Post-earthquake Satellite Images Research Articles

A GIS-Based emergency response and management support framework for Earthquake crisis: A case study of Antakya and Kahramanmaras earthquake in Turkey

Earthquakes can cause significant damage, including loss of lives, collapsed buildings, and blocked roads. However, the severity and frequency of earthquakes cannot be accurately predicted. To mitigate these effects, successful disaster management, particularly in improving post-earthquake road network connectivity, is crucial. Therefore, this study presents a novel satellite imagery-based approach for identifying post-earthquake road blockage and to assess its impact on urban infrastructure and emergency response management. This study utilised real-world pre- and post-earthquake satellite images of the earthquake that struck Turkey on February 6, 2023 using ArcGIS Pro. The results demonstrated that in the scenario when people in affected areas (incidents) tried to escape to emergency gathering zones, out of the initial 126 incident locations in Antakya, 101 of them experienced alterations in the selected routes after the earthquake. In Kahramanmaras, out of 35 incidents, 28 experienced changes in the selected routes. In the case of emergency vehicles (firefighting, medical aid, etc.) traveling to affected areas, some emergency vehicles were assigned a great number of incidents, whereas some vehicles had no incidents assigned to them. The findings of this study suggest that the developed framework can identify road blockage and inefficiencies in an emergency response framework with high accuracy. Therefore, the approach presented in this paper can be implemented to develop a practical geographic information system (GIS) based model to enhance the emergency response management for potential future earthquakes. Thereby, this study can facilitate the level of resilience of urban environments to withstand and adapt to future crises.

Source Model of the 2023 Turkey Earthquake Sequence Imaged by Sentinel-1 and GPS Measurements: Implications for Heterogeneous Fault Behavior along the East Anatolian Fault Zone

On 6 February 2023, a devastating doublet of earthquakes with magnitudes of Mw 7.8 and Mw 7.6 successively struck southeastern Turkey near the border of Syria. The earthquake sequence represents the strongest earthquakes in Turkey during the past 80 years and caused an extensive loss of life and property. In this study, we processed Sentinel-1 and GPS data to derive the complete surface displacement caused by the earthquake sequence. The surface displacements were adopted to invert for the fault geometry and coseismic slip distribution on the seismogenic faults of the earthquake sequence. The results indicate that the coseismic rupture of the Turkey earthquake sequence was dominated by left-lateral strike slips with a maximum slip of ~10 m on the East Anatolian Fault Zone (EAFZ) and the Sürgü fault (SF). Significant surface ruptures are recognized based on the geodetic inversion, which is consistent with the analysis of post-earthquake satellite images. The cumulative released moment of the two earthquakes reached 9.62 × 1020 Nm, which corresponds to an event of Mw 7.95. Additionally, the interseismic fault slip rates and locking depths along the central and western segments of the EAFZ were estimated using the high-resolution long-term velocity field. The results reveal significant lateral variations of fault slip rates and locking depths along the central and western segments of the EAFZ. Generally, the estimated fault locking zone showed good spatial consistency with the coseismic fault rupture of the Mw 7.8 shock on the EAFZ. The static coulomb failure stress (CFS) change due to the Mw 7.8 earthquakes suggests that the subsequent Mw 7.6 event was certainly promoted by the Mw 7.8 shock. The stress transfers from the fault EAFZ to the fault SF were realized by unclamping the interface of the fault SF, which significantly reduces the effective normal stress on the fault plane. Large CFS increases in the western Puturge segment of the EAFZ, which was not ruptured in the 2020 Mw 6.8 and the 2023 Mw 7.8 earthquakes, highlight the future earthquake risk in this fault segment.

Shortcut Faults and Lateral Spreading Activated in a Pull-Apart Basin by the 2018 Palu Earthquake, Central Sulawesi, Indonesia

Our understanding of pull-apart basins and their fault systems has been enhanced by analog experiments and simulations. However, there has been scarce interest to compare the faults that bound pull-apart basins with surface ruptures during earthquakes. In this study, we investigated the effects of a 2018 earthquake (Mw 7.5) on a pull-apart basin in the Palu–Koro fault system, Sulawesi Island, Indonesia, using geomorphic observations on digital elevation models and optical correlation with pre- and post-earthquake satellite images. A comparison of active fault traces determined by geomorphology with the locations of surface ruptures from the 2018 earthquake shows that some of the boundary faults of the basin are inactive and that active faulting has shifted to basin-shortcut faults and relay ramps. We also report evidence of lateral spreading, in which alluvial fan materials moved around the end of the alluvial fan. These phenomena may provide insights for anticipating the location of future surface ruptures in pull-apart basins.

Intensity estimation for the 2001 Bhuj earthquake, India on ESI-07 scale and comparison with historical 16th June 1819 Allah Bund earthquake: A test of ESI-07 application for intraplate earthquakes

On 26th January 2001, an earthquake of magnitude Mw 7.7 occurred near Bhuj, in northwestern India, resulting in severe environmental effects. No unequivocal primary surface rupture was observed for the earthquake, but it caused widespread liquefaction and lateral spreading in the Rann of Kachchh and Little Rann. After the earthquake, several researchers collected field evidence of secondary surface rupture, rockfall, dry craters, and surface manifestations of liquefaction, including the formation of mud volcanoes and lateral spreads, in the meizoseismal area. Analysis of pre- and post-earthquake satellite images suggests that several “dry” streams in the Rann of Kachchh began to flow due to extensive liquefaction induced by the earthquake. In this present study, the macroseismic intensity of the Bhuj earthquake is evaluated by considering these environmental effects and applying the ESI-07 intensity scale to the affected area. As an outcome, the epicentral intensity of the 2001 Bhuj earthquake was determined to be XI. According to historical records and seismic catalogs, 16th June 1819 Allah Bund earthquake caused prominent surface rupture which was not so clear in the case of 2001 Bhuj earthquake, but the secondary effects were similar for both earthquakes. Considering the environmental effects caused by the 1819 Allah Bund earthquake, an intensity of XI was estimated for the epicentral area. For both earthquakes, the ESI scale yields a significant difference of one to two degrees with the traditional intensity scales. The 2001 Bhuj earthquake and 1819 Allah Bund earthquake shows similar ESI-07 intensity of XI despite of different epicentral locations. This implies the reliability of ESI-07 scale application for different earthquakes of similar dimensions in the same geological setting. This study contributes to the application of ESI-07 scale for Indian earthquakes, especially reverse faulting events, and to the future improvement of the ESI scale with emphasis on its applicability to historical earthquakes on the Indian subcontinent. Also, this study may help in future land use planning in the meizoseismal area of 1919 Allah Bund and 2001 Bhuj earthquakes.

An Artificial Intelligence Application for Post-Earthquake Damage Mapping in Palu, Central Sulawesi, Indonesia.

A Mw 7.4 earthquake hit Donggala County, Central Sulawesi Province, Indonesia, on 28 September 2018, triggering a tsunami and liquefaction in Palu City and Donggala. Around 2101 fatalities ensued and 68,451 houses were damaged by the earthquake. In light of this devastating event, a post-earthquake map is required to establish the first step in the evacuation and mitigation plan. In this study, remote sensing imagery from the Landsat-8 and Sentinel-2 satellites was used. Pre- and post-earthquake satellite images were classified using artificial neural network (ANN) and support vector machine (SVM) classifiers and processed using a decorrelation method to generate the post-earthquake damage map. The affected areas were compared to the field data, the percentage conformity between the ANN and SVM results was analyzed, and four post-earthquake damage maps were generated. Based on the conformity analysis, the Landsat-8 imagery (85.83%) was superior to that of Sentinel-2 (63.88%). The resulting post-earthquake damage map can be used to assess the distribution of seismic damage following the Palu earthquake and may be used to mitigate damage in the event of future earthquakes.

BUILDING DAMAGE EXTRACTION TRIGGERED BY EARTHQUAKE USING THE UAV IMAGERY

Abstract. When extracting building damage information, we can only determine whether the building is collapsed using the post-earthquake satellite images. Even the satellite images have the sub-meter resolution, the identification of slightly damaged buildings is still a challenge. As the complementary data to satellite images, the UAV images have unique advantages, such as stronger flexibility and higher resolution. In this paper, according to the spectral feature of UAV images and the morphological feature of the reconstructed point clouds, the building damage was classified into four levels: basically intact buildings, slightly damaged buildings, partially collapsed buildings and totally collapsed buildings, and give the rules of damage grades. In particular, the slightly damaged buildings are determined using the detected roof-holes. In order to verify the approach, we conduct experimental simulations in the cases of Wenchuan and Ya’an earthquakes. By analyzing the post-earthquake UAV images of the two earthquakes, the building damage was classified into four levels, and the quantitative statistics of the damaged buildings is given in the experiments.

Database and spatial distribution of landslides triggered by the Lushan, China Mw 6.6 earthquake of 20 April 2013

On 20 April 2013, an earthquake with Mw 6.6 (Ms 7.0) hit Lushan County, Sichuan Province of China (30.3°N, 103°E), only 85km southwest of the 2008 Wenchuan Mw 7.9 event. The Lushan shock triggered a large number of landslides with various types, including highly disrupted shallow slides and rock falls, deep-seated landslides and large-scale rock avalanches. Post-earthquake high resolution aerial photographs and satellite images, as well as a series of pre-earthquake high resolution satellite images were collected to construct a detailed, accurate, objective, and complete coseismic landslide database/inventory, which was validated by field investigation in selected areas. Based on the aerial photographs (0.2 or 0.6m resolution) that partly cover the affected area and pre-earthquake satellite images, 14,580 coseismic landslides were recognized and mapped. In those areas without post-earthquake aerial photographs coverage, we mapped 7,948 more coseismic landslides based on post-earthquake satellite images (Rapideye images with 5m resolution and ZY-3 images including panchromatic images with 2.1m resolution and multi-spectral images with 5.8m resolution) and pre-earthquake satellite images. The 22,528 coseismic landslides, with a horizontal projection area of 18.88km2 and an estimated total volume of 41.56×106m3, were distributed in a nearly elliptic area of about 5,400km2. Correlations between coseismic landslide abundances and topographic, geologic, and seismic factors were analyzed on 15,546 landslides of area ≥100m2. Scatter plots between regional slope angle and landslide abundances in generalized homogeneous lithology combinations show no obvious relationship is present between them, which challenges the conclusions of previous studies. Combining the Lushan earthquake-triggered landslides with other events on reverse and/or thrust faults such as the 1999 Chi-Chi and 2008 Wenchuan shocks, we found that coseismic landslides tend to occur in areas enveloped by two or more imbricated reverse and/or thrust faults, rather than only along the seismogenic fault. The Lushan event shows a higher ability of triggering landslides compared with other earthquakes of similar magnitudes, which is likely due to the steep and rugged topography and fractured and densely jointed lithology resulted from long-term tectonic activity. The blind reverse seismogenic fault is likely also another significant factor. Based on detailed coseismic landslide inventory maps and databases of several recent major earthquakes such as the 2008 Wenchuan, 2010 Haiti, 2010 Yushu, and 2013 Lushan temblors, we suggest that the empirical correlations between earthquake magnitude and coseismic landslides need to be updated.

The role of national and international geospatial data sources in the management of natural disasters

Abstract. An earthquake occurred at Van City on 23 October 2011 at 13:41 local time. The magnitude, moment magnitude and depth of earthquake were respectively MI:6.7, Mw:7.0 and 19.07 km. Van city centre and its surrounding villages were affected from this destructive earthquake. Many buildings were ruined and approximately 600 people died. Acquisition and use of geospatial data is very important and crucial for the management of such kind of natural disasters. In this paper, the role of national and international geospatial data in the management of Van earthquake is investigated.. With an international collaboration with Charter, pre and post-earthquake satellite images were acquired in 24 hours following the Earthquake. Also General Command of Mapping (GCM), the national mapping agency of Turkey, produced the high resolution multispectral orthophotos of the region. Charter presented the orthophotos through 26–28 October 2012. Just after the earthquake with a quick reaction, GCM made the flight planning of the 1296 km2 disaster area to acquire aerial photos. The aerial photos were acquired on 24 October 2012 (one day after the earthquake) by UltraCamX large format digital aerial camera. 152 images were taken with 30 cm ground sample distance (GSD) by %30 sidelap and %60 overlap. In the evening of same flight day, orthophotos were produced without ground control points by direct georeferencing and GCM supplied the orthophotos to the disaster management authorities. Also 45 cm GSD archive orthophotos, acquired in 2010, were used as a reference in order to find out the effects of the disaster. The subjects written here do not represent the ideas of Turkish Armed Forces.

Documenting Earthquake-Induced Liquefaction Using Satellite Remote Sensing Image Transformations

Research Article| November 01, 2013 Documenting Earthquake-Induced Liquefaction Using Satellite Remote Sensing Image Transformations Thomas Oommen; Thomas Oommen Department of Geological Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931 1Corresponding author: phone: 906-487-2045, fax: 906-487-3371, email: toommen@mtu.edu. Search for other works by this author on: GSW Google Scholar Laurie G. Baise; Laurie G. Baise Department of Civil and Environmental Engineering, Tufts University, Medford MA 02155 Search for other works by this author on: GSW Google Scholar Rudiger Gens; Rudiger Gens Alaska Satellite Facility, Geophysical Institute, University of Alaska–Fairbanks, Fairbanks, AK 99775 Search for other works by this author on: GSW Google Scholar Anupma Prakash; Anupma Prakash Geophysical Institute, University of Alaska–Fairbanks, Fairbanks, AK 99775 Search for other works by this author on: GSW Google Scholar Ravi P. Gupta Ravi P. Gupta Department of Earth Sciences, Indian Institute of Technology, Roorkee 247667, India Search for other works by this author on: GSW Google Scholar Environmental and Engineering Geoscience (2013) 19 (4): 303–318. https://doi.org/10.2113/gseegeosci.19.4.303 Article history first online: 02 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Search Site Citation Thomas Oommen, Laurie G. Baise, Rudiger Gens, Anupma Prakash, Ravi P. Gupta; Documenting Earthquake-Induced Liquefaction Using Satellite Remote Sensing Image Transformations. Environmental and Engineering Geoscience 2013;; 19 (4): 303–318. doi: https://doi.org/10.2113/gseegeosci.19.4.303 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentBy SocietyEnvironmental and Engineering Geoscience Search Advanced Search Abstract Documenting earthquake-induced liquefaction effects is important to validate empirical liquefaction susceptibility models and to enhance our understanding of the liquefaction process. Currently, after an earthquake, field-based mapping of liquefaction can be sporadic and limited due to inaccessibility and lack of resources. Alternatively, researchers have used change detection with remotely sensed pre- and post-earthquake satellite images to map earthquake-induced effects. We hypothesize that as liquefaction occurs in saturated granular soils due to an increase in pore pressure, liquefaction-induced surface changes should be associated with increased moisture, and spectral bands/transformations that are sensitive to soil moisture can be used to identify these areas. We verify our hypothesis using change detection with pre- and post-earthquake thermal and tasseled cap wetness images derived from available Landsat 7 Enhanced Thematic Mapper Plus (ETM+) for the 2001 Bhuj earthquake in India. The tasseled cap wetness image is directly related to the soil moisture content, whereas the thermal image is inversely related to it. The change detection of the tasseled cap transform wetness image helped to delineate earthquake-induced liquefaction areas that corroborated well with previous studies. The extent of liquefaction varied within and between geomorphological units, which we believe can be attributed to differences in the soil moisture retention capacity within and between the geomorphological units. You do not currently have access to this article.

Automated Hazard Assessment Techniques Using Satellite Images Following the 2008 Sichuan China Earthquake

ABSTRACT Rapid seismic hazard assessment is crucial for accurate damage estimation right after earthquakes. New technologies provide faster damage detection compared to the traditional, manual assessments. One of the new technologies includes using satellite images. Pre- and post-earthquake satellite images can be used to identify damage patterns. One of the recent disastrous earthquakes occurred in Sichuan (Mw = 7.9) on May 12, 2008. Records show that 5 million buildings have collapsed, and more than 21 million buildings were damaged. This article presents an approach for earthquake hazard assessment using a change detection method applied to pre- and post-earthquake satellite imagery of Sichuan. The damage inspection for the identified areas was carried out performing image analysis of the pre- and post-event satellite images. In this study, a novel automated image analysis technique was developed to assess the impact of the earthquake on the flooding of the area's rivers as well as the tectonic movement of mountains. The technique was used to quantify the flooding and movement of mountains in Sichuan right after the earthquake. The proposed methodology utilizes satellite images and may potentially be used as a rapid procedure to quantify damage soon after an earthquake.

Constraints on the Source Parameters of the 26 January 2001 Bhuj, India, Earthquake from Satellite Images

The Bhuj earthquake of 26 January 2001 (M w 7.6) was the largest in- tracontinental earthquake of the modern era of seismology. Field investigations did not provide any evidence of coseismic surface rupture or ground deformation due to primary faulting. We analyze pre- and postearthquake satellite images of the epicen- tral region to suggest that there was a significant change in the flooding pattern of the seasonal Rann of Kachchh lagoon after the 2001 and 2002 monsoons in the region of coseismic uplift. The maximum uplift is located about 15 km north of the reported epicenter and acted as a barrier against the northward draining rainwater runoff. Furthermore, the earthquake caused a northward shift in the southern limit of the Rann of Kachchh. We use this information to place constraints on the location and geometry of the earthquake rupture and suggest that the depth of the updip edge of the rupture is about 10 km.

Damage assessment after 2001 Gujarat earthquake using Landsat-7 satellite images

In this paper, we present a method of earthquake damage detection by comparing the optical images with panchromatic bands for the Gujarat, India earthquake, which occurred on January 26, 2001. The data used in this study are optical remote sensing images taken by Landsat-7 satellite on January 8 and February 29, 2001, before and after the earthquake. We have investigated the pre and post-earthquake satellite images calculating the differences in the reflection intensity (digital number) of the two images. The estimated affected area has been subtracted on a pixel unit based on the obtained frequency distributions of the differences in the optical sensor values, which show significant changes in the reflectance due to the earthquake disaster. We have investigated the accuracy of our analysis result using a classification method for the training areas with aerial photographs taken after the earthquake. The two damage detection methods show a very similar result.