InSAR – Collaboration

InSAR Access — API

Among ASF’s many collaborations, University NAVSTAR Consortium (UNAVCO)/Western North American InSAR (WInSAR), the Alaska Satellite Facility (ASF), and the Jet Propulsion Laboratory (JPL) worked on an information technology and data-management development project to design and implement a seamless distributed access system for synthetic aperture radar (SAR) data and derived interferometric data products. The seamless SAR archive increases the accessibility and the utility of SAR science data to solid Earth and cryospheric science researchers.

An example of the Vertex baseline plot. Users are provided with the capability to observe the perpendicular and temporal baseline distribution of an InSAR stack based on the selection of a desired master, filter granules, and select granules to download.

Specifically, the project will provide simple web services tools to more seamlessly and effectively exchange and share SAR metadata, data and archived and on-demand derived products between the distributed archives, individual users, and key information technology development systems such as the NASA/JPL Advanced Rapid Imaging and Analysis (ARIA) projects that provide higher level resources for geodetic data processing, data assimilation and modeling, and integrative analysis for scientific research and hazards applications. The proposed seamless SAR archive will significantly enhance mature IT capabilities at ASF’s NASA-supported DAAC, the Group on Earth Observations (GEO) Supersites archive, supported operationally by UNAVCO, and UNAVCO’s WInSAR and EarthScope archives that are supported by NASA, the National Science Foundation (NSF), and the United States Geological Survey (USGS) in close collaboration with the European Space Agency (ESA)/European Space Research Institute (ESRIN).

ALOS-PALSAR amplitude image, coherence image, interferogram, and interferogram overlaid on the amplitude of the master image (left to right). Master image: acquired 2006-11-05. Paired image acquired 2008- 11-10 over Baja, California, Mexico. The copyright for the scenes used to create this image (and those below) is held by the Japan Aerospace Exploration Agency/Ministry of Economy, Trade and Industry.

As part of the proposed effort, data/product standard formats and new QC/QA definitions will be developed and implemented to streamline data usage and enable advanced query capability. The seamless SAR archive will provide users with simple browser and web service API access tools to view and retrieve SAR data from multiple archives, to place their tasking requests, to order data, and to report results back to data providers; to make a larger pool of data available to scientific data users; and to encourage broader national and international use of SAR data. The new Advancing Collaborative Connections for Earth System Science (ACCESS)-developed tools will help overcome current obstacles including heterogeneous archive access protocols and data/product formats, data provider access policy constraints, and an increasingly broad and diverse selection of SAR data that now includes ESA/European Remote Sensing Satellite (ERS)/Environmental Satellite (ENVISAT) (and upcoming Sentinel mission), the Canadian Space Agency (CSA)/Radarsat, the Japan Aerospace Exploration Agency (JAXA)/Advanced Land Observation Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR), German Aero-Space Research Establishment (DLR)/TerraSAR-X satellite data and NASA/Uninhabited Aerial Vehicle SAR (UAVSAR) data. The list will continue to expand with NASA/Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) further increasing the need to efficiently discover, access, retrieve, distribute, and process huge quantities of new and diverse data.

To facilitate terrain corrections, the proposed NASA SAR (NSAR) project will provide InSAR-ready topographic data through OpenTopography. Shown in (a) above is the terrain correction (EGM96 removed) via Generic Mapping Tools (GMT) SAR (GMTSAR) from NASA SRTM data. The terrain-corrected differential interferogram unwrapped phase in (b) from the same ALOS PALSAR pair was processed using ROI_PAC. Red star shows epicenter of April 2010 Mw 7.2 earthquake. The apparent range change variation is 30 cm. (c) shows the zenith path delay difference from Online Services for Correcting Atmosphere in Radar (OSCAR) Modeling, Data and Information Systems (MODIS) zenith path delay maps. The path delay difference map shows no large gradient due to the troposphere in this case. The NSAR project will standardize product and corrections/QC formats and facilitate this type of product quality evaluation and access to products critical to the interpretation of interferograms for earth surface motions and deformation.

Project Objectives:

  • Develop and implement a federated metadata query and product-download capability from distributed airborne (NASA UAVSAR) and spaceborne SAR archives at ASF and UNAVCO/WInSAR.
  • Define and make available new QC parameters and products that will enhance the usability of data and data products from these existing NASA-funded collections.
  • Implement a web services enabled terrain correction service for interferometry (InSAR) using NASA Shuttle Radar Topography Mission (SRTM) data at the San Diego Supercomputer Center (SDSC).
  • Enhance ASF InSAR processing service to access distributed data collections, utilize terrain correction service, and generate enhanced QC products.
  • Establish processed data products archive.

InSAR – Find Data

Seamless Synthetic Aperture Radar Archive API

Search and Download Data from Multiple Archives

The Seamless Synthetic Aperture Radar (SAR) Archive (SSARA) Application Programming Interface (API) enables users to search and download:

  • Master and paired (slave) granules from the SAR archives at ASF and University NAVSTAR Consortium (UNAVCO)/Western North America InSAR (WInSAR);
  • Corresponding Digital Elevation Models (DEMs) from Open Topography and tropospheric data from Jet Propulsion Lab (JPL); and
  • Sample standardized InSAR data products from archives at ASF and WInSAR/UNAVCO.

SSARA API Services

SSARA API Keywords

absoluteOrbit asfResponseTimeout beamMode beamSwath
collectionName flightDirection frame intersectsWith
lookDirection masterStart/masterEnd maxBaselinePerp maxDoppler
maxFaradayRotation maxInsarStackSize maxResults minBaselinePerp
minDoppler minFaradayRotation minInsarStackSize minPercentCoherence
minPercentTroposphere minPercentUnwrapped output platform
polarization processingLevel relativeOrbit slaveStart/slaveEnd

To construct SSARA SAR API queries please visit the  API Tool or visit the SSARA Federated Querier GUI.

For information on the SSARA project please visit InSAR Collaborations.

If you have questions regarding the utilization of the ASF or SSARA API, please contact ASF User Support at [email protected].

Vertex Search and Download

ASF provides users the ability to search, evaluate, and download InSAR pairs via the Baseline Tool in the Vertex interface.

Users are able to:

  • Identify stacks of SAR granules suitable for interferometric processing;
  • Assess the perpendicular and temporal baseline distribution of a stack by interacting with the online Baseline Tool and
  • Select pairs for download

Selecting this option will show those granules that belong to an InSAR stack over the geographic region of interest. 

Using the Path & Frame option when constructing a search allows a user to see results that closely match their requirements. The Path & Frame option requires that you already know which path corresponds to your area of interest.

Searching by Path allows the user to dramatically narrow their search, and speed up search results. Useful when you know the path(s) associated with your AOI.

Helpful info regarding repeat passes:

Platform  |  Number of orbits before the satellite revisits the same area  |  Number of days before the satellite revisits the same area

  • ALOS: 671 (46 days)
  • R1: 343 (24 days)
  • E1: 501 (35 days)
  • E2: 501 (35 days)
  • Sentinel-1A: 175 (12 days) (6 days as S-1 constellation)
  • Sentinel-1B: 175 (12 days) (6 days as S-1 constellation)

An InSAR pair consists of two granules, a Master image, and a Paired image, that can form an interferogram.

An InSAR stack is composed of all granules that cover the same geographic region, are from the same platform (see exceptions in the next question), and were acquired with the same beam mode. Theoretically, any two granules in an InSAR stack may be used to create an interferogram, as long as the baseline is not beyond a certain critical length.

In principle, data from all satellites in the ASF archive should be suitable for InSAR, as long as the image pair adheres to some very basic rules: the data needs to be acquired by the same satellite, in the same beam mode, and with the same look direction.

There are a few exceptions to this rule. Sentinel-1A and Sentinel-1B can be used interchangeably. The tandem mode of the ERS-1 and ERS-2 satellites provide data very suitable for InSAR applications because both satellites meet the criteria above and have a favorable temporal baseline (data acquired one day apart). All the data in the archive, except RAMP data, are right looking. This means that RAMP data cannot be combined with any other Radarsat-1 data, even if those had been acquired with the same beam mode.

ScanSAR data, available for R1 or ALOS PALSAR, are another special case, as they are formed by combining several beam modes in one data set. This requires special processing techniques and is at this stage considered research-level processing.

  1. Radarsat-1
    1. Fine Beam (FN1-5)
    2. Standard Beam (ST1-7)
    3. Wide Beam
    4. Extended High Beam
    5. Extended Low Beam
    6. RAMP
  2. JERS-1 
    1. Fine Beam Single Polarimetric (FBS)
    2. Fine Beam Dual Polarimetric (FBD)
    3. Fine Beam Polarimetric
  4. ERS-1/ERS-2
  5. Sentinel-1A/Sentinel-1B (IW)

Baseline length is the temporal and spatial distance between two satellite observations:

  1. Perpendicular Baseline (B┴) is the spatial distance between the first and second observations measured perpendicular to the look direction. It gives an indication of the sensitivity to topographic height, the amount of decorrelation due to phase gradients, and the effectiveness of the phase unwrapping. The longer B┴, the weaker the coherency and the lower the sensitivity to height changes (Hanssen, R. Radar Interferometry: Data Interpretation and Error Analysis. Kluwer Academic Publishers; 2001. 308 p.)
  2. Temporal Baseline is the time difference between the first and second acquisition. To minimize decorrelation, the temporal baseline should be as short as possible. However, this may not be the case for studies of continuous deformation such as earthquake or volcano monitoring.
  3. Critical baseline is the maximum horizontal separation between two satellite orbits at which the Interferometric correlation becomes zero. It is a function of wavelength (λ), incidence angle (θinc), topographic slope (ζ), range bandwidth (BR), and range (R):

Standard interferometric processing techniques can only be applied when the baseline of the interferometric pair is well below the critical baseline. Advanced interferometric processing techniques, such as persistent scatterer analysis, are able to overcome this limitation.

The Baseline Tool is an interactive tool that allows users to visualize the perpendicular and temporal baseline distribution of all granules within a given InSAR stack. To access this tool select “Baseline” button in the search results page of Vertex.

    • Critical Baseline: Shown as a gray box on the plot. Represents the maximum baseline viable for interferometry.
    • Master Granule: The default Master granule is the interferable granule corresponding to the granule you have selected to analyze. It is highlighted by a black dot on the baseline plot and by the blue radio button in the baseline table (RAW, GRD, L1, L1.5 products may display in the Analyze box, but will not display in the table or plot).
    • Paired Granules: Granules represented by gray dots.
    • Selected Granules: Granules that have been selected for download appear as blue dots in the plot, and have a check mark in the download column of the table.
    • Baseline Filters
      • Acquisition Date: Click on the blue box and use sliders to filter by date. 
      • Perpendicular Baseline: Click on the blue box and use sliders to filter by baseline.
      • Temporal Baseline: Click on the blue box and use sliders to filter by time. 
    • Granule Information 
      • Queue: Click to add to queue for download by Download script.
      • Set As Master: Click gray dot on plot, then click Set As Master to change master granule.
      • Download: Click to download granule in the Granule Information box.
    • Baseline Table
      • Download Select: Check the box to queue product for download via the download script.
      • Master Select: Click the radio button to set the master.
      • Export CSV: Exports the baseline table to CSV.
      • Download Script: Download a script which will download products checked in the download column.
      • One-Click Download: Click the blue down-arrow to immediately download the product.
      • Column Sorting: Click at top of column to sort.


Differential interferometric synthetic aperture radar (InSAR) is used to measure displacements on Earth’s surface to a precision of a few centimeters or less….

Sentinel-1 Interferograms – Command Line Tools

There are many ways to access Sentinel-1 interferograms for users comfortable working at the command line. Below are steps and options to explore.

Find Interferograms via the CMR Search API

Sentinel-1 Interferogram (BETA) products are integrated with the ESDIS Common Metadata Repository (CMR), and are searchable via the CMR Search API. Visit the CMR Search API documentation for details and available search parameters.

The CMR collection concept IDs for Sentinel-1 Interferogram (BETA) products are:

  • C1379535891-ASF — Sentinel-1 All Interferometric Products (BETA)
  • C1379522387-ASF — Sentinel-1 Full Resolution Wrapped Interferogram and DEM (BETA)
  • C1379535600-ASF — Sentinel-1 Unwrapped Interferogram and Coherence Map (BETA)

For example, this search returns a list of all “Sentinel-1 All Interferometric Products (BETA)” products over Pasadena, CA since Jan 1, 2018:,&point=-118.1445,34.1478&page_size=50


The download URL for each product can be extracted from CMR search results and downloaded via command line tools like cURL and Wget.

Get Interferograms via cURL and Wget

Visit How To Access Data With cURL and Wget for instructions on downloading products with cURL and Wget, including how to provide your Earthdata Login credentials via a .netrc file.

Get Interferograms via AWS CLI, Boto 3, and GDAL

Sentinel-1 Interferogram (BETA) products are stored in Amazon Web Services’ Simple Storage Service (AWS S3). In addition to obtaining files via HTTP download, ASF makes these products available for download via AWS tools such as the AWS CLI, the Python Boto 3 library, and GDAL’s vsis3 utility.

Configuring Temporary Security Credentials

Users can obtain a temporary AWS access key from ASF using their Earthdata Login credentials. The temporary key is then used to obtain data while the access key is valid. Temporary access keys are obtained by invoking the following URL

Enter your Earthdata Login credentials when prompted. If accessing via cURL or Wget, you can provide your credentials via a .netrc file as described at How To Access Data With cURL and Wget.

The “Credentials” block of the response includes an Access Key, Secret Key, and Session Token for a temporary S3 session, along with the session’s expiration date. The “PolicyDocument” block describes the AWS permissions granted for the session, including the name of the S3 bucket where Sentinel-1 Interferogram (BETA) products are stored.

Authentication for the AWS CLI and other tools can be configured by setting the following environment variables:

$ export AWS_SESSION_TOKEN=FQoDYXdzEGMaDAcgUNixqCXpy…<remainder of security token>


This python script is an example of requesting credentials and formatting the necessary export commands.


The AWS Command Line Interface (CLI) is a unified tool to manage your AWS services that introduces a set of simple file commands for efficient file transfers to and from Amazon S3.

NOTE: You must configure temporary security credentials before using Boto.

AWS Command Line Interface Documentation
Using Temporary Security Credentials with the AWS CLI
s3 Command Reference
s3api Command Reference

$ aws s3 ls s3://grfn-content-prod/S1-IFG_RM_M1S1_TN158_20180422T130337-20180410T130310_s1-resorb-70ec-v1.2.1-standard
2018-04-22 21:21:16 32402145
2018-04-22 21:21:11 39487496
2018-04-22 21:20:58 496855659

$ aws s3 cp s3://grfn-content-prod/ .
download: s3://grfn-content-prod/ to ./

Boto 3 Python Library

Boto is the Amazon Web Services (AWS) SDK for Python, which allows Python developers to write software that makes use of Amazon services like S3.

NOTE: You must configure temporary security credentials before using Boto.

Boto 3 Documentation
Credentials Configuration
S3 API Reference

>>> import boto3
>>> s3 = boto3.client(‘s3’)
>>> s3.list_objects_v2(Bucket=’grfn-content-prod’, MaxKeys=2)[‘Contents’][
‘Key’: ‘’,
‘StorageClass’: ‘GLACIER’,
‘ETag’: ‘”f2b2d9b77157e2f4be2d9811700e5908-2″‘,
‘Size’: 164511413,
‘LastModified’: datetime.datetime(2018, 2, 20, 18, 16, 7, tzinfo = tzlocal())
‘Key’: ‘’,
‘StorageClass’: ‘GLACIER’,
‘ETag’: ‘”2a9e191d8727af0836c19b050c8c8e2f-3″‘,
‘Size’: 299567035,
‘LastModified’: datetime.datetime(2018, 2, 20, 18, 16, 7, tzinfo = tzlocal())
]>>> s3.head_object(Bucket=’grfn-content-prod’, Key=’’)
‘Metadata’: {},
‘ResponseMetadata’: {
‘HTTPHeaders’: {
‘date’: ‘Wed, 25 Apr 2018 18:35:07 GMT’,
‘etag’: ‘”f2b2d9b77157e2f4be2d9811700e5908-2″‘,
‘content-type’: ‘application/zip’,
‘x-amz-storage-class’: ‘GLACIER’,
‘last-modified’: ‘Tue, 20 Feb 2018 18:16:07 GMT’,
‘x-amz-id-2’: ‘X9z2Dmd/Ba4D0SRedulBVQEKk5IHsgRYAkaHi+9iGedW6NQZsT1Qk43b8ztonDT3GA6XpBlprcQ=’,
‘accept-ranges’: ‘bytes’,
‘server’: ‘AmazonS3’,
‘x-amz-request-id’: ‘6B9E0C3BD197BBDA’,
‘content-length’: ‘164511413’
‘HostId’: ‘X9z2Dmd/Ba4D0SRedulBVQEKk5IHsgRYAkaHi+9iGedW6NQZsT1Qk43b8ztonDT3GA6XpBlprcQ=’,
‘HTTPStatusCode’: 200,
‘RetryAttempts’: 0,
‘RequestId’: ‘6B9E0C3BD197BBDA’
‘ETag’: ‘”f2b2d9b77157e2f4be2d9811700e5908-2″‘,
‘ContentType’: ‘application/zip’,
‘ContentLength’: 164511413,
‘AcceptRanges’: ‘bytes’,
‘LastModified’: datetime.datetime(2018, 2, 20, 18, 16, 7, tzinfo = tzutc()),
‘StorageClass’: ‘GLACIER’

Geospatial Data Abstraction Library (GDAL)

GDAL is a translator library for raster and vector geospatial data formats.

NOTE: You must configure temporary security credentials before using GDAL.

GDAL Documentation
Virtual File Systems — AWS S3 Files
Virtual File Systems — Zip Archives
Raster Utility Programs

$ gdalinfo /vsizip/vsis3/grfn-content-prod/
Driver: VRT/Virtual Raster
Files: /vsizip/vsis3/grfn-content-prod/
Size is 5084, 6062
Coordinate System is:
        SPHEROID[“WGS 84”,6378137,298.257223563,
    AUTHORITY[“EPSG”,”4326″]]Origin = (-105.581388888888895,33.450277777777778)
Pixel Size = (0.000277777777778,-0.000277777777778)
Corner Coordinates:
Upper Left  (-105.5813889,  33.4502778)  (105d34’53.00″W,  33d27′ 1.00″N)
Lower Left  (-105.5813889,  31.7663889)  (105d34’53.00″W,  31d45’59.00″N)
Upper Right (-104.1691667,  33.4502778)  (104d10′ 9.00″W,  33d27′ 1.00″N)
Lower Right (-104.1691667,  31.7663889)  (104d10′ 9.00″W,  31d45’59.00″N)
Center      (-104.8752778,  32.6083333)  (104d52’31.00″W,  32d36’30.00″N)
Band 1 Block=5084×1 Type=Float32, ColorInterp=Undefined
Band 2 Block=5084×1 Type=Float32, ColorInterp=Undefined

$ gdal_translate -of GTiff /vsizip/vsis3/grfn-content-prod/ out.tif
Input file size is 5084, 6062
0…10…20…30…40…50…60…70…80…90…100 – done.

Get Interferograms from Long-Term Storage

Sentinel-1 Interferogram (BETA) products older than 60 days may be transitioned to long-term storage. Files in long-term storage are not immediately available for download.

The storage status of a file (available, archived, or retrieving) can be checked by invoking<file_name> :

$ wget -O- -q
  “status”: “archived”


Invoking the download URL for archived products will initiate the retrieval process and return a HTTP 202 ACCEPTED response:

$ wget -O- -q
Your requested data are being fetched from long-term storage. Please try again later.

$ wget -O- -q
  “status”: “retrieving”


The status URL can be monitored until the file’s status transitions to “available”. This usually takes a few minutes, but can take several hours when requesting a large number of files.

$ wget -O- -q
  “status”: “available”,
  “expiration_date”: “2018-05-02 00:00:00”


Files with a status of “available” are immediately available for download via their download URL.

This python script is an example of using these tools to download a file from long-term storage.

Sentinel-1 Interferograms – Get Interferograms

Register for an Earthdata Login Account

A NASA EOSDIS Earthdata Login account is required for downloading data from the Alaska Satellite Facility. Visit the Register for an Earthdata Login Profile page to create an account.

Get Interferograms via Vertex

Sentinel-1 Interferogram (BETA) products can be browsed in Vertex from the “Missions” tab under “Beta Products”.  

Bulk downloads via python script or metalink files are not supported for Sentinel-1 Interferogram (BETA) products.

Get Interferograms via Earthdata Search

Sentinel-1 Interferogram (BETA) products can be located in Earthdata Search by entering “sentinel-1_insar” in the search bar. For more information, visit the How to Search using Earthdata Search documentation.

Get Interferograms from Long-Term Storage

Sentinel-1 Interferogram (BETA) products older than 60 days may be transitioned to long-term storage. Users attempting to access these files will see a brief delay while they are retrieved and made available for download. This usually takes a few minutes, but can take several hours when requesting large numbers of files. Users can choose to be emailed when all of the files they have requested are available for download.

Deformation in the Carlsbad, New Mexico, region is revealed in this Sentinel-1 InSAR beta image. Created through the collaborative Getting Ready for NISAR project with JPL, this image is one of many available through either ASF DAAC’s Vertex or NASA’s Earthdata Search. See the full article for more about the project, available products, and how to offer feedback. Image credit: ASF DAAC & JPL 2017, contains modified Copernicus Sentinel data 2017.

Sentinel-1 Interferograms

Sentinel-1 Interferogram (BETA) products are prototype Level 2 interferometric products produced as part of the Getting Ready for NISAR (GRFN) project using the ARIA Science Data System under development for the NISAR mission….

Terrestrial Ecology – How To Cite

Citing Terrestrial Ecology Dataset

Cite datasets in publications such as journal papers, articles, presentations, posters, and websites. Please send copies of, or links to, published works citing data, imagery, or tools accessed through ASF to [email protected] with “New Publication” on subject line.

Also see ALOS PALSAR Terms and Conditions and How to Cite ALOS-1 PALSAR data.

Format Example
Dataset: SAR Subsets for Selected Field Sites, ASF DAAC, ORNL DAAC, 2010. Retrieved from] ASF DAAC [day month year of data access]. Includes Material © JAXA/METI [year of data acquisition]. Dataset: SAR Subsets for Selected Field Sites, ASF DAAC, ORNL DAAC, 2010. Retrieved from ASF DAAC 11 June 2015. Includes Material © JAXA/METI 2007.

Crediting Terrestrial Ecology Imagery

Include credit with each image shown in publications such as journal papers, articles, presentations, posters, and websites.

Format Example
[creator credit, year created]; Includes Material © JAXA/METI [year of data acquisition]. ASF DAAC, ORNL DAAC 2010; Includes Material © JAXA/METI 2007.