## 2 Materials and Methods
### Digital Elevation Model Generation and Analysis  
High-resolution satellite imagery from Pleiades and WorldView-2 satellites were used to produce DSMs and orthorectified satellite images for building footprint and height extraction (Figure 2b). We used a stereo WorldView-2 acquisition from 10 October 2019 (0.5 m panchromatic, 2 m multi-spectral) and a tri-stereo Pleiades acquisition from 2 November 2013 (0.7 m panchromatic, 2.5 m multi-spectral) (Figure 1b) delivered with rational polynomial coefficients (RPCs) (Table S1). Agisoft Metashape v1.8.0 [55] was used to process the imagery to derive DSMs and orthorectified imagery, e.g., [56]. (1) The panchromatic imagery was aligned in one chunk to produce a sparse point cloud; (2) outliers were removed from the sparse cloud using Metashape's gradual selection tools to reduce the root mean square reprojection error to \(\leq\)0.5 pix; (3) the panchromatic imagery was used to derive a dense point cloud using 'high' quality settings and no depth filtering, which was used to interpolate a 1.5 m resolution DSM; (4) this DSM was used to orthorectify both the most nadir panchromatic and multi-spectral satellite images. The Pleiades and WorldView-2 multi-spectral imagery was pansharpened to 0.5 m resolution using the Gram-Schmidt algorithm and the respective sensor model and band weights (Pleiades or WorldView-2) in ArcGIS Pro 2.8 [57].  
Two additional DSMs were derived using 3.7 m resolution PlanetScope (PS) imagery [58] to determine whether these DSMs were able to resolve buildings in Bishkek. We used the red, green, and blue bands from 43 level 1B images from the PSB.SD instruments onboard the SuperDove satellite constellation acquired March to April 2021 (Table S1) and followed the same processing workflow described in Metashape, with an additional filter applied to the dense point cloud to minimize noise. The PlanetScope imagery has a near-nadir viewing geometry; therefore, many overlapping images are required to generate a DSM [59]. We removed dense cloud points that were present in less than three depth maps to create DSM 'v1', and points present in less than six depth maps to create a DSM 'v2', both output at 9 m resolution.  
All DSMs were coregistered to the 12 m resolution TanDEM-X DSM [60] following the x, y, z shift correction of [PERSON] and [PERSON] [61]. Ice, Cloud, and land Elevation Satellite (ICESat-2) altimetry data were used to validate the vertical accuracy of the DSMs (Figure 1b). We downloaded all ATL03 ICESat-2 data [62; 63] over Bishkek up to 8 April 2021 using OpenAltimetry [64]. Data spanned 14 November 2018 to 9 November 2020 and included tracks 0272, 0310, 0714, 0752, 1156, 1194. Only 'high' confidence photons were used, which were gridded at 5 m resolution and removed cells with fewer than two photons, a range greater than 1 m, and a vertical difference from the TanDEM-X of \(>\)80 m to avoid removing points on tall buildings. Accuracy statistics were reported over slopes \(<\)10\({}^{\circ}\), e.g., [65], which captures our city area of interest (AOI), and outliers \(\geq\)20 m were removed (\(\geq\)50 m for PlanetScope). Error metrics included root mean square error (RMSE) and normalized absolute median deviation (NMAD), of which the latter is considered more resilient to outliers [66].