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
2018-11-24 10:33:05	ga_s2am_ard_3-2-1_54KUA_2018-11-24_final.stac-item
2018-11-24 10:33:09	ga_s2am_ard_3-2-1_54KTA_2018-11-24_final.stac-item
2018-11-24 10:33:09	ga_s2am_ard_3-2-1_53KRR_2018-11-24_final.stac-item
2018-11-24 10:33:13	ga_s2am_ard_3-2-1_53KQR_2018-11-24_final.stac-item
2018-11-24 10:33:16	ga_s2am_ard_3-2-1_53KPR_2018-11-24_final.stac-item
2018-11-24 10:33:24	ga_s2am_ard_3-2-1_53KRQ_2018-11-24_final.stac-item
2018-11-24 10:33:27	ga_s2am_ard_3-2-1_53KQQ_2018-11-24_final.stac-item
2018-11-24 12:13:47	ga_s2am_ard_3-2-1_50KKA_2018-11-24_final.stac-item
2018-11-24 12:13:47	ga_s2am_ard_3-2-1_49KHR_2018-11-24_final.stac-item
2018-11-24 12:13:51	ga_s2am_ard_3-2-1_49KGR_2018-11-24_final.stac-item
2018-11-24 12:14:01	ga_s2am_ard_3-2-1_49KHQ_2018-11-24_final.stac-item
2018-11-24 12:14:05	ga_s2am_ard_3-2-1_49KGQ_2018-11-24_final.stac-item
2018-11-26 09:32:47	ga_s2am_ard_3-2-1_56KMA_2018-11-26_final.stac-item
2018-11-26 09:32:51	ga_s2am_ard_3-2-1_56KLA_2018-11-26_final.stac-item
2018-12-06 09:32:47	ga_s2am_ard_3-2-1_56KMA_2018-12-06_final.stac-item
2018-12-06 09:32:51	ga_s2am_ard_3-2-1_56KLA_2018-12-06_final.stac-item
2019-03-23 11:03:21	ga_s2am_ard_3-2-1_52KHA_2019-03-23_final.stac-item
2019-03-23 11:03:26	ga_s2am_ard_3-2-1_52KGA_2019-03-23_final.stac-item
2019-03-23 11:03:29	ga_s2am_ard_3-2-1_52KFA_2019-03-23_final.stac-item
2019-03-23 11:03:31	ga_s2am_ard_3-2-1_52KHV_2019-03-23_final.stac-item
2019-03-23 11:03:33	ga_s2am_ard_3-2-1_52KEA_2019-03-23_final.stac-item
2019-03-23 11:03:40	ga_s2am_ard_3-2-1_52KGV_2019-03-23_final.stac-item
2019-03-27 10:43:15	ga_s2am_ard_3-2-1_53KQR_2019-03-27_final.stac-item
2019-03-27 10:43:19	ga_s2am_ard_3-2-1_53KPR_2019-03-27_final.stac-item
2019-03-27 10:43:22	ga_s2am_ard_3-2-1_53KNR_2019-03-27_final.stac-item
2019-03-27 10:43:25	ga_s2am_ard_3-2-1_53KMR_2019-03-27_final.stac-item
2019-03-28 10:13:04	ga_s2am_ard_3-2-1_55KBR_2019-03-28_final.stac-item
2019-03-28 10:13:04	ga_s2am_ard_3-2-1_54KZA_2019-03-28_final.stac-item
2019-04-03 10:33:14	ga_s2am_ard_3-2-1_54KUA_2019-04-03_final.stac-item
2019-04-03 10:33:17	ga_s2am_ard_3-2-1_54KTA_2019-04-03_final.stac-item
2019-04-03 10:33:17	ga_s2am_ard_3-2-1_53KRR_2019-04-03_final.stac-item
2019-04-03 10:33:21	ga_s2am_ard_3-2-1_53KQR_2019-04-03_final.stac-item
2019-04-03 10:33:24	ga_s2am_ard_3-2-1_53KPR_2019-04-03_final.stac-item
2019-04-03 10:33:32	ga_s2am_ard_3-2-1_53KRQ_2019-04-03_final.stac-item
2019-04-03 10:33:35	ga_s2am_ard_3-2-1_53KQQ_2019-04-03_final.stac-item
2019-04-03 12:13:55	ga_s2am_ard_3-2-1_50KKA_2019-04-03_final.stac-item
2019-04-03 12:13:55	ga_s2am_ard_3-2-1_49KHR_2019-04-03_final.stac-item
2019-04-03 12:13:59	ga_s2am_ard_3-2-1_49KGR_2019-04-03_final.stac-item
2019-04-03 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2019-04-03_final.stac-item
2019-04-03 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2019-04-03_final.stac-item
2019-04-08 09:42:51	ga_s2am_ard_3-2-1_56KMA_2019-04-08_final.stac-item
2019-04-08 09:42:55	ga_s2am_ard_3-2-1_56KLA_2019-04-08_final.stac-item
2019-04-08 09:42:59	ga_s2am_ard_3-2-1_56KKA_2019-04-08_final.stac-item
2019-04-08 09:42:59	ga_s2am_ard_3-2-1_55KHR_2019-04-08_final.stac-item
2019-04-08 09:43:02	ga_s2am_ard_3-2-1_55KGR_2019-04-08_final.stac-item
2019-04-08 09:43:13	ga_s2am_ard_3-2-1_55KHQ_2019-04-08_final.stac-item
2019-04-08 09:43:17	ga_s2am_ard_3-2-1_55KGQ_2019-04-08_final.stac-item
2019-04-09 10:53:23	ga_s2am_ard_3-2-1_53KMR_2019-04-09_final.stac-item
2019-04-09 10:53:26	ga_s2am_ard_3-2-1_53KLR_2019-04-09_final.stac-item
2019-04-09 10:53:29	ga_s2am_ard_3-2-1_53KKR_2019-04-09_final.stac-item
2019-04-09 10:53:30	ga_s2am_ard_3-2-1_52KHA_2019-04-09_final.stac-item
2019-04-09 10:53:34	ga_s2am_ard_3-2-1_52KGA_2019-04-09_final.stac-item
2019-04-09 10:53:44	ga_s2am_ard_3-2-1_52KHV_2019-04-09_final.stac-item
2019-04-09 10:53:48	ga_s2am_ard_3-2-1_52KGV_2019-04-09_final.stac-item
2019-07-25 10:43:19	ga_s2am_ard_3-2-1_53KQR_2019-07-25_final.stac-item
2019-07-25 10:43:24	ga_s2am_ard_3-2-1_53KPR_2019-07-25_final.stac-item
2019-07-25 10:43:28	ga_s2am_ard_3-2-1_53KNR_2019-07-25_final.stac-item
2019-07-25 10:43:31	ga_s2am_ard_3-2-1_53KMR_2019-07-25_final.stac-item
2019-07-27 09:42:55	ga_s2am_ard_3-2-1_56KMA_2019-07-27_final.stac-item
2019-07-27 09:42:59	ga_s2am_ard_3-2-1_56KLA_2019-07-27_final.stac-item
2019-07-27 09:43:02	ga_s2am_ard_3-2-1_56KKA_2019-07-27_final.stac-item
2019-07-27 09:43:03	ga_s2am_ard_3-2-1_55KHR_2019-07-27_final.stac-item
2019-07-27 09:43:06	ga_s2am_ard_3-2-1_55KGR_2019-07-27_final.stac-item
2019-07-27 09:43:17	ga_s2am_ard_3-2-1_55KHQ_2019-07-27_final.stac-item
2019-07-27 09:43:21	ga_s2am_ard_3-2-1_55KGQ_2019-07-27_final.stac-item
2019-07-27 11:23:40	ga_s2am_ard_3-2-1_52KBA_2019-07-27_final.stac-item
2019-07-27 11:23:40	ga_s2am_ard_3-2-1_51KZR_2019-07-27_final.stac-item
2019-07-27 11:23:44	ga_s2am_ard_3-2-1_51KYR_2019-07-27_final.stac-item
2019-07-27 11:23:48	ga_s2am_ard_3-2-1_51KXR_2019-07-27_final.stac-item
2019-07-27 11:23:54	ga_s2am_ard_3-2-1_51KZQ_2019-07-27_final.stac-item
2019-07-27 11:23:59	ga_s2am_ard_3-2-1_51KYQ_2019-07-27_final.stac-item
2019-07-30 09:53:01	ga_s2am_ard_3-2-1_55KGR_2019-07-30_final.stac-item
2019-07-30 09:53:05	ga_s2am_ard_3-2-1_55KFR_2019-07-30_final.stac-item
2019-07-30 09:53:08	ga_s2am_ard_3-2-1_55KER_2019-07-30_final.stac-item
2019-07-30 09:53:12	ga_s2am_ard_3-2-1_55KDR_2019-07-30_final.stac-item
2019-08-03 09:33:00	ga_s2am_ard_3-2-1_56KMA_2019-08-03_final.stac-item
2019-08-03 09:33:03	ga_s2am_ard_3-2-1_56KLA_2019-08-03_final.stac-item
2019-08-08 12:03:56	ga_s2am_ard_3-2-1_50KMA_2019-08-08_final.stac-item
2019-08-08 12:04:00	ga_s2am_ard_3-2-1_50KLA_2019-08-08_final.stac-item
2019-08-08 12:04:03	ga_s2am_ard_3-2-1_50KKA_2019-08-08_final.stac-item
2019-08-08 12:04:03	ga_s2am_ard_3-2-1_49KHR_2019-08-08_final.stac-item
2019-08-08 12:04:07	ga_s2am_ard_3-2-1_50KLA_2019-08-08_final.stac-item
2019-08-08 12:04:08	ga_s2am_ard_3-2-1_50KKA_2019-08-08_final.stac-item
2019-08-08 12:04:08	ga_s2am_ard_3-2-1_49KHR_2019-08-08_final.stac-item
2019-08-08 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-08-08_final.stac-item
2019-08-08 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2019-08-08_final.stac-item
2019-08-08 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2019-08-08_final.stac-item
2019-08-09 09:53:00	ga_s2am_ard_3-2-1_55KGR_2019-08-09_final.stac-item
2019-08-09 09:53:04	ga_s2am_ard_3-2-1_55KFR_2019-08-09_final.stac-item
2019-08-09 09:53:08	ga_s2am_ard_3-2-1_55KER_2019-08-09_final.stac-item
2019-08-09 09:53:11	ga_s2am_ard_3-2-1_55KDR_2019-08-09_final.stac-item
2019-08-11 10:33:24	ga_s2am_ard_3-2-1_53KQR_2019-08-11_final.stac-item
2019-08-11 10:33:28	ga_s2am_ard_3-2-1_53KPR_2019-08-11_final.stac-item
2019-08-11 10:33:35	ga_s2am_ard_3-2-1_53KRQ_2019-08-11_final.stac-item
2019-08-11 10:33:38	ga_s2am_ard_3-2-1_53KQQ_2019-08-11_final.stac-item
2019-08-12 11:43:47	ga_s2am_ard_3-2-1_51KUR_2019-08-12_final.stac-item
2019-08-12 11:43:51	ga_s2am_ard_3-2-1_51KTR_2019-08-12_final.stac-item
2019-08-12 11:43:51	ga_s2am_ard_3-2-1_50KRA_2019-08-12_final.stac-item
2019-08-12 11:43:55	ga_s2am_ard_3-2-1_50KQA_2019-08-12_final.stac-item
2019-08-12 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-08-12_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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