Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KKA_2017-09-17_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KKB_2017-09-17_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KKV_2017-09-17_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KLA_2017-09-17_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KLV_2017-09-17_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KMA_2017-09-17_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_50KMV_2017-09-17_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_49KHQ_2017-09-17_final.stac-item
2017-09-17 12:03:44	ga_s2am_ard_3-2-1_49KHR_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKQ_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKR_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JLQ_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JLR_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JMR_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGK_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKS_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKT_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JLS_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JLT_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JMS_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGL_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGM_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGN_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JHM_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JHN_2017-09-17_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_56KKF_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JCK_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JCL_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JCM_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JCN_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JDK_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JDL_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JDM_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JDN_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JEK_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JEL_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JEM_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JEN_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JFK_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JFL_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JFM_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JFN_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JGM_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55JGN_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KDP_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KDQ_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KDR_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KDS_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KEP_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KEQ_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KER_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KES_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KET_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KEU_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KEV_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KFA_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KFB_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KFP_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KFQ_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KFR_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KFS_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KFT_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KFU_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KGB_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KGP_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KGQ_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KGR_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KGS_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KGT_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KGU_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55KHS_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55LFC_2017-09-18_final.stac-item
2017-09-18 09:51:01	ga_s2am_ard_3-2-1_55LGC_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JBG_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JBH_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JCG_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JCH_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JCJ_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JCK_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JDG_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JDH_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JDJ_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JDK_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JEG_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JEH_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JEJ_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JEK_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JFH_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JFJ_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JFK_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JDF_2017-09-18_final.stac-item
2017-09-18 09:54:23	ga_s2am_ard_3-2-1_55JEF_2017-09-18_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_50HQK_2017-09-18_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_50JPL_2017-09-18_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_50JQL_2017-09-18_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_50JQM_2017-09-18_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_51HTE_2017-09-18_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_51HUE_2017-09-18_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_51HVE_2017-09-18_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_51JTF_2017-09-18_final.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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