OPERA Dynamic Surface Water Extent from Harmonized Landsat Sentinel-2 product (Version 1)

(OPERA_L3_DSWX-HLS_V1)
Version1.0
Processing Level3
Start/Stop Date2023-Apr-04 to Present
Short NameOPERA_L3_DSWX-HLS_V1
DescriptionThis dataset contains Level-3 Dynamic OPERA surface water extent product version 1. The data are validated surface water extent observations beginning April 2023. Known issues and caveats on usage are described under Documentation. The input dataset for generating each product is the Harmonized Landsat-8 and Sentinel-2A/B (HLS) product version 2.0. HLS products provide surface reflectance (SR) data from the Operational Land Imager (OLI) aboard the Landsat 8 satellite and the MultiSpectral Instrument (MSI) aboard the Sentinel-2A/B satellite. The surface water extent products are distributed over projected map coordinates using the Universal Transverse Mercator (UTM) projection. Each UTM tile covers an area of 109.8 km × 109.8 km. This area is divided into 3,660 rows and 3,660 columns at 30-m pixel spacing. Each product is distributed as a set of 10 GeoTIFF (Geographic Tagged Image File Format) files including water classification, associated confidence, land cover classification, terrain shadow layer, cloud/cloud-shadow classification, Digital elevation model (DEM), and Diagnostic layer. To access the calibration/validation database for OPERA Dynamic Surface Water Extent Products, please contact podaac@podaac.jpl.nasa.gov
DOI10.5067/OPDSW-PL3V1
MeasurementTERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER PROCESSES/MEASUREMENTS
Platform/Sensor
LANDSAT-8
Platform
Name: LANDSAT-8 (LANDSAT-8)
Orbit Period: 99.0 minutes
Inclination Angle: 98.2 degrees
/
OLI
SENSOR
Name: Operational Land Imager (OLI)

Sentinel-2A
Platform
Name: Sentinel-2A (Sentinel-2A)
Orbit Period: 98.6 minutes
Inclination Angle: 98.18 degrees
/
Sentinel-2 MSI
SENSOR
Name: Sentinel-2 Multispectral Imager (Sentinel-2 MSI)

Sentinel-2B
Platform
Name: Sentinel-2B (Sentinel-2B)
Orbit Period: 98.6 minutes
Inclination Angle: 98.18 degrees
/
Sentinel-2 MSI
SENSOR
Name: Sentinel-2 Multispectral Imager (Sentinel-2 MSI)

ProjectObservational Products for End-Users from Remote Sensing Analysis, Satellite Needs Working Group (SNWG/OPERA)
Data ProviderPublisher: PO.DAAC
Creator: OPERA
Release Place: PO.DAAC
Release Date: 2023-Apr-10

FormatCloud Optimized GeoTIFF
Keyword(s)surface water, surface water extent, water area, DSWX, OPERA, HLS, Harmonized Landsat Sentinel-2
Questions related to this dataset? Contact podaac@podaac.jpl.nasa.gov
Resolution
Spatial Resolution: 30 Meters x 30 Meters
Temporal Resolution: Daily - < Weekly
 
Coverage
North Bounding Coordinate: 84 degrees
South Bounding Coordinate: -84 degrees
West Bounding Coordinate: -180 degrees
East Bounding Coordinate: 180 degrees
Time Span: 2023-Apr-04 to Present
 
Projection
Projection Type: Universal Transverse Mercator (UTM)
Projection Detail: Geolocation information included for each pixel
Ellipsoid: WGS 84
 
DATA CITATION POLICY
GENERAL DOCUMENTATION
PUBLICATIONS
  • https://doi.org/10.3390/rs11040374
    Jones, John W. “Improved Automated Detection of Subpixel-Scale Inundation—Revised Dynamic Surface Water Extent (DSWE) Partial Surface Water Tests.” Remote Sensing, vol. 11, no. 4, 2019 374. doi: 10.3390/rs11040374
PRODUCT USAGE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
IMPORTANT NOTICE
  • https://d2pn8kiwq2w21t.cloudfront.net/documents/ProductSpec_DSWX_URS309746.pdf
    > Issue: Cloud dilation and cirrus cloud labeling may obscure valid water detection.
    > Description: The DSWx WTR layer inherits labels for cloud, cloud shadow, and adjacent to cloud from the input HLS Fmask. The current HLS implementation of Fmask does not distinguish cirrus from other cloud types and pixels labeled as clouds are dilated (buffered) by a large distance to conservatively remove reflectance values that might be errant. However, the DSWx algorithm often correctly distinguishes inundated land ‘under’ these masked areas.
    > Recommendation(s): If this issue is problematic and the application permits, users are advised to composite multiple days of DSWx WTR observations, taking the minimum non-zero value across all dates in the composite period. Should this prove inadequate or when specific dates are of interest, the DSWx WTR-2 layer is explicitly designed as a potential substitute for the WTR layer when snow/ice isn’t prevalent, but cloud masking is excessive. No cloud, cloud shadow, or adjacent to cloud masking is applied to create WTR-2. See the Product Specification and Algorithm Theoretical Basis Documents for more information on DSWx band characteristics and purposes.

    > Issue: Occasional erroneous snow/ice labels.
    > Description: The DSWx WTR layer inherits snow/ice classification directly from the input HLS Fmask. Occasionally, Fmask misclassification occurs over water with atypical coloration due to dissolved solids, high concentrations of sediment or where waves are breaking along coastline segments.
    > Recommendation(s): HLS Fmask based labels for snow/ice have not been applied to the DSWx WTR-2 layer. When snow/ice labeling is observed in the DSWx WTR layer and they are not expected, users are advised to check the DSWx WTR-2 layer and consider whether this layer or a combination of it and just cloud-related labels might be applicable to their study area and application. See the Product Specification Document for a description of applicable class values in the DSWx CLOUD layer.

    > Issue: Occasional unmasked clouds over ocean.
    > Description: The DSWx WTR layer inherits labels for cloud, cloud shadow, and adjacent to cloud from the input HLS Fmask. Occasionally, the DSWx algorithm will classify as ‘not water’, clouds present over water that Fmask failed to detect. This visual artifact does not impact DSWx performance over dominantly land areas.
    > Recommendation(s): If this artifact unduly affects product utility and simple masking of ocean areas are not appropriate, the user is advised to temporally composite DSWx, taking the lowest non-zero value in each composite period. See the Product Specification Document for a description of applicable class values in the DSWx CLOUD layer.
Citation is critically important for dataset documentation and discovery. Please cite the data as follows, and cite the reference papers when it is appropriate.
Citation OPERA . 2023. OPERA Dynamic Surface Water Extent from Harmonized Landsat Sentinel-2 (Version 1). Ver. 1.0. PO.DAAC, CA, USA. Dataset accessed [YYYY-MM-DD] at https://doi.org/10.5067/OPDSW-PL3V1

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For more information see Data Citations and Acknowledgments.
Journal Reference Jones, John W. 2019. Improved Automated Detection of Subpixel-Scale Inundation—Revised Dynamic Surface Water Extent (DSWE) Partial Surface Water Tests , Remote Sensing, 11, 4. https://doi.org/10.3390/rs11040374