Analyzing satellite-derived 3D building inventories and quantifying urban growth towards active faults: a case study of Bishkek, Kyrgyzstan

Earth observation (EO) data can provide large scale, high-resolution, and transferable methodologies to quantify the sprawl and vertical development of cities and are required to inform disaster risk reduction strategies for current and future populations. We synthesize the evolution of Bishkek, Kyrgyzstan, which experiences high seismic hazard, and derive new datasets relevant for seismic risk modeling. First, the urban sprawl of Bishkek (1979–2021) was quantified using built-up area land cover classifications. Second, a change detection methodology was applied to a declassified KeyHole Hexagon (KH-9) and Sentinel-2 satellite image to detect areas of redevelopment within Bishkek. Finally, vertical development was quantified using multi-temporal high-resolution stereo and tri-stereo satellite imagery, which were used in a deep learning workflow to extract buildings footprints and assign building heights. Our results revealed urban growth of 139 km2 (92%) and redevelopment of ~26% (59 km2) of the city (1979–2021). The trends of urban growth were not reflected in all the open access global settlement footprint products that were evaluated. Building polygons that were extracted using a deep learning workflow applied to high-resolution tri-stereo (Pleiades) satellite imagery were most accurate (F1 score = 0.70) compared to stereo (WorldView-2) imagery (F1 score = 0.61). Similarly, building heights extracted using a Pleiades-derived digital elevation model were most comparable to independent measurements obtained using ICESat-2 altimetry data and field-measurements (normalized absolute median deviation < 1 m). Across different areas of the city, our analysis suggested rates of building growth in the region of 2000–10,700 buildings per year, which when combined with a trend of urban growth towards active faults highlights the importance of up-to-date building stock exposure data in areas of seismic hazard. Deep learning methodologies applied to high-resolution imagery are a valuable monitoring tool for building stock, especially where country-level or open-source datasets are lacking or incomplete

Significant Seismic Risk Potential From Buried Faults Beneath Almaty City, Kazakhstan, Revealed From High-Resolution Satellite DEMs

Major faults of the Tien Shan, Central Asia, have long repeat times, but fail in large (Mw 7+) earthquakes. In addition, there may be smaller, buried faults off the major faults which are not properly characterized or even recognized as active. These all pose hazard to cities along the mountain range front such as Almaty, Kazakhstan. Here, we explore the seismic hazard and risk for Almaty from specific earthquake scenarios. We run three historical-based earthquake scenarios (1887 Verny Mw 7.3, 1889 Chilik Mw 8.0 and 1911 Chon-Kemin Mw 8.0) on the current population and four hypothetical scenarios for near-field faulting. By making high-resolution Digital Elevation Models (DEMs) from SPOT and Pleiades stereo optical satellite imagery, we identify fault splays near and under Almaty. We assess the feasibility of using DEMs to estimate city building heights, aiming to better constrain future exposure datasets. Both Pleiades and SPOT-derived DEMs find accurate building heights of the majority of sampled buildings within error; Pleiades tri-stereo estimates 80% of 15 building heights within one sigma and has the smallest average percentage difference to field-measured heights (14%). A moderately sized Mw 6.5 earthquake rupture occurring on a blind thrust fault, under folding north of Almaty is the most damaging scenario explored here due to the modeled fault stretching under Almaty, with estimated 12,300±5,000 completely damaged buildings, 4,100 ± 3,500 fatalities and an economic cost of 4,700 ± Million US dollars (one sigma uncertainty). This highlights the importance of characterizing location, extent, geometry, and activity of small faults beneath cities

Variability in surface rupture between successive earthquakes on the Suusamyr Fault, Kyrgyz Tien Shan: Implications for palaeoseismology

Interpretation of surface fault scarps and palaeoseismic trenches is a key component of estimating fault slip rates, earthquake recurrence rates and maximum magnitudes for hazard assessments. Often these analyses rely on the assumption that successive earthquakes all breached the surface and that the ruptures are recorded topographically, or by the deposits exposed in a trench. The Mw7.2 1992 Suusamyr earthquake, Kyrgyzstan, is an apparently problematic case for such analyses because its ruptures show significant displacement but are only mapped as having broken the surface along small, disparate portions of the fault. Here we present the results of surveys conducted along the Suusamyr Fault to establish whether that is the case. Two sets of ruptures were identified following the earthquake. They are unusually short for their displacement and are separated by a 25 km gap. Using satellite imagery, high-resolution digital elevation models and palaeoseismic trenching we first reassess the distribution of the 1992 ruptures and then reconstruct the Holocene earthquake record to establish the extent to which the 1992 earthquake is representative of the rupture behaviour of this fault. We find evidence for at least two prehistoric surface rupturing earthquakes in the Holocene: one ~3 ka and one > 8 ka that, along with the modern event, gives recurrence intervals of ~3 and ~5 kyr. Within spatial gaps between segments of the 1992 ruptures there are clear prehistoric surface ruptures and the ruptures in each prehistoric earthquake were discontinuous. We conclude that there is significant variability in the surface rupture pattern of successive earthquakes on the Suusamyr Fault, with implications for the completeness of palaeoseismic records obtained from thrust scarps