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Earthquakes and Volcanoes Data Pathfinder

An unexpected series of blasts from a remote volcano in the Kuril Islands sent ash and volcanic gases streaming high over the North Pacific Ocean, June 22, 2019.

An unexpected series of blasts from a remote volcano in the Kuril Islands sent ash and volcanic gases streaming high over the North Pacific Ocean, June 22, 2019. Credit NASA Earth Observatory

While earthquakes are only the third most common disaster, they kill the greatest number of people. Earthquakes cannot be accurately predicted, yet scientists and decision makers can still seek to understand relative fault activity, earthquake likelihood, population vulnerability, exposure, and risk to aid in response and relief.

Volcanic eruptions are less frequent and rarely kill people, as there are natural warnings leading up to eruptions allowing for the evacuation of people in threatened areas; however, volcanoes can still have tremendous impacts locally, regionally and even globally.

In addition to the datasets below, NASA has several other projects that may have earthquake- and volcano-related data or tools. View the Other NASA Assets section to find out more.

Find Socioeconomic Data

Find Socioeconomic Data

Multihazard risks calculated by summing the vulnerability-weighted single-hazard Total Economic Loss risk values for each grid cell across the six hazard types: cyclones, drought, earthquakes, floods, landslides, and volcanoes.

Multihazard risks calculated by summing the vulnerability-weighted single-hazard Total Economic Loss risk values for each grid cell across the six hazard types: cyclones, drought, earthquakes, floods, landslides, and volcanoes. Credit: Socioeconomic Data and Applications Center (SEDAC)

The Socioeconomic Data and Applications Center (SEDAC) provides a number of datasets on population exposure, vulnerability and risk, and earthquake hazard potential.



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Find Disaster Response Data

Find Disaster Response Data

Advanced Rapid Imaging and Analysis (ARIA) Damage Proxy Map (DPM) depicting areas that are likely damaged caused by the 2020 Zagreb Earthquake. The map was derived from synthetic aperture radar (SAR) images from the Copernicus Sentinel-1 satellites, operated by the European Space Agency (ESA). The team compared the post-event image acquired on March 23, 2020 with pre-event images taken since January 2020.
Advanced Rapid Imaging and Analysis (ARIA) Damage Proxy Map (DPM) depicting areas that are likely damaged caused by the 2020 Zagreb Earthquake. The map was derived from synthetic aperture radar (SAR) images from the Copernicus Sentinel-1 satellites, operated by the European Space Agency (ESA). The team compared the post-event image acquired on March 23, 2020 with pre-event images taken since January 2020. Credit: NASA and the California Institute of Technology
Geodetic imaging's unique ability to capture surface deformation caused by earthquakes and subsurface magma movement in high spatial and temporal resolution has revolutionized both earthquake science and volcanology. The Advanced Rapid Imaging and Analysis (ARIA) project is using this information to bring geodetic imaging capabilities to an operational level in support of local, national, and international hazard science and response communities. The products are crafted specifically for an event.

GeoGateway makes it possible for non-expert users of geodetic imaging to overlay multiple types of data and rapidly analyze airborne radar products from the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). Custom products are also posted for some disasters, such as for the Ridgecrest earthquake sequence.

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the Terra and Aqua satellites and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the joint NASA/NOAA Suomi-National Polar-orbiting Partnership (Suomi NPP) satellite and onboard the NASA/NOAA Joint Polar Satellite System (JPSS) NOAA-20 satellite provide satellite-derived information on hotspots/fires and thermal anomalies, as well as smoke plume movement via true color reflectance imagery.

Land surface reflectance can be used to monitor and measure thick plumes of ash and steam and flows of molten lava. This is important in assessing how ash plumes might affect aviation routes and air quality and how lava flows might impact surrounding infrastructure.

Near real-time (NRT) data can be accessed via Worldview. Corrected reflectance imagery is only available as NRT data, as the processing algorithms provide natural-looking images by removing gross atmospheric effects, such as Rayleigh scattering.

Lava flows can be detected with both MODIS and VIIRS thermal anomalies datasets.

Research quality, or higher-level "standard" data products can be accessed via the Earthdata Search.

Note, the thermal anomalies/fire NRT data, available in Worldview, are basically a snapshot in time, showing what is occurring at the moment the data was acquired. It is determined by a contextual algorithm that utilizes the infrared or thermal radiation of the fires. Each MODIS active fire represents the center of a 1km pixel that is flagged by the algorithm as containing one or more fires within the pixel. Because VIIRS has a higher resolution, it can pick up fires that MODIS overlooks, especially those in relatively small areas. It is important to note that the NRT products are not considered standard science quality because predicted geolocation is used.

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Find Volcanic Aerosols Data

Find Volcanic Aerosols Data

Nishinoshima Volcano, off the coast of Japan, emits a plume of sulfur dioxide as it erupts, July 3, 2020. Data are from the Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI).

Nishinoshima Volcano, off the coast of Japan, emits a plume of sulfur dioxide as it erupts, July 3, 2020. Data are from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI). Credit: NASA

The dispersal of aerosols such as sulfur dioxide preceding and during an event can have not only an immediate but also a long-term effect on the atmosphere. For example, in 1991 during the eruption of Mount Pinatubo in the Philippines, so much sulfur dioxide (SO2) was released that it set off a period of global cooling for several years. The aerosols released in the eruption reflected sunlight, reducing the amount of energy reaching the lower atmosphere and the Earth's surface, cooling them.

SO2 can also aggravate respiratory conditions in humans, especially those with asthma, leading to an increase in symptoms, hospital admissions, and emergency visits. In areas where there are high levels of sulfur oxides, their reactions with other atmospheric components can create small particles, which contribute to overall particulate matter (PM) levels. Particulate matter can lower visibility and, when inhaled by humans, adversely affect their health. SO2 can also lead to acid rain.

Data Products for Measuring Sulfur Dioxide
Research quality, or higher-level "standard" data products, can be accessed via Earthdata Search:

  • OMI SO2 Data from Earthdata Search
    Ozone Monitoring Instrument (OMI), aboard the Aura spacecraft, provides daily total column data at a resolution of 13x24 km; data are in HE5 format (HDF Release 5) and can be opened using Panoply.
  • OMPS SO2 Data from Earthdata Search
    SO2 Total and Tropospheric Column data from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor is on the Suomi NPP satellite; data are in HE5 format and can be opened using Panoply. Note that the data are at the various atmospheric levels (planetary boundary layer, stratospheric layer, and tropospheric layers).
  • TROPOMI SO2 data from Earthdata Search
    TROPOspheric Monitoring Instrument (TROPOMI), aboard Sentinel 5, is a European Space Agency (ESA) Mission. ESA TROPOMI SO2 provides additional information on this Level 2 data product. Data are NetCDF and can be opened using Panoply. Note: you may need to adjust the scaling factor in Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

NRT data can be accessed via Worldview:

NASA also has a global sulfur dioxide monitoring site that provides imagery of daily SO2 measurements from OMI, OMPS, and TROPOMI. The site also provides information on the source of emissions.

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Find Power Outages Data

Find Power Outages Data

Top image shows a typical night before Hurricane Maria made landfall, based upon cloud-free and low moonlight conditions; the below image is a composite that shows light detected by VIIRS on the nights of September 27 and 28, 2017. The images above show widespread outages around San Juan, including key hospital and transportation infrastructure.
Images show light detected by VIIRS on the nights of September 27 and 28, 2017. The images above show widespread outages around San Juan, including key hospital and transportation infrastructure. Credit: NASA
The VIIRS Nighttime Imagery layer shows the earth's surface and atmosphere using a sensor designed to capture low-light emission sources, under varying illumination conditions, which provides an assessment of power outages across an area due to the event.

Research-quality data products can be accessed via Earthdata Search and close to NRT data can be accessed via Worldview:





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Find Post-Event Assessment Data

Find Post-Event Assessment Data

Example of an interferogram created from SAR imagery. This example shows ground displacement caused by an earthquake in Chile in 2015. Displacement is indicated by multi-colored fringes, with the distance between fringes of the same color indicating 8.5 cm of displacement.
NASA ASF DAAC scientists used SAR data acquired from the European Space Agency (ESA) Sentinel-1A mission to create this interferogram showing land displacement following a September 16, 2015, earthquake in Chile. One complete color cycle represents a relative line-of-sight motion of 8.5 cm. NASA’s ASF DAAC distributes the complete historical archive of ESA-processed Sentinel-1A SAR data by agreement between the U.S. State Department and the European Commission. This image is combined with a Landsat image in Google Earth (© 2015 Google). Credit: F. Meyer, W. Gong 2015
Repeat-pass radar interferometry from spaceborne platforms is routinely used to produce topographic change maps as digital displacement models (DDMs). When two observations are made from the same location in space but at different times, the interferometric phase is directly proportional to any change in the range of a surface feature. This change allows for the measurement of any displacement or ground deformation that has occurred between the time of the two observations.

Interferometric SAR thus provides centimeter-level measurements of displacement from earthquake ruptures and volcanic eruptions. This displacement or deformation is seen as contour lines; where the lines are closer together, there was a lot of movement. Discontinuities in the contour lines also show where the actual fault rupture is. Contour lines are half of the radar's wavelength; so Sentinel-1 with a radar length of 6 cm has contour lines indicating ground deformation of 3 cm.

Research-quality data products can be accessed via Earthdata Search or from NASA's Alaska Satellite Facility Distributed Active Archive Center (ASF DAAC).

To learn more about SAR, view What is SAR? or about processing Level 1 data, view NASA's Applied Remote Sensing Training (ARSET) Introduction to SAR training or the Earthdata webinars, Introduction to SAR and Applications of SAR Data in GIS Environments

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Tools for Data Access and Visualization

Tools for Data Access and Visualization

Earthdata Search | Panoply | Giovanni | Worldview | Sentinel Toolbox

Earthdata Search is a tool for data discovery of Earth Observation data collections from NASA's Earth Observing System Data and Information System (EOSDIS), as well as U.S and international agencies across the Earth science disciplines.

Users (including those without specific knowledge of the data) can search for and read about data collections, search for data files by date and spatial area, preview browse images, and download or submit requests for data files, with customization for select data collections.

Screenshot of the Search Earthdata site.

In the project area, for some datasets, you can customize your granule. You can reformat the data and output as HDF, NetCDF, ASCII, KML, or a GeoTIFF. You can also choose from a variety of projection options. Lastly, you can subset the data, obtaining only the bands that are needed.

Earthdata Search customization tools diagram.

Panoply

HDF and NetCDF files can be viewed in Panoply, a cross-platform application that plots geo-referenced and other arrays. Panoply offers additional functionality, such as slicing and plotting arrays, combining arrays, and exporting plots and animations.

Giovanni

Giovanni is an online environment for the display and analysis of geophysical parameters. There are many options for analysis. The following are the more popular ones.

  • Time-averaged maps are a simple way to observe the variability of data values over a region of interest.
  • Map animations are a means to observe spatial patterns and detect unusual events over time.
  • Area-averaged time series are used to display the value of a data variable that has been averaged from all the data values acquired for a selected region for each time step.
  • Histogram plots are used to display the distribution of values of a data variable in a selected region and time interval.

For more detailed tutorials:

  • Giovanni How-To's on NASA's GES DISC YouTube channel.
  • Data recipe for downloading a Giovanni map as NetCDF and converting its data to quantifiable map data in the form of latitude-longitude-data value ASCII text.

Worldview

NASA's EOSDIS Worldview visualization application provides the capability to interactively browse over 900 global, full-resolution satellite imagery layers and then download the underlying data. Many of the available imagery layers are updated within three hours of observation, essentially showing the entire Earth as it looks "right now." This supports time-critical application areas such as wildfire management, air quality measurements, and flood monitoring. Imagery in Worldview is provided by NASA's Global Imagery Browse Services (GIBS). Worldview now includes nine geostationary imagery layers from GOES-East, GOES-West and Himawari-8 available at ten minute increments for the last 30 days. These layers include Red Visible, which can be used for analyzing daytime clouds, fog, insolation, and winds; Clean Infrared, which provides cloud top temperature and information about precipitation; and Air Mass RGB, which enables the visualization of the differentiation between air mass types (e.g., dry air, moist air, etc.). These full disk hemispheric views allow for almost real-time viewing of changes occurring around most of the world.

Worldview data visualization of the nighttime lights in Puerto Rico pre- and post- Hurricane Maria, which made landfall on September 20, 2017. Post-hurricane image shows widespread outages around San Juan, including key hospital and transportation infrastructure.

Worldview data visualization of the nighttime lights in Puerto Rico pre- and post- Hurricane Maria, which made landfall on September 20, 2017. The post-hurricane image on the left shows widespread outages around San Juan, including key hospital and transportation infrastructure.

Sentinel Toolbox

The European Space Agency (ESA) Sentinel-1 Mission consists of two satellites, Sentinel-1A and Sentinel-1B, with synthetic aperture radar instruments operating at a C-Band frequency. They orbit 180° apart, together imaging the entire Earth every six days. Synthetic Aperture Radar (SAR) is an active sensor and so can penetrate cloud cover and vegetation canopy and can observe at night. It also provides useful information to detect movement of Earth material after an earthquake, volcanic eruption or landslide. SAR data are very complex to process, but ESA has developed a Sentinel-1 Toolbox to aid with processing and analysis of Sentinel-1 data.

For more information on active sensors, see What is Remote Sensing; and for more information on SAR specifically, see What is SAR?

SAR Interferometry

Once you have downloaded the data, a data file before the event and a data file after the event, you will need to coregister the two files and then create an interferogram. The process for doing that follows:

  1. Visualize: Open the files in the Sentinel Toolbox. Important note: DO NOT unzip the downloaded SAR file. When you expand the Bands folder, you will find bands containing the real (i) and imaginary (q) parts of the complex data. In Sentinel-1 IW SLC products, you will find three sub-swaths labeled IW1, IW2, and IW3. To view the data, double-click on the Intensity_Sub-Swath_Polarization band of one of the two images.
  2. Coregister: For interferometric processing, two or more images must be coregistered into a stack. One image is selected as the master and the other images are the "slaves." The pixels in "slave" images will be moved to align with the master image to sub-pixel accuracy. To do this, select Radar/Coregistration/S-1 TOPS Coregistration. For more information on this type of processing, view Sentinel Online's Terrain Observation with Progressive Scans SAR (TOPSAR) processing technique.
    1. In the Read tab, select the first product. This should be the earlier of the two SLCs.
    2. In the Read(2) tab, select the other product. This will be your "slave" image.
    3. In the TOPSAR-Split tabs, select the appropriate sub-swath and polarization for each of the products.
    4. In the Apply-Orbit-File tabs, select the Sentinel Precise Orbit State Vectors. If precise orbits are not yet available for your product, you may select the restituted orbits, which may not be as accurate but will be better than the predicted orbits available within the product.
    5. Sentinel-1 Toolbox coregistration process. Note the arrow to the left and right in the coregistration window; it will cycle through the different tabs.

      Sentinel-1 Toolbox coregistration process. Note the arrow to the left and right in the coregistration window; it will cycle through the different tabs.

      In the Back-Geocoding tab, select the Digital Elevation Model (DEM) to use and the interpolation methods. The default is the SRTM 3 Sec DEM.
    6. In the Write tab, set the Directory path to your working directory.
    7. Click Run to begin coregistering the data. The resulting coregistered stack product will appear in the Product Explorer window with the suffix Orb_Stack.
  3. Interferogram: The interferogram is formed by cross-multiplying the master image with the complex conjugate of the "slave." The amplitude of both images is multiplied while their respective phases are differenced to form the interferogram.
    1. Select the new stack file in the product explorer and then select Radar/Interferometric/Products/Interferogram Formation.
    2. Keep the default values for Interferogram Formation, but confirm that the output Directory path is correct.
    3. Click Run.
    Sentinel-1 Toolbox interferogram

    Through the interferometric processing flow, the tool tries to eliminate other sources of error so that what is left is typically the surface deformation related to an event. You can visualize the phase information at this step.

    Interferometric fringes represent a full 2π cycle of phase change. Fringes appear on an interferogram as cycles of colors, with each cycle representing relative range difference of half a sensor's wavelength. Relative ground movement between two points can be calculated by counting the fringes and multiplying by half of the wavelength. The closer the fringes are together, the greater the strain on the ground.

  4. Multilooking and Phase Filtering: Lastly the phase associated with topography has to be removed and additional phase filtering to reduce noise and enhance the appearance of the deformation fringes.

Step-by-steps of this can be found within the ASF DAAC Interferometric SAR data recipes.

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Published July 22, 2020

Page Last Updated: Jul 27, 2020 at 1:18 PM EDT