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While unprecedented amounts of building damage data are now produced after earthquakes, stakeholders do not have a systematic method to synthesize and evaluate damage information, thus leaving many datasets unused. We propose a Geospatial Data Integration Framework (G-DIF) that employs regression kriging to combine a sparse sample of accurate field surveys with spatially exhaustive, though uncertain, damage data from forecasts or remote sensing. The framework can be implemented after an earthquake to produce a spatially distributed estimate of damage and, importantly, its uncertainty. An example application with real data collected after the 2015 Nepal earthquake illustrates how regression kriging can combine a diversity of datasets—and downweight uninformative sources—reflecting its ability to accommodate context-specific variations in data type and quality. Through a sensitivity analysis on the number of field surveys, we demonstrate that with only a few surveys, this method can provide more accurate results than a standard engineering forecast.

Shaking from the 6 July 2019 Mw 7.1 Ridgecrest, California, mainshock was strongly felt through southern California, but generated relatively minimal structural damage in Ridgecrest. We consider the extent to which a damage proxy map (DPM) generated from satellite-based Synthetic Aperture Radar images can detect minor damage throughout the town of Ridgecrest. The DPM does not, as expected, detect all minor structural damage to individual structures, nor can it distinguish between structural damage and earthquake-related movement that is not consequential. However, the DPM does confirm many instances of minor structural damage to larger structures and groups of smaller structures and in some instances suggests minor structural damage that is not apparent upon visual inspection. Although ambiguous identification of minor damage may not be useful to guide earthquake response, the identification of minor, possibly hidden damage is potentially useful for other purposes. Overall, the DPM confirms that structural damage was commensurate with modified Mercalli intensity no higher than 7 throughout Ridgecrest. We consider both instrumental and intensity data to explore further the distribution of near-field ground motions over the frequency range of engineering concern. Peak ground accelerations and peak ground velocities estimated from “Did You Feel It?” intensity data using the Worden et al. (2012) ground-motion intensity conversion equation (GMICE) are consistent with recorded instrumental data. Both instrumental and estimated mainshock peak accelerations are further consistent with predictions from both the Boore et al. (2014) ground-motion prediction equation (GMPE), but lower than predicted by the Atkinson and Wald (2007) and Atkinson et al. (2014) intensity prediction equations (IPEs). A GMPE such as Boore et al. (2014), which is constrained by a large global dataset, together with a well-constrained GMICE, may thus characterize expected shaking intensities for large earthquakes better than an IPE based on more limited intensity data.

A series of four Mw>6 earthquakes struck the northern region of Lombok, eastern Indonesia, in a span of three weeks from late July to mid-August 2018. The series was thought to be associated with the Flores thrust, but the exact mechanism causing the unusual earthquake series has remained elusive. Our Interferometric Synthetic Aperture Radar analysis, combined with insights from seismology, indicates that the events originated at different hypocenter depths with differing fault geometries, which may explain the cascading behavior of the events, and indicates that better imaging of active fault geometry might provide some insight into future rupture behavior on other similar thrust systems. Our static stress change calculations suggest that the earlier events in the sequence played a role in promoting the later events. In addition, the second event brought the most significant impact on a nearby volcano, by causing volumetric expansion at its shallow magma plumbing system and unclamping its magma ascent zone, which may potentially have an impact on its future eruptive activity. However, no volcanic activity has so far occurred after the earthquakes. Finally, our damage proxy maps suggest that the second event caused the greatest damage to buildings.

The death toll and economic impact of an earthquake can be greatly exacerbated if seismic ground shaking triggers landslides. Earthquake-triggered landslides typically occur in two different contexts: localized failure of steep slopes and resulting landslides that pose a major threat to life in areas below; and lateral spreading of nearly flat sediment plains due to shaking-induced liquefaction, which can damage large areas of critical infrastructure. Unexpected catastrophic landsliding triggered by the 28 September 2018 earthquake at Palu, Indonesia did not occur in either typical context, but produced both destructive outcomes. Here, we show that alluvial ground failure in the Palu Valley was a direct consequence of irrigation creating a new liquefaction hazard. Aqueduct-supported cultivation, primarily of wet rice, raised the water table to near ground level, saturating sandy alluvial soils that liquefied in response to strong ground shaking. Large-displacement lateral spreads occurred on slopes of 1°. Slopes steeper than 1.5° sourced long-runout landslides and debris flows that swept through villages occupying the gentler slopes below. The resulting damage and loss of life would probably not have occurred in the absence of a raised water table. Earthquake-triggered landsliding of gentle, irrigated alluvial slopes is an under-recognized, but avoidable, anthropogenic hazard. Aqueduct-supported cultivation of rice resulted in liquefaction of the alluvial soils that led to the landslides triggered by the Palu 2018 earthquake, according to satellite analyses.

Intensive wildfire is one of the catastrophic hazards threatening human life and the economy. In this study, we aim to detect building damage caused by the Camp Fire, which occurred in Paradise, California in 2018. We use multitemporal coherence based on C-band Sentinel-1 (SAR) and normalized burn ratio based on Sentinel-2 (multispectral) imagery. The results revealed that the multi-temporal coherence approach has the promising capability to map building damage but is not as accurate for detecting building damage under a vegetation canopy. Meanwhile, the normalized burn ratio (NBR) still provides meaningful damage maps independent of the canopy, however, the accuracy was slightly lower than the multi-temporal coherence approach for the buildings not covered by the canopy. Nonetheless, we observed that the multi-temporal coherence methods better classified the damage severity than the NBR method. Both methods can playa complementary role in responding to wildfire depending on the characteristics of the land cover.

We analyzed Synthetic Aperture Radar (SAR) images from Copernicus Sentinel-1A and 1B satellites operated by the European Space Agency and the Advanced Land Observation Satellite-2 (ALOS-2) satellite operated by the Japan Aerospace Exploration Agency and Global Navigation Satellite System (GNSS) data from the Network of the Americas for the 4 July 2019 Mw 6.4 and 5 July (local; 6 July UTC) Mw 7.1 Ridgecrest earthquakes. We integrated geodetic measurements for the 3D vector field of coseismic surface deformation for the two events, using SAR data from Sentinel-1 and ALOS-2 satellites. We combined less precise large-scale displacements from SAR images by pixel offset tracking or matching, including the along-track component, with the more precise SAR interferometry (Interferometric Synthetic Aperture Radar [InSAR]) measurements in the radar line of sight (LoS) direction and intermediate-precision along-track InSAR to estimate all three components of the surface displacement for the two events together. We also estimated the coseismic deformation for the two earthquakes from time-series processing of continuous Global Navigation Satellite System data stations in the area. InSAR coherence and coherence change maps the surface disruptions due to fault ruptures reaching the surface. Large slip in the Mw 6.4 earthquake was on a NE-striking fault that intersects with the NW-striking fault that was the main rupture in the Mw 7.1 earthquake. The main fault bifurcates towards the southeast ending 3 km from the Garlock Fault. The Garlock fault had triggered slip of about 20 mm in the radar LoS along a short section directly south of the main rupture. About 3 km northwest of the Mw 7.1 epicenter, the surface fault separates into two strands that form a pull-apart with about 1 m of down-drop. Further northwest is a wide zone of complex deformation.

Damage mapping using Synthetic Aperture Radar (SAR) imagery has been studied in recent decades to support rapid response to natural disasters. Many researches have been developing coherent and incoherent change detection. However, their performances can vary depending on the types of the damages, the characteristics of the scatterers and the corresponding capability of algorithms. In particular, the coherence-based methods have been used as promising detectors over urban areas where high coherences are observed, but their detection accuracies still remain controversial over the area where low coherences are mainly observed such as the 2018 Hokkaido landslides. In order to understand the characteristics of landslide (damage) detectors for low-coherence areas and find an alternative and complementary method, we designed the coherence difference, coherence normalized difference, log-ratio, intensity correlation difference, and normalized differences of the intensity correlation assuming limited availability of dataset, and also developed multi-temporal algorithms using the coherence, intensity, and intensity correlation. They were tested and evaluated using multiple polygons extracted from aerial photos. We were able to observe that the multi-temporal intensity correlation method has the potential to detect the landslides over the low coherence region and all types of land uses.

Sudden breaching of a saddle dam on July 23, 2018, on the perimeter of the Xe Nammoy hydroelectric-power reservoir, recently constructed in the Mekong basin, southern Laos, caused catastrophic flooding that resulted in fatalities and displaced thousands of individuals. This study aims to (1) assess the cause of the dam breach, and (2) understand the hydrologic and geomorphic impact of the flood. Our analysis shows that the collapse of the dam occurred as the reservoir was nearly full, and the water level was rising against the inner slope of the earthen dam. As the water discharged through the breach, we calculate that the reservoir fell ~22 m and lost ~350 million m3, more than a third of the total stored volume on July 23. Inspection of publicly available photographs of the failed dam confirms our interpretation that the failure was structural, involving both piping and rotational slumping, and not due to overtopping of the dam. Failure to properly process the local materials before construction of the earth-core of the dam is the likely cause of failure. Our analysis of satellite imagery, bolstered by field observations, reveals that the flooding inundated an area of ~46 km2 of villages and rural land in the Vang Ngao River, a tributary of the Mekong River basin. By using 1D and 2D hydrological modeling, we calculate a peak flood discharge of ~8500 m3/s, about half the mean discharge of the Mississippi River. The dam failure and concomitant losses are consistent with common inadequacies in this region in assessing potential hazards, challenges of geomorphological-geotechnical engineering when using tropical materials for construction, and emergency planning and warning. Thus, this analysis has important implications for the safer design and construction of the myriad of other dams that are either operating or planned within the multi-national Mekong River basin. We acknowledge ASF and NASA for providing Sentinel-1 imagery and GPM data, respectively. Part of the research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. EP would like to acknowledge support by the SUG-NAP (3/19) by National Institute of Education at NTU. We thank Lum Shawn Kaihekulani Yamauchi for the botanical identifications, Pavel Adamek for his assistance with the manuscript style, and Abang M.S. Nugraha for his assistance in XRD analyses. We thank Thomas Dunne for his suggestions at the early stages of this research. We specially thanks MoE and NRF for their sustained support to the Earth Observatory of Singapore-EOS. We thank as well two anonymous reviewers and Editor Zhongyuan Chen for their critical reviews and suggestions.

This paper presents a new damage-mapping algorithm based on coherence images estimated from multitemporal polarimetric–interferometric synthetic aperture radar (SAR) data. The interferometric coherence has been restricted in the conventional damage-mapping approaches because the decorrelation sources are too complicated to interpret accurately and temporal decorrelation effects caused by slowly occurring natural changes and disaster events are often coupled together. To overcome these limitations, we formulate a coherence model that accounts for temporal decorrelation in two simplified layers, ground and volume layers, for long-temporal repeat-pass scenarios with zero spatial baseline. The model parameters include: 1) ground-to-volume ratio, a factor to determine the relative scattering contribution of ground and volume layers; 2) temporally correlated change, which captures the exponentially decaying behavior of coherence with time; and 3) temporally uncorrelated change, which is associated with random temporal changes. We estimate the model parameters in three steps: coherence optimization, interferometric pair-invariant parameter estimation, and interferometric pair-variant parameter estimation. To isolate the effects of disaster events from background natural changes, we calculate the probability density functions of historical change pixel by pixel and produce a probability map of damage. We tested the algorithm with uninhabited aerial vehicle data acquired from 2009 to 2015 for mapping the area damaged by the 2015 Lake Fire in California. Based on performance evaluation using receiver operating characteristic curves for optimized coherences and averaged probability maps, the proposed method reduced the false alarm from 0.25 to 0.07 when the probability of detection was 0.85 compared to coherence products alone.

We developed a terpyridine-functionalized microgel (tpy-mG) for its supramolecular assembly. Tpy-mG was synthesized by amidation between 3-(4-([2,2':6',2 ''-terpyridin]-4'-yl)phenoxy) propan-1-amin ...

Detection of weak volcano deformation helps constrain characteristics of eruption cycles. We have developed a signal detection technique, called the Targeted Projection Operator (TPO), to monitor surface deformation with Global Positioning System (GPS) data. We have applied the TPO to GPS data collected at Akutan volcano from June 2005 to March 2017 and detected four inflation events that occurred in 2008, 2011, 2014 and 2016 with inflation rates of about 8~22 mm/yr above the background trend at a near-source site AV13. Numerical modeling suggests that the events should be driven by closely located sources or a single source in a shallow magma chamber at a depth of about 4 km. The inflation events suggest that magma has episodically accumulated in a shallow magma chamber.

During the aftermath of Typhoon Hagibis, we made flood and damage proxy maps, rapidly derived from synthetic aperture radar (SAR) data using change detection approaches. The maps have large spatial coverage over the Tokyo, Fukushima, Ibaraki, Iwate, and Nagano prefectures of Japan. The maps are also largely in agreement with various validation sources including aerial imagery, optical imagery and news sources. Apart from visual maps, we provide flood and damage extents in various formats compatible with geographic information system (GIS) applications. The data may potentially be used for applications such as typhoon risk modelling, investigating spatial correlations of typhoon impacts, and comparing alternative flood or damage mapping techniques., Measurement(s)damage • floodTechnology Type(s)synthetic aperture radarFactor Type(s)geographic locationSample Characteristic - EnvironmentcycloneSample Characteristic - LocationJapan Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11968443

In this study we explored the application of synthetic aperture radar (SAR) intensity time series for urban flood detection. Our test case was the flood in Lumberton, North Carolina, USA, caused by the landfall of Hurricane Matthew on 8 October 2016, for which airborne imagery—taken on the same day as the SAR overpass—is available for validation of our technique. To map the flood, we first carried out normalization of the SAR intensity observations, based on the statistics from the time series, and then construct a Bayesian probability function for intensity decrease (due to specular reflection of the signal) and intensity increase (due to double bounce) cases separately. We then formed a flood probability map, which we used to create our preferred flood extent map using a global cutoff probability of 0.5. Our flood map in the urban area showed a complicated mosaicking pattern of pixels showing SAR intensity decrease, pixels showing intensity increase, and pixels without significant intensity changes. Our approach shows improved performance when compared with global thresholding on log intensity ratios, as the time series-based normalization has accounted for a certain level of spatial variation by considering the different history for each pixel. This resulted in improved performance for urban and vegetated regions. We identified smooth surfaces, like asphalt roads, and SAR shadows as the major sources of underprediction, and aquatic plants and soil moisture changes were the major sources of overprediction. NRF (Natl Research Foundation, S’pore) MOE (Min. of Education, S’pore) Published version

The kinematics of rift segment linkage in magmatic rifts remain debated. Strain patterns from Afar provide tests of current models of how segmented rifts grow in areas of incipient oceanic spreading. Here, we present a combined analysis of seismicity, interferometric synthetic aperture radar (InSAR), and GPS–derived strain rate maps to reveal that the plate-boundary linkage between the Red Sea and Gulf of Aden rifts of Afar is accommodated primarily by distributed extensional faulting. Large rotations about vertical axes predicted by bookshelf faulting models are not detected. Additionally, models of stress changes and seismicity induced by recent dikes provide poor fits to the observed time-space patterns of strike-slip earthquakes. Instead, we explain these features as resulting from rift-perpendicular shearing at the tips of spreading rifts where extension terminates against less stretched lithosphere. Our results demonstrate that distributed extension drives rift-perpendicular shearing, achieving plate-boundary linkage during incipient seafloor spreading.

Detection of changes caused by major events-such as earthquakes, volcanic eruptions, and floods-from interferometric synthetic aperture radar (SAR) data is challenging because of the coupled effects with temporal decorrelation caused by natural phenomena, including rain, snow, wind, and seasonal changes. The coupled effect of major events and natural phenomena sometimes leads to misinterpretation of interferometric coherence maps and often degrades the performance of change detection algorithms. To differentiate decorrelation sources caused by natural changes from those caused by an event of interest, we formulated a temporal decorrelation model that accounts for the random motion of canopy elements, temporally correlated dielectric changes, and temporally uncorrelated dielectric changes of canopy and ground. The model parameters are extracted from the interferometric pairs associated with natural changes in canopy and ground using the proposed temporal decorrelation model. In addition, the cumulative distribution functions of the temporally uncorrelated model parameters, which are associated with natural changes in canopy and ground, are estimated from interferometric pairs acquired before the event. Model parameters are also extracted from interferometric SAR data acquired across the event and compared with the cumulative probabilities of natural changes in order to calculate the probability of a major event. Subsequently, pixels with cumulative probabilities greater than 75% are marked as changed due to the event. A case study for detecting volcanic ash during the eruption of the Shinmoedake volcano in January 2011 was carried out using L-band Advanced Land Observation Satellite PALSAR data.

Shallow dike intrusions may be accompanied by fault slip above the dikes, a superposition which complicates seismic and geodetic data analyses. The diverse volcano-tectonic and low-frequency local earthquakes accompanying the 2005-2010 large-volume dike intrusions in the Dabbahu-Manda Hararo rift (Afar), some with fault displacements of up to 3m at the surface, provide an opportunity to examine the relations among the earthquakes, dike intrusions, and surface ruptures. We apply the frequency index (FI) method to characterize the spectra of swarm earthquakes from six of the dikes. These earthquakes often have broad spectra with multiple peaks, making the usual peak frequency classification method unreliable. Our results show a general bimodal character with high FI earthquakes associated with deeper dikes (top 3 km subsurface) and low FI earthquakes associated with shallow dikes, indicating that shallow dikes result in earthquakes with more low-frequency content and larger-amplitude surface waves. Low FI earthquakes are more common during dike emplacement, suggesting that interactions between the dike and faults may lead to lower FI. Taken together, likely source processes for low FI earthquakes are shallow hypocenters ( 3 km) possibly with surface rupture, slow rupture velocities, and interactions with dike fluids. Strong site effects also heavily influence the earthquake spectral content. Additionally, our results suggest a continuum of spectral responses, implying either that impulsive volcano-tectonic earthquakes and the unusual, emergent earthquakes have similar source processes or that simple spectral analyses, such as FI, cannot distinguish different source processes.

Several current and expected future SAR satellites missions (e.g., TanDEM-X (TDX)/PAZ, COSMO-SkyMed (CSK), and Sentinel-1A/B) are designed as constellations of SAR sensors. Relative to single satellite systems, such constellations can provide greater spatial coverage and temporal sampling, thereby enabling better control on interferometric decorrelation and lower latency data access. These improvements lead to more effective near real-time disaster monitoring, assessment and response, and a greater ability to constrain dynamically changing physical processes. Using observations from the CSK system, we highlight examples of the potential for such imaging capabilities to enable advances in Earth science and natural hazards response.

Change detection using synthetic aperture radar (SAR) data is useful in emergency situations and unfavorable weather conditions. In this letter, change detection using multitemporal polarimetric Uninhabited Aerial Vehicle SAR data is investigated in an urban environment. The most robust polarimetric parameters are determined, and change detection techniques using a maximum likelihood ratio and a hyperbolic tangent model function are applied to the selected parameter. The model function was introduced to quantify the change characteristics and to rule out seasonal changes or those related to mobile features, and thus to only detect durable and permanent changes in urban environments. A comparison of results with historical Google Earth images showed a good level of agreement. Fitting of the hyperbolic tangent function to the multitemporal polarimetric parameters significantly reduces the false detection rate and indicates whether a building was constructed or destroyed, as well as when the detected changes occurred.

The Great 2011 Thailand flood is one of the most catastrophic flood disasters recorded worldwide in modern history, which covered about 100,000 km2 of the country and resulted in 813 casualties and incurring US$ 46 billion in economic losses. In this paper, we re-evaluate the flood event to identify the root source of the catastrophe. By analyzing hydrological data from gauge stations along the Chao Phraya River (CPR) and remote sensing data, we decoupled the volumetric contributions of river overflow and local rainfall to the lowland reach of the basin and found that the latter contributed most to the flooding. More specifically, out of the total of 77.6 km3 of floodwaters estimated, 73.7% was from precipitation, while only 26.3% was from river discharges. This finding differs from the official reports or previous studies, which attributed the main cause of the river overbank flow. Therefore, it is also inferred that the upstream dam operations would have been only marginally helpful in mitigating the flood since rainfall made up most of the floodwaters in the downstream reach of the river. Our finding offers a new perspective that the local rainfall could be a significant source of the floodwater, rather than river overflow in the lower reaches of a large monsoonal river system in Southeast Asia. Thus, this paper contributes to the understanding of complex flood processes in large river basins and provides fresh insights for efficient flood control and stormwater management.

This study aims to monitor the deformation of bridges, namely in the form of long-term deflection and thermal dilation, using multi-temporal interferometric synthetic aperture radar (InSAR) observations. To precisely estimate the vertical and longitudinal displacements, we used the InSAR time-series technique with multi-track stacks of Sentinel-1 SAR dataset and a single-track stack of COSMO-SkyMed SAR data over two extradosed bridge cases; Kimdaejung and Muyoung bridges between 2013 and 2017. The vertical and longitudinal displacements are estimated using multi-track Sentinel-1 SAR data and orientation angle of bridges, and we converted the displacements into thermal dilation and long-term vertical deflection. From COSMO-SkyMed data, we calculated the horizontal thermal dilation and long-term vertical deflection assuming that they dominantly contribute to the horizontal and vertical displacements, respectively. This assumption appeared reasonable based on the comparison with calculations from Sentinel-1 data. The deflection patterns exhibit downward movements at the mid-spans between towers. The results reveal that both bridges have been suffering long-term deflection over the observation period. Thus, this study verifies the potential to monitor the long-term deflection and implies that the bridges need to be monitored periodically.

We reconstructed the three-dimensional (3D) surface displacement field of the 24 August 2014 M6.0 South Napa earthquake using SAR data from the Italian Space Agency’s COSMO-SkyMed and the European Space Agency’s Sentinel-1A satellites. Along-track and cross-track displacements produced with conventional SAR interferometry (InSAR) and multiple-aperture SAR interferometry (MAI) techniques were integrated to retrieve the east, north, and up components of surface deformation. The resulting 3D displacement maps clearly delineated the right-lateral shear motion of the fault rupture with a maximum surface displacement of approximately 45 cm along the fault’s strike, showing the east and north components of the trace particularly clearly. These maps also suggested a better-constrained model for the South Napa earthquake. We determined a strike of approximately 338° and dip of 85° by applying the Okada dislocation model considering a single patch with a homogeneous slip motion. Using the distributed slip model obtained by a linear solution, we estimated that a peak slip of approximately 1.7 m occurred around 4 km depth from the surface. 3D modelling using the retrieved 3D maps helps clarify the fault’s nature and thus characterize its behaviour.

Detection of changes induced by major events such as earthquakes, flooding and volcanic eruptions from interferometric SAR data is difficult due to the coupled effects with temporal decorrelation caused by natural phenomena such as rain, snow, wind and seasonal changes. In this study, we aim to separate the decorrelation caused by natural changes from the one caused by the major event by analyzing the coherence behavior using a temporal decorrelation model. We formulated the temporal decorrelation model that accounts for the random motion and dielectric changes. By applying the model into the multi-temporal coherence before the event, we extracted the temporal decorrelation components induced by natural phenomena. Based on the extracted parameters, their decorrelation probabilities related to natural changes were estimated in canopy and ground. The model parameters are also extracted from the interferometric SAR data acquired across the event. We compared probabilities between the natural phenomena and the certain event in order to assign the changed regions. Pixels with cumulative probabilities greater than 80% are selected as changed due to the event. A case study for detecting volcanic ash during the eruption of the Shinmoedake volcano in January 2011 was carried out using L-band Advanced Land Observation Satellite (ALOS) PALSAR data.

ZnO nanowires (NWs) would provide significant enhancement in sensitivity due to high surface to volume ratio. We investigated the first methodical study on the quantitative relationship between the process parameters of solution concentration ratio, structure, and physical and properties of ZnO NWs grown on different flexible fabric surfaces. To develop a fundamental following concerning various substrates, we controlled the growth speed of ZnO NWs and nanowires on cotton surface with easy and moderate cost fabrication method. Using ammonium hydroxide as the reactant with zinc nitrate hexahydrate, ZnO NWs layer have been grown on metal layers, instead of seed layer. ZnO NWs fabrication was done on different fabric substrates such as wool, nylon and polypropylene (PP). After the ZnO NWs grown to each substrates, we coated insulating layer with polyurethane (PU) and ethyl cellulose for prevent external intervention. Detailed electrical characterization was subsequently performed to reveal the working characteristics of the hybrid fabric. For electrical verification of fabricated ZnO NWs, we implemented measurement impact test and material properties with FFT analyzer and LCR meter.