities. (c) The elevation map of Sichuan and the location of ground-based weather stations used in this study. (d) and (e) An example of air pollution in the Tianfu New Area, Chengdu City in December 2023.

Figure 2. The main workflow of this study.

Table 2. Description of different GSC classes in this study.

Class type	Description
tall GSC	Tall GSC refers to a category of GSC that includes tall vegetation types, such as forests and shrub areas, that exceed a height of 2 meters.
short GSC	The short GSC category includes small GSC types, such as shrubs that are less than 2 meters in height, grasslands, and croplands.
non-GSC	Non-GSC refers to a category that encompasses all areas that are not classified as GSC, including developed areas, bare lands, open water, and snow/ice.
mixed	This class combines characteristics from the three types mentioned above.

Figure 3. An example of the generated GSC map for the HHA of Chengdu City, the capital of Sichuan province.

Figure 4. (a) & (b) Satellite-based NO₂ retrieval for 2019 and 2022 over Sichuan Province. (c) Monthly mean value of NO₂ over Sichuan Province. (d) Annual min, max, mean, and StDev values of NO₂ over Sichuan Province. (e) & (f) Satellite-based PM2.5 retrieval for the years 2019 and 2022 over Sichuan Province. (g) Monthly mean value of PM2.5 over Sichuan Province. (h) Annual min, max, mean, and StDev values of PM2.5 over Sichuan Province.

Figure 5. (a) Monthly mean value of PM2.5 in 2019 and 2022 over HHA and LHA regions. (b) Monthly mean value of NO₂ in 2019 and 2022 over HHA and LHA regions. (c) Annual min, max, mean, and StDev values of NO₂ in 2019 and 2022 over HHA and LHA regions. (d) Annual min, max, mean, and StDev values of PM2.5 in 2019 and 2022 over HHA and LHA regions.

Figure 6. Annual min, max, mean, and StDev values for NO₂ and PM2.5 pollutants for various GSC classes over HHA and LHA regions.

Data availability statement

Landsat-8 and satellite-based NO2 data are accessible for free download at https://developers.google.com/earth-engine/datasets; PM 2.5 data is also publicly available at https://weijing-rs.github.io/product.html. The ground-based NO₂ and PM2.5 provided by the China national environmental monitoring center is available at http://www.cnemc.cn/.