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
2016-12-05 09:59:28	ga_s2am_ard_3-2-1_54JYR_2016-12-05_final.stac-item
2016-12-05 09:59:28	ga_s2am_ard_3-2-1_54JYS_2016-12-05_final.stac-item
2016-12-05 09:59:28	ga_s2am_ard_3-2-1_54JZS_2016-12-05_final.stac-item
2016-12-05 09:59:28	ga_s2am_ard_3-2-1_55JBL_2016-12-05_final.stac-item
2016-12-05 09:59:28	ga_s2am_ard_3-2-1_55JBM_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HVD_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HVE_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HVF_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HVG_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HVH_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HWC_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HWD_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HWE_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HWF_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HWG_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HWH_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HWJ_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HWK_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HXC_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HXD_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HXE_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HXF_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HXG_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HXH_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HXJ_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HXK_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HYD_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HYE_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HYF_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HYG_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HYH_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HYJ_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54HYK_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JWL_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JWM_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JXL_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JXM_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JXN_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JXP_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JXQ_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JXR_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JYL_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JYM_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JYN_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JYP_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JYQ_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_54JYR_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55HBA_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55HBB_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55HBC_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55HBD_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55HBE_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55HBV_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55HCE_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55JBF_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55JBG_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55JBH_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55JBJ_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55JBK_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55JBL_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55JCF_2016-12-05_final.stac-item
2016-12-05 10:04:17	ga_s2am_ard_3-2-1_55JCG_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HMH_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HMJ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HMK_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HNH_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HNJ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HNK_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HPJ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HPK_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HQH_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HQJ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HQK_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JML_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JMM_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JNL_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JNM_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JNN_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JNP_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JNQ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JNR_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JPL_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JPM_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JPN_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JPP_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JPQ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JPR_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JQL_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JQM_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JQN_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JQP_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JQQ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JQR_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51JTF_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51JTG_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51JTH_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51JTJ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51JTK_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51JTL_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51JUL_2016-12-05_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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