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Fault slip rates estimated from geodetic data are being integrated into seismic hazard models. The standard approach requires modeling velocities and relative (micro‐)plate motions, which is challenging for fault‐based models. We present a new approach to directly invert strain rates to solve for slip rates and distributed strain simultaneously. We generate velocity and strain rate fields over the southeastern Tibetan Plateau, utilizing Sentinel‐1 Interferometric Synthetic Aperture Radar data spanning 2014–2023. We derive slip rates using block modeling and by inverting strain rates. Our results show a partitioning between localized strain on faults and distributed deformation. The direct inversion of strain rates matches the geodetic data best when incorporating distributed moment sources, accounting for a similar proportion to on‐fault sources. The direct strain methodology also aligns best with the independent geological slip rates, especially near fault tips. As high‐resolution strain rate fields become increasingly available, we recommend direct inversion as the preferred practice. Plain Language Summary: We focus on understanding earthquake potential in the southeastern Tibetan Plateau by measuring how and how fast the crust deforms. By analyzing 9 years of satellite radar images, we estimate how fast faults are slipping, which is crucial for assessing the hazard of future earthquakes. We tested two methods and found that the method directly incorporating measurements of surface strain rates provides more accurate results when compared to field‐based geologic slip rates. We show that the total deformation field is roughly equally split between energy accumulation on mapped active faults and distributed deformation away from the faults. The large amount of diffuse strain is an important constraint for rates of background seismicity. We discuss the limitations of various techniques used in modeling Earth's interseismic deformation and suggest prioritizing the direct strain methodology. Key Points: We construct velocity and strain rate fields covering 1.3 million km2 of SE Tibet from Sentinel‐1 Interferometric Synthetic Aperture RadarDeformation is partitioned approximately equally between focused strain on the main mapped faults and diffuse deformationDirect inversion of strain rates removes the requirement to define artificial "blocks" and gives a better match to geological slip rates [ABSTRACT FROM AUTHOR]

Artificial light at night (ALAN) has positive and negative effects on social, economic, environmental, and ecological systems, and will increase with urban expansion. In this study, we used a multi-spectral 1.5 m resolution night-time acquisition from a Jilin-1 satellite over the city of Quito, Ecuador, to evaluate spatial lighting patterns in an expanding and topography complex-built environment. We demonstrated a requirement for robust georeferencing and orthorectification due to the complex topography, with errors on the order of 4–6 pixels (5.8–8.4 m CE95). We also quantified differences in observed brightness due to the image acquisition and local geometry. Street light type was distinguishable between high-pressure sodium (HPS) and light emitting diode (LED) sources (F1-score = 0.72–0.83) using a shark random forest decision tree approach. Additionally, street lights could be located within 10 m (F1-score = 0.71) with balanced omissions and commissions. Spatial trends revealed that the road network was the dominant source of illumination, accounting for 45% of illuminated pixels, whereas built-up areas accounted for 23%. Overall, 68% of all illuminated pixels were on or within 10 m of the road. Higher socio-economic development was associated with higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces. The broad impacts of ALAN mean that addressing the causes and consequences of lighting inequalities is a complex issue. Nonetheless, Jilin-1 night-time imagery offers a low-cost way to map and monitor light sources at high-resolution that will be beneficial to city-planners and progressing Sustainable Development Goals. Image acquisition geometry affects the observed radiance and would require consideration when evaluating spatial and temporal trends. Jilin-1 night-time satellite imagery offers a low-cost mechanism to map and monitor light sources at high-resolution that is sufficient to identify individual sources such as street lights, buildings, and recreational spaces. Radiance intensity was correlated with the degree of socio-economic development. In the higher socio-economic classes, we observed higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In the continents, the importance of earthquakes that occur away from major block‐bounding faults is still debated. The 21 May 2021 MW ∼ 7.4 Maduo earthquake occurred on a secondary fault away from previously‐identified major block boundaries. Here we use 7 years of Sentinel‐1 Interferometric Synthetic Aperture Radar (InSAR) time series (between October 2014 and November 2021) to determine the distribution of coseismic slip and early postseismic afterslip following the Maduo earthquake, and the preceding interseismic strain accumulation. We devised a 13‐segment 3‐D fault geometry constrained by the SAR range offsets and the distribution of relocated aftershocks and used a Bayesian method incorporating von Karman regularization to solve for coseismic slip and afterslip models. We also used teleseismic waveforms as a standalone inversion to show the rupture evolution in space and time during the earthquake, finding that it propagates bilaterally with three notable rupture episodes. Our preferred coseismic self‐similar slip model shows a moderate shallow slip deficit, with the majority of moment release occurring in the depth interval of 1–10 km. The coseismic slip deficit is taken up in part by afterslip at shallow (<4 km) depths that grows linearly with time during the first ∼6 months, and at >10 km depths where afterslip grows logarithmically with time. We suggest that this heterogeneity is likely controlled by spatial variations in fault friction related to lithology. We discuss the implications for seismic hazard away from major tectonic block boundaries in light of our observations of the earthquake cycle on this intrablock fault. Plain Language Summary: Collision between the Indian and Eurasian plates has created the largest deforming region on the planet. Part of the resultant deformation is accommodated by movements on block‐bounding faults where major earthquakes usually occur. A large earthquake ruptured a slow‐moving fault away from the major pre‐identified block boundaries on 21 May 2021. We used 7 years of satellite radar images to measure the deformation that occurred before, during, and after the earthquake. We also used seismic observations to investigate the temporal evolution of the earthquake rupture. Our model agrees with the results from field mapping. Postseismic deformation at shallow and deep depths shows different temporally varying behavior, which is likely caused by the frictional properties of the fault associated with different physical characteristics of rocks. The causative fault was accumulating relatively subtle strain before the earthquake. We observed the strain being localized on one of the faults in the block interior, highlighting elevated earthquake potential in the future. Key Points: We present the earthquake cycle deformation for the 2021 Maduo earthquake from Sentinel‐1 Interferometric Synthetic Aperture Radar and teleseismic waveformsCoseismic slip deficit is taken up by shallow and deep afterslip with different temporal behavior; this may be controlled by lithologyInterseismic strain observed in the interior of a mapped tectonic block highlights importance of seismic hazard away from block boundaries [ABSTRACT FROM AUTHOR]

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 ± 2,700 Million US dollars (one sigma uncertainty). This highlights the importance of characterizing location, extent, geometry, and activity of small faults beneath cities. Plain Language Summary: Many cities around the world are potentially at risk from earthquakes, due to buried faults that have been hidden by the expansion of the city. Whilst the earthquake hazard and risk due to larger faults is often more widely appreciated, these smaller, subtle faults may potentially be more damaging due to their proximity to the cities, even if the earthquakes that occur on them are much smaller. In this study, we use high‐resolution satellite data to make elevation models across Almaty, Kazakhstan, and identify faults from small changes in the height of the surface. We then simulate the risk to Almaty for a number of specific, defined earthquakes and show the damage (number of buildings with damage) and losses (fatalities and economic cost) for each of these scenarios. We find that a fault to the north of Almaty city could be the most damaging and cause the most losses, because it is close to Almaty and much of the city's building and population is situated directly above the fault at depth. This work shows that knowing the location and shape of faults close to cities is key to understanding seismic hazard and risk. Key Points: Digital elevation models derived from high‐resolution satellite imagery can map active faulting near cities and determine building heightsScenario risk calculations show a moderate earthquake on a fault in north Almaty would cause considerable damage and loss due to proximityProperly characterizing fault location and geometry close to cities is key to quantifying the relative level of seismic hazard and risk [ABSTRACT FROM AUTHOR]