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Researchers working with the Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at NASA's Jet Propulsion Laboratory, Pasadena, California, created monthly average coherence products for the active landslides in Rancho Palos Verdes, Los Angeles, California, USA.<\/span><\/p>

The ARIA/OPERA team computed the interferometric coherence from interferometric synthetic aperture radar (InSAR) data between October 2017 and September 2024. The InSAR data were acquired by Copernicus Sentinel-1A/B satellites on descending (satellite moving south and looking west) track 71 and processed by the ARIA team to geocoded standard unwrapped interferograms (GUNW) with coherence layers. ARIA GUNWs are archived at the NASA Alaska Satellite Facility Distributed Active Archive Center (ASF DAAC).<\/span><\/p>

Interferometric coherence is a measure of the correlation or similarity between two satellite acquisition returns over the same area. Coherence values range from 0 to 1, where 0 represents decorrelation (drastic change in ground surface conditions between repeat satellite returns) and 1 represents perfect coherence (high degree of similarity between repeat satellite returns). A significant drop in coherence could be indicative of changes such as vegetation growth, snow cover, and/or surface changes due to rapid ground motion.<\/span><\/p>

The <\/span>PV_12DayMonthlyCoherence-2017-2024_S1D64_map.png<\/a> shows the monthly average of 12-day interferometric coherence with a color variation from dark red to white. The red tones indicate lower coherence values indicative of higher surface changes. The white areas show good coherence that could mean either stable or slow moving surface condition. For the landslide, low coherence may also be used in some cases as a proxy for rapid landslide motion. The top row, Average (2015-2022), shows the monthly average between 2015-2022, which may be used as a reference to compare the 2023/2024 monthly averages.<\/span><\/p>

Processing Details<\/span><\/p>

We calculate mean monthly 12 day coherence maps from ARIA Standard InSAR products.<\/span><\/p>

We provide mean monthly 12 day coherence maps from ARIA Standard InSAR products for the 2023 water year (October 2022 - September 2023), 2024 water year (October 2022 - September 2023), and monthly coherence values are averaged for years 2017-2022, to compare with values in the 2023 water year and the 2024 water year.<\/span><\/p>

Files: <\/span><\/p>

All files can be downloaded at: <\/span>https://maps.disasters.nasa.gov/download/gis_products/event_specific/2024/palos_verdes_landslides_202410/opera/coherence/descending/<\/a><\/p>

PV_Avg12dayCoh_*_S1D71.tif (geotiff) shows the 12-day average coherence for the month/year in the file name.<\/span><\/p>

PV_Avg12dayCoh_2017-2022_S1D71.tif (geotiff) shows the 12-day average coherence for the month in the file name averaged between the years 2017 and 2022.<\/span><\/p>

PV_12DayMonthlyCoherence-2017-2024_S1D71_map.png shows average monthly 12-day coherence maps draped on lidar hillshade of topography. Landslide boundaries from the California Geological Survey (CGS) and roads and buildings from OpenStreetMap. <\/span><\/p>

Released October 28, 2024.<\/span><\/p>

Data Availability<\/span><\/p>

The Sentinel-1 InSAR products produced by ARIA - JPL, contain modified Copernicus data (2024). The products are available to download at <\/span>https://aria-share.jpl.nasa.gov/20241028-Palos_Verdes_Landslides<\/a><\/p>

Esri REST Endpoint<\/span><\/p>

See URL section on right side of page<\/span><\/p>

Resolution<\/span><\/p>

90 meters<\/span><\/p>

Credits<\/span><\/p>

NASA-JPL/Caltech ARIA Team<\/span><\/p>

Product POCs<\/span><\/p>

Alexander L. Handwerger (alexander.handwerger@jpl.nasa.gov)<\/span><\/p>

Marin Govorcin (marin.govorcin@jpl.nasa.gov)<\/span><\/p>

David Bekaert (david.bekaert@jpl.nasa.gov)<\/span><\/p>

Eric Fielding (eric.j.fielding@jpl.nasa.gov)<\/span><\/p>

References/Acknowledge<\/span><\/p>

https://aria.jpl.nasa.gov/<\/a> (ARIA project)<\/span><\/p>

https://www.jpl.nasa.gov/go/opera/<\/a> (OPERA Project)<\/span><\/p>

https://github.com/aria-tools/ARIA-tools<\/a> (ARIA InSAR data)<\/span><\/p>

https://github.com/insarlab/MintPy<\/a> (InSAR time series software)<\/span><\/p>

https://opentopography.org/<\/a> (topographic data)<\/span><\/p>

https://www.openstreetmap.org/<\/a> (buildings and road data)<\/span><\/p>

https://www.conservation.ca.gov/cgs/landslides<\/a> (landslide inventories)<\/span><\/p>

ACCESS 19-0023. The InSAR processor was first developed under JPL-Caltech ARIA project.
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Handwerger (alexander.handwerger@jpl.nasa.gov)Marin Govorcin (marin.govorcin@jpl.nasa.gov)David Bekaert (david.bekaert@jpl.nasa.gov)Eric Fielding (eric.j.fielding@jpl.nasa.gov)References/Acknowledgehttps://aria.jpl.nasa.gov/ (ARIA project)https://www.jpl.nasa.gov/go/opera/ (OPERA Project)https://github.com/aria-tools/ARIA-tools (ARIA InSAR data)https://github.com/insarlab/MintPy (InSAR time series software)https://opentopography.org/ (topographic data)https://www.openstreetmap.org/ (buildings and road data)https://www.conservation.ca.gov/cgs/landslides (landslide inventories)ACCESS 19-0023. 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The InSAR data were acquired by Copernicus Sentinel-1A/B satellites on descending (satellite moving south and looking west) track 71 and processed by the ARIA team to geocoded standard unwrapped interferograms (GUNW) with coherence layers. ARIA GUNWs are archived at the NASA Alaska Satellite Facility Distributed Active Archive Center (ASF DAAC).Interferometric coherence is a measure of the correlation or similarity between two satellite acquisition returns over the same area. Coherence values range from 0 to 1, where 0 represents decorrelation (drastic change in ground surface conditions between repeat satellite returns) and 1 represents perfect coherence (high degree of similarity between repeat satellite returns). A significant drop in coherence could be indicative of changes such as vegetation growth, snow cover, and/or surface changes due to rapid ground motion.The PV_12DayMonthlyCoherence-2015-2024_S1A64_map.png shows the monthly average of 12-day interferometric coherence with a color variation from dark red to white. The red tones indicate lower coherence values indicative of higher surface changes. The white areas show good coherence that could mean either stable or slow moving surface condition. For the landslide, low coherence may also be used in some cases as a proxy for rapid landslide motion. The top row, Average (2015-2022), shows the monthly average between 2015-2022, which may be used as a reference to compare the 2023/2024 monthly averages.Processing DetailsWe calculate mean monthly 12 day coherence maps from ARIA Standard InSAR products.We provide mean monthly 12 day coherence maps from ARIA Standard InSAR products for the 2023 water year (October 2022 - September 2023), 2024 water year (October 2022 - September 2023), and monthly coherence values are averaged for years 2017-2022, to compare with values in the 2023 water year and the 2024 water year.Files: PV_Avg12dayCoh_*_S1D71.tif (geotiff) shows the 12-day average coherence for the month/year in the file name.PV_Avg12dayCoh_2017-2022_S1D71.tif (geotiff) shows the 12-day average coherence for the month in the file name averaged between the years 2017 and 2022.PV_12DayMonthlyCoherence-2017-2024_S1D71_map.png shows average monthly 12-day coherence maps draped on lidar hillshade of topography. Landslide boundaries from the California Geological Survey (CGS) and roads and buildings from OpenStreetMap. Released October 28, 2024.Data AvailabilityThe Sentinel-1 InSAR products produced by ARIA - JPL, contain modified Copernicus data (2024). The products are available to download at https://aria-share.jpl.nasa.gov/20241028-Palos_Verdes_LandslidesEsri REST EndpointSee URL section on right side of pageResolution90 metersCreditsNASA-JPL/Caltech ARIA TeamProduct POCsAlexander L. Handwerger (alexander.handwerger@jpl.nasa.gov)Marin Govorcin (marin.govorcin@jpl.nasa.gov)David Bekaert (david.bekaert@jpl.nasa.gov)Eric Fielding (eric.j.fielding@jpl.nasa.gov)References/Acknowledgehttps://aria.jpl.nasa.gov/ (ARIA project)https://www.jpl.nasa.gov/go/opera/ (OPERA Project)https://github.com/aria-tools/ARIA-tools (ARIA InSAR data)https://github.com/insarlab/MintPy (InSAR time series software)https://opentopography.org/ (topographic data)https://www.openstreetmap.org/ (buildings and road data)https://www.conservation.ca.gov/cgs/landslides (landslide inventories)ACCESS 19-0023. 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