## 3 Results
### Building Characteristics  
High-resolution DSMs were used to assign heights to building polygons following the workflow outlined in Section 2.3.2. The Pleiades and WorldView-2 DSMs had comparable errors (NMAD = 0.62 and 0.51, respectively) (Figure 7). Within the same intersecting AOI extents (Figure 1b), data gaps were greatest in the WorldView-2 DSM, which featured 91% coverage, compared to 99% for the Pleiades DSM. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Metric** & **Pleiades (2013)** & **WorldView-2 (2019)** &
\begin{tabular}{c} **Google Satellite** \\ **Basemap (2021)** \\ \end{tabular} \\ \hline Number of buildings (Mask R-CNN) & 1090 & 1024 & 967 \\ Number of buildings (validation) & 1163 & 1113 & 1064 \\ TP (overlap) & 781 & 652 & 676 \\ FP (no overlap) & 309 & 372 & 291 \\ FN (reference not overlapping Mask R-CNN) & 374 & 461 & 388 \\ Total area reference (m\({}^{2}\)) & 151,961 & 194,427 & 141,164 \\ Total area Mask R-CNN & 142,930 & 189,880 & 140,597 \\ Total area overlap (m\({}^{2}\)) & 110,223 & 149,066 & 108,072 \\ True overlapping area (\%) & 72.53 & 76.67 & 76.56 \\ Precision & 0.72 & 0.64 & 0.70 \\ Recall & 0.68 & 0.59 & 0.64 \\ F1 & 0.70 & 0.61 & 0.67 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Validation of the building detection deep leaning classification (see Section 2.3.1). Figure 6: (**a–f**) Examples of building detections (blue) and validation (green) within 200 m analysis windows for Pleiades, WorldView-2, and Google Satellite Basemap imagery (Section 2.3.1). The top row (**a,c,e**) shows examples of low-rise residential areas, and the bottom row (**b,d,f**) shows examples of medium/high-rise buildings). Mean and one standard deviation of elevation values were assigned to individual building polygons using internal polygon buffers of ranging from zero to three meters (Figure 8). The standard deviation of building height was observed to decrease with increasing buffer size. For example, standard deviation decreased from 0.9 m to 0.6 m in the Pleiades dataset for building polygons with no buffer and a buffer of \(-2\) m, respectively (Figure 8b). The most stringent internal buffer (\(-3\) m) did not lead to further improvement and notably reduced the number of buildings with valid heights assigned (following Section 2.3.2). We therefore used building heights extracted with a buffer of \(-2\) m (Figure 8). Figure 7: (a–d) Elevation accuracy statistics for DSMs compared to ICESat-2 data over their respective AOIs (Figure 1b). Independent Pleiades and WorldView-2 derived building heights (MAE = 0.79 m) and absolute elevations (DSM elevation values) (MAE = 0.50 m) (Figure 9a,b) showed close agreement. Similarly, comparing DSM-derived elevation values to ICESat-2 altimetry data revealed that the DSM elevation values were systematically lower than the ICESat-2 data by \(\sim\)2 m (median values of \(-1.9\) m and \(-1.6\) m for Pleiades and WorldView-2, respectively) (Figure 9c). NMAD values from the DSM and ICESat-2 comparison were 0.67 m for Pleiades and 0.68 m for WorldView-2, whereas MAE values were closer to 2 m (Figure 9c). The building height MAE 1.74 m (Pleiades) and 1.78 m (WorldView-2) for buildings observed in the field were comparable to those obtained in the ICESat-2 comparison (1.86 m--Pleiades and 1.72 m--WorldView-2) (Figure 9c). The NMAD was lowest for the Pleiades-derived building heights for both the ICESat-2 (0.67 m) and field comparisons (0.43 m) (Figure 9c,d). We show the distribution of Pleiades-derived building heights, which covered most of Bishkek's districts in Figure 10. The tallest buildings are clustered in the center of Bishkek and the southeast. Figure 8: (**a**) Mean building heights for the dataset of Pleiades and WorldView-2 detections. (**b**) One standard deviation of building height for Pleiades and WorldView-2 detections. Boxplot annotation (**a,b**) shows mean values. Building counts (n) are shown for each dataset buffer.