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
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HTF_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HTG_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HTH_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HTJ_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HUF_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HUG_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HUH_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HUJ_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HVD_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HVE_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HVF_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HVG_2018-10-19_final.stac-item
2018-10-19 10:07:01	ga_s2am_ard_3-2-1_54HVH_2018-10-19_final.stac-item
2018-10-19 11:47:03	ga_s2am_ard_3-2-1_51LUE_2018-10-19_final.stac-item
2018-10-19 11:47:03	ga_s2am_ard_3-2-1_51LUF_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLS_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLT_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JMS_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JMT_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JNS_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JNT_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JPS_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JPT_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JQT_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KLU_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KMA_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KMB_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KMC_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KMU_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KMV_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KNA_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KNB_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KNC_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KNU_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KNV_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KPA_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KPB_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KPC_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KPU_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KPV_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KQA_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KQB_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KQC_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KQU_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KQV_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KRC_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KRD_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_51KTU_2018-10-19_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56HKK_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JKL_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JKM_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JKN_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JKP_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JKQ_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JKR_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JKS_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JKT_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JLQ_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JLR_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JLS_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56JLT_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KKA_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KKB_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KKF_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KKU_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KKV_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KLA_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KLB_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KLD_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KLE_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KLF_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KLU_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KLV_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_56KMA_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JEK_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JEL_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JFJ_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JFK_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JFL_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JFM_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JFN_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JGF_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JGG_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JGH_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JGJ_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JGK_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JGL_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JGM_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JGN_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JHM_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JHN_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KFP_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KGP_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KGQ_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KGR_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KGS_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KGT_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KHP_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KHQ_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55KHR_2018-10-20_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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