## 2 Data and Methods
### Data and Preprocessing  
The land cover data for the Lanxi urban cluster in 2001 and 2021 were extracted from the 30 m annual land cover dataset (CLCD) provided by the [PERSON] team at Wuhan University [51]. The dataset, with a spatial resolution of 30 m and uses the World Geodetic System 1984 (WGS 1984) [52], achieves an average accuracy of 79.31%, which outperforms the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product (MCD12Q1) [53], the annual land-cover (LC) maps produced by the European Space Agency Climate Change Initiative (ESA-CCI) project [22] and Fine Resolution Observation and Monitoring of Global Land Cover (FROM_GLC) [54]. Compared with other Landsat-based thematic products, this dataset exhibits superior consistency in impermeable surface and global forest change delineation. This dataset consists of 9 land cover categories (cropland, forest, shrub, grassland, water, built-up area, barren, barren and wetland), which are widely employed in research on land cover type conversions. They play an indispensable role in land use studies in China [55; 56; 57]. The dataset was masked via the vector boundary of the Lanxi urban cluster in ArcGIS 10.8 software [58] to extract the urban land cover data for 2001 and 2021. The vegetation defined in this study includes cultivated land, forests, shrubs, and grasslands, which means that this study investigates the impact of urban expansion on the aforementioned land types.  
Figure 1: The Lanxi urban cluster. (**a**) Mean precipitation of the Lanxi urban cluster from 2000 to 2020. (**b**) The proportion of different land cover types in the Lanxi urban cluster in 2021.  
The vector boundaries of the Lanxi urban cluster were obtained from the 1:1,000,000 National Basic Geographical Database, a component of the National Geospatial Information Resource Catalog Service System: [[https://www.webmap.cn/](https://www.webmap.cn/)]([https://www.webmap.cn/](https://www.webmap.cn/)) (accessed on 20 April 2024).  
The rainfall data from 2001 to 2021 were sourced from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) high-resolution global rainfall dataset: [[https://data.chc.ucsb.edu/products/CHIRPS-2.0/](https://data.chc.ucsb.edu/products/CHIRPS-2.0/)]([https://data.chc.ucsb.edu/products/CHIRPS-2.0/](https://data.chc.ucsb.edu/products/CHIRPS-2.0/)) (accessed on 20 April 2024). This global precipitation dataset was developed by the Climate Hazards Group at the University of California, Santa Barbara; it combines satellite infrared observations with ground station observations to provide high-resolution rainfall data worldwide. The CHIRPS dataset spans over 30 years and has a spatial resolution of 0.05 degrees, providing daily precipitation data. The data were processed by cropping and downloading via the Google Earth Engine platform [59].  
The EVI data were sourced from the MODIS dataset released by the National Aeronautics and Space Administration (NASA): [[https://lpdaac.usgs.gov/data/](https://lpdaac.usgs.gov/data/)]([https://lpdaac.usgs.gov/data/](https://lpdaac.usgs.gov/data/)) (accessed on 17 April 2024). The spatial resolution is 250 m, and the temporal resolution is 16 days. The data were extracted and downloaded via the Google Earth Engine. In ArcGIS, the EVI data were subsequently combined with the rainfall data to calculate the VDI.