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
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKM_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKN_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKP_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKQ_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKR_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKS_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKT_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLL_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLM_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLN_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLP_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLQ_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLR_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLS_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLT_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JMR_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JMS_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JMT_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50KKU_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50KKV_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50KLU_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50KLV_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50KMU_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50KMV_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGJ_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGK_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGL_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGN_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JHM_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JHN_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49KGP_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49KGQ_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49KHP_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49KHQ_2018-08-13_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_56KKF_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JCK_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JCL_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JCM_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JCN_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JDK_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JDL_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JDM_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JDN_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JEK_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JEL_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JEM_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JEN_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JFK_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JFL_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JFM_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JFN_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JGM_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JGN_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KDP_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KDQ_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KDR_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KDS_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KEP_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KEQ_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KER_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KES_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KET_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KEU_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KEV_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KFA_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KFB_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KFP_2018-08-14_final.stac-item
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55KFQ_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_50JQP_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_50JRS_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_50JRT_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JTJ_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JTK_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JTL_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JTM_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JTN_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JUJ_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JUK_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JUL_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JUM_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JUN_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JVJ_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JVK_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JVL_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JVM_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JVN_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JWJ_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JWK_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JWL_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JWM_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JWN_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JXN_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KUP_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KUQ_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KVP_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KVQ_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KWP_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KWQ_2018-08-14_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KXP_2018-08-14_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

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