## 3 Results
### Building Classification  
Within the respective data extents (Figure 1b), we extracted 205,056 buildings from the 2013 Pleiades imagery, 67,091 from the 2019 WorldView-2 imagery, and 429,001 from the 2021 Google Satellite Basemap imagery. OpenStreetMap buildings within the same AOI as the Google Satellite Basemap detections totaled 160,141. We extracted all building detections falling within the intersecting WorldView-2, Pleiades, and Google Satellite Basemap imagery extents (83 km\({}^{2}\)) (Figure 1b) to enable a comparison across all datasets through time. Buildings totaled 49,502 for the Pleiades imagery (2013), 61,102 for the WorldView-2 imagery (2019), 65,349 for the Google Satellite Basemap imagery (2021), 63,597 for GlobalMLBuildingFootprints (dated \(\sim\)2016 for Bishkek, see Section 2.3.1), and 33,283 for OpenStreetMap (unknown date). The number of buildings within the intersecting AOI therefore increased by 11,600, as observed by the Pleiades (2013) and WorldView-2 (2019) datasets, and 15,847, as observed using the Pleiades and Google Satellite Basemap (2021). Within the larger Pleiades AOI (Figure 1b), there was a 42% (85,658) increase in buildings 2013-2021 observed from the 2013 Pleiades data (205,056 buildings) and 2021 Google Satellite Basemap (290,714 buildings). Buildings from the GlobalMLBuildingFootprints dataset within the Pleiades AOI totaled 275,462, which was therefore in the range of the Pleiades and Google Satellite Basemap-derived estimates. Figure 3: Built-up area change in Bishkek. (**a**) 1979 KH-9 built-up area classification. (**b**) Difference in built-up area 1979–2016–2021 with Bishkek’s districts overlaid. (**c**) Landcover classification of the 2021 Sentinel-2 image. (**d**) Change in built-up area through time for the same AOI (**a–c**). 95% confidence intervals are shown for the KH-9 and Sentinel-2 ‘S2′ classifications (2016 and 2021). Population estimates (blue line) are from Macrotrends [72] and United Nations Statistics Division [73] (blue squares). Leninsk District had the most buildings overall and by square kilometer (1351 buildings/km\({}^{2}\)) (Figure 5, Table 1). Oktiabrskii District had the largest buildings on average (208 \(\pm\) 461 m\({}^{2}\)), which corresponded with the presence of industrial/commercial areas (Figure 3c) and the larger observed building size in these areas (mean of 176 m\({}^{2}\)) (Figure 5d). Figure 4: Redevelopment within Bishkek (1979–2021). **(a)** Digital number change 1979–2021 from the difference of KH-9 and Sentinel-2 imagery (Section 2.1.4). Pie charts show the proportional DN change aggregated to a 1 km\({}^{2}\) grid for areas \(\geq\)50% built-up. Inset shows a violin and boxplot of Sentinel-2 NDVI values for negative DN change (vegetated) and positive DN change (built-up redevelopment) classes. **(b)** Example of redevelopment of an area in central Bishke where the building layout noticeably changes. **(c)** Example increased vegetation (trees) around buildings in south Bishkek. Extents of **(b,c)** are shown on panel **(a)**. The Pleiades classification featured the highest precision, recall, and F1 score (0.72, 0.68, and 0.70, respectively) (Table 2), followed by Google Satellite Basemap (0.70, 0.64, 0.67) and WorldView-2 (0.64, 0.59, 0.61). Examples of detections and validation data are shown in Figure 6. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**District** & **District Size** & **Number of** **(km2)** & **Buildings** & **Buildings** & **Mean Building Size** (m2) & **500 m Grid Cell Building** \\  & **(km2)** & **Buildings** & **per km2** & **(m2)** & **(One Standard** & **Coverage (\%) (One** \\  & & & & **Deviation)** & **Standard Deviation)** \\ \hline Leninskii District & 54 & 72,714 & 1351 & 137 (239) & 19 (6) \\ Oktiabrskii District & 35 & 23,714 & 670 & 208 (461) & 15 (9) \\ Pervomaiskii District & 42 & 48,773 & 1150 & 137 (250) & 18 (7) \\ Sverlovskii District & 35 & 45,155 & 1274 & 146 (368) & 19 (7) \\ \hline \hline \end{tabular}
\end{table}