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
2018-01-30 09:32:35	ga_s2am_ard_3-2-1_56KLV_2018-01-30_final.stac-item
2018-02-03 10:53:11	ga_s2am_ard_3-2-1_53KKQ_2018-02-03_final.stac-item
2018-02-03 10:53:11	ga_s2am_ard_3-2-1_53KLQ_2018-02-03_final.stac-item
2018-02-03 10:53:11	ga_s2am_ard_3-2-1_53KMQ_2018-02-03_final.stac-item
2018-02-03 10:53:11	ga_s2am_ard_3-2-1_52KGV_2018-02-03_final.stac-item
2018-02-03 10:53:11	ga_s2am_ard_3-2-1_52KHU_2018-02-03_final.stac-item
2018-02-03 10:53:11	ga_s2am_ard_3-2-1_52KHV_2018-02-03_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_54KTV_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_54KUV_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KPQ_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KQQ_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KRP_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KRQ_2018-02-07_final.stac-item
2018-02-16 10:58:46	ga_s2am_ard_3-2-1_52KDV_2018-02-16_final.stac-item
2018-02-16 10:58:46	ga_s2am_ard_3-2-1_52KEV_2018-02-16_final.stac-item
2018-02-16 10:58:46	ga_s2am_ard_3-2-1_52KFV_2018-02-16_final.stac-item
2018-02-16 10:58:46	ga_s2am_ard_3-2-1_52KGV_2018-02-16_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_54KYV_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_54KZU_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_54KZV_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_55KBQ_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_55KCQ_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_55KDQ_2018-02-18_final.stac-item
2018-02-22 09:42:24	ga_s2am_ard_3-2-1_56KKV_2018-02-22_final.stac-item
2018-02-22 09:42:24	ga_s2am_ard_3-2-1_56KLV_2018-02-22_final.stac-item
2018-02-22 09:42:24	ga_s2am_ard_3-2-1_55KGQ_2018-02-22_final.stac-item
2018-02-22 09:42:24	ga_s2am_ard_3-2-1_55KHP_2018-02-22_final.stac-item
2018-02-22 09:42:24	ga_s2am_ard_3-2-1_55KHQ_2018-02-22_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51KWQ_2018-02-22_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51KXQ_2018-02-22_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51KYQ_2018-02-22_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51KZP_2018-02-22_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51KZQ_2018-02-22_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_52KBV_2018-02-22_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_51KWQ_2018-10-30_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_51KXQ_2018-10-30_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_51KYQ_2018-10-30_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_51KZP_2018-10-30_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_51KZQ_2018-10-30_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_52KBV_2018-10-30_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KUQ_2018-11-02_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KVQ_2018-11-02_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KWQ_2018-11-02_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KXQ_2018-11-02_final.stac-item
2018-11-08 11:53:56	ga_s2am_ard_3-2-1_50KQV_2018-11-08_final.stac-item
2018-11-08 11:54:00	ga_s2am_ard_3-2-1_50KPV_2018-11-08_final.stac-item
2018-11-08 11:54:03	ga_s2am_ard_3-2-1_50KNV_2018-11-08_final.stac-item
2018-11-11 12:04:02	ga_s2am_ard_3-2-1_50KMV_2018-11-11_final.stac-item
2018-11-11 12:04:05	ga_s2am_ard_3-2-1_50KLV_2018-11-11_final.stac-item
2018-11-11 12:04:08	ga_s2am_ard_3-2-1_50KKV_2018-11-11_final.stac-item
2018-11-21 12:04:00	ga_s2am_ard_3-2-1_50KMV_2018-11-21_final.stac-item
2018-11-21 12:04:03	ga_s2am_ard_3-2-1_50KLV_2018-11-21_final.stac-item
2018-11-21 12:04:06	ga_s2am_ard_3-2-1_50KKV_2018-11-21_final.stac-item
2018-11-21 12:04:07	ga_s2am_ard_3-2-1_49KHQ_2018-11-21_final.stac-item
2018-11-21 12:04:11	ga_s2am_ard_3-2-1_49KGQ_2018-11-21_final.stac-item
2018-11-21 12:04:21	ga_s2am_ard_3-2-1_49KHP_2018-11-21_final.stac-item
2018-11-22 09:53:04	ga_s2am_ard_3-2-1_55KGQ_2018-11-22_final.stac-item
2018-11-22 09:53:08	ga_s2am_ard_3-2-1_55KFQ_2018-11-22_final.stac-item
2018-11-22 09:53:11	ga_s2am_ard_3-2-1_55KEQ_2018-11-22_final.stac-item
2018-11-22 09:53:14	ga_s2am_ard_3-2-1_55KDQ_2018-11-22_final.stac-item
2018-11-25 10:03:09	ga_s2am_ard_3-2-1_55KDQ_2018-11-25_final.stac-item
2018-11-25 10:03:13	ga_s2am_ard_3-2-1_55KCQ_2018-11-25_final.stac-item
2018-11-25 10:03:16	ga_s2am_ard_3-2-1_55KBQ_2018-11-25_final.stac-item
2018-11-25 10:03:16	ga_s2am_ard_3-2-1_54KZV_2018-11-25_final.stac-item
2018-11-25 10:03:30	ga_s2am_ard_3-2-1_54KZU_2018-11-25_final.stac-item
2018-12-02 09:53:03	ga_s2am_ard_3-2-1_55KGQ_2018-12-02_final.stac-item
2018-12-02 09:53:06	ga_s2am_ard_3-2-1_55KFQ_2018-12-02_final.stac-item
2018-12-02 09:53:10	ga_s2am_ard_3-2-1_55KEQ_2018-12-02_final.stac-item
2018-12-02 09:53:13	ga_s2am_ard_3-2-1_55KDQ_2018-12-02_final.stac-item
2018-12-03 11:03:33	ga_s2am_ard_3-2-1_52KGV_2018-12-03_final.stac-item
2018-12-03 11:03:37	ga_s2am_ard_3-2-1_52KFV_2018-12-03_final.stac-item
2018-12-03 11:03:40	ga_s2am_ard_3-2-1_52KEV_2018-12-03_final.stac-item
2018-12-03 11:03:45	ga_s2am_ard_3-2-1_52KDV_2018-12-03_final.stac-item
2018-12-06 11:13:36	ga_s2am_ard_3-2-1_52KEV_2018-12-06_final.stac-item
2018-12-06 11:13:39	ga_s2am_ard_3-2-1_52KDV_2018-12-06_final.stac-item
2018-12-06 11:13:43	ga_s2am_ard_3-2-1_52KCV_2018-12-06_final.stac-item
2018-12-06 11:13:46	ga_s2am_ard_3-2-1_51KZQ_2018-12-06_final.stac-item
2018-12-06 11:13:46	ga_s2am_ard_3-2-1_52KBV_2018-12-06_final.stac-item
2019-05-18 09:43:12	ga_s2am_ard_3-2-1_56KLV_2019-05-18_final.stac-item
2019-05-18 09:43:16	ga_s2am_ard_3-2-1_56KKV_2019-05-18_final.stac-item
2019-05-18 09:43:19	ga_s2am_ard_3-2-1_55KGQ_2019-05-18_final.stac-item
2019-05-18 09:43:30	ga_s2am_ard_3-2-1_55KHP_2019-05-18_final.stac-item
2019-06-06 10:13:21	ga_s2am_ard_3-2-1_55KBQ_2019-06-06_final.stac-item
2019-06-06 10:13:21	ga_s2am_ard_3-2-1_54KZV_2019-06-06_final.stac-item
2019-06-06 10:13:25	ga_s2am_ard_3-2-1_54KYV_2019-06-06_final.stac-item
2019-06-06 10:13:28	ga_s2am_ard_3-2-1_54KXV_2019-06-06_final.stac-item
2019-06-06 10:13:32	ga_s2am_ard_3-2-1_54KWV_2019-06-06_final.stac-item
2019-06-06 10:13:35	ga_s2am_ard_3-2-1_54KZU_2019-06-06_final.stac-item
2019-06-06 11:54:03	ga_s2am_ard_3-2-1_50KQV_2019-06-06_final.stac-item
2019-06-06 11:54:06	ga_s2am_ard_3-2-1_50KPV_2019-06-06_final.stac-item
2019-06-06 11:54:10	ga_s2am_ard_3-2-1_50KNV_2019-06-06_final.stac-item
2019-06-06 11:54:13	ga_s2am_ard_3-2-1_50KMV_2019-06-06_final.stac-item
2019-06-10 09:53:14	ga_s2am_ard_3-2-1_55KGQ_2019-06-10_final.stac-item
2019-06-10 09:53:17	ga_s2am_ard_3-2-1_55KFQ_2019-06-10_final.stac-item
2019-06-10 09:53:21	ga_s2am_ard_3-2-1_55KEQ_2019-06-10_final.stac-item
2019-06-10 09:53:24	ga_s2am_ard_3-2-1_55KDQ_2019-06-10_final.stac-item
2019-06-21 11:03:45	ga_s2am_ard_3-2-1_52KGV_2019-06-21_final.stac-item
2019-06-21 11:03:49	ga_s2am_ard_3-2-1_52KFV_2019-06-21_final.stac-item
2019-06-21 11:03:53	ga_s2am_ard_3-2-1_52KEV_2019-06-21_final.stac-item
2019-06-21 11:03:58	ga_s2am_ard_3-2-1_52KDV_2019-06-21_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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