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
2015-12-06 10:52:27	ga_s2am_ard_3-2-1_53KKQ_2015-12-06_final.stac-item
2015-12-06 10:52:27	ga_s2am_ard_3-2-1_53KKR_2015-12-06_final.stac-item
2015-12-06 10:52:27	ga_s2am_ard_3-2-1_53KLR_2015-12-06_final.stac-item
2015-12-06 10:52:27	ga_s2am_ard_3-2-1_53KMR_2015-12-06_final.stac-item
2015-12-06 10:52:27	ga_s2am_ard_3-2-1_52KGA_2015-12-06_final.stac-item
2015-12-06 10:52:27	ga_s2am_ard_3-2-1_52KGV_2015-12-06_final.stac-item
2015-12-06 10:52:27	ga_s2am_ard_3-2-1_52KHA_2015-12-06_final.stac-item
2015-12-06 10:52:27	ga_s2am_ard_3-2-1_52KHV_2015-12-06_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51KXR_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51KYQ_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51KYR_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51KZQ_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51KZR_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_52KBA_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_52KBV_2015-12-25_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_53KKQ_2015-12-26_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_53KKR_2015-12-26_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_53KLR_2015-12-26_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_53KMR_2015-12-26_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_52KGA_2015-12-26_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_52KGV_2015-12-26_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_52KHA_2015-12-26_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_52KHV_2015-12-26_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_50KKA_2015-12-27_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_50KLA_2015-12-27_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_50KMA_2015-12-27_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_49KHQ_2015-12-27_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_49KHR_2015-12-27_final.stac-item
2016-01-06 10:27:28	ga_s2am_ard_3-2-1_54KUA_2016-01-06_final.stac-item
2016-01-06 10:27:28	ga_s2am_ard_3-2-1_54KVA_2016-01-06_final.stac-item
2016-01-06 10:27:28	ga_s2am_ard_3-2-1_54KWA_2016-01-06_final.stac-item
2016-01-06 10:27:28	ga_s2am_ard_3-2-1_54KXA_2016-01-06_final.stac-item
2016-01-06 12:04:05	ga_s2am_ard_3-2-1_50KKA_2016-01-06_final.stac-item
2016-01-06 12:04:05	ga_s2am_ard_3-2-1_50KLA_2016-01-06_final.stac-item
2016-01-06 12:04:05	ga_s2am_ard_3-2-1_50KMA_2016-01-06_final.stac-item
2016-01-06 12:04:05	ga_s2am_ard_3-2-1_49KHQ_2016-01-06_final.stac-item
2016-01-06 12:04:05	ga_s2am_ard_3-2-1_49KHR_2016-01-06_final.stac-item
2016-01-23 10:15:08	ga_s2am_ard_3-2-1_54KWA_2016-01-23_final.stac-item
2016-01-23 10:15:08	ga_s2am_ard_3-2-1_54KXA_2016-01-23_final.stac-item
2016-01-23 10:15:08	ga_s2am_ard_3-2-1_54KYA_2016-01-23_final.stac-item
2016-01-23 10:15:08	ga_s2am_ard_3-2-1_54KYV_2016-01-23_final.stac-item
2016-01-23 10:15:08	ga_s2am_ard_3-2-1_54KZA_2016-01-23_final.stac-item
2016-01-23 10:15:08	ga_s2am_ard_3-2-1_54KZV_2016-01-23_final.stac-item
2016-01-23 10:15:08	ga_s2am_ard_3-2-1_55KBQ_2016-01-23_final.stac-item
2016-01-23 10:15:08	ga_s2am_ard_3-2-1_55KBR_2016-01-23_final.stac-item
2016-01-31 11:12:11	ga_s2am_ard_3-2-1_51KZQ_2016-01-31_final.stac-item
2016-01-31 11:12:11	ga_s2am_ard_3-2-1_51KZR_2016-01-31_final.stac-item
2016-01-31 11:12:11	ga_s2am_ard_3-2-1_52KBA_2016-01-31_final.stac-item
2016-01-31 11:12:11	ga_s2am_ard_3-2-1_52KCA_2016-01-31_final.stac-item
2016-01-31 11:12:11	ga_s2am_ard_3-2-1_52KDA_2016-01-31_final.stac-item
2016-01-31 11:12:11	ga_s2am_ard_3-2-1_52KEA_2016-01-31_final.stac-item
2023-05-02 10:33:13	ga_s2am_ard_3-2-1_54KUA_2023-05-02_final
2023-05-02 10:33:17	ga_s2am_ard_3-2-1_54KTA_2023-05-02_final
2023-05-02 10:33:17	ga_s2am_ard_3-2-1_53KRR_2023-05-02_final
2023-05-02 10:33:20	ga_s2am_ard_3-2-1_53KQR_2023-05-02_final
2023-05-03 10:02:58	ga_s2am_ard_3-2-1_55KER_2023-05-03_final
2023-05-03 10:03:03	ga_s2am_ard_3-2-1_55KDR_2023-05-03_final
2023-05-03 10:03:06	ga_s2am_ard_3-2-1_55KCR_2023-05-03_final
2023-05-03 10:03:09	ga_s2am_ard_3-2-1_55KBR_2023-05-03_final
2023-05-03 10:03:10	ga_s2am_ard_3-2-1_54KZA_2023-05-03_final
2023-05-03 10:03:24	ga_s2am_ard_3-2-1_54KZV_2023-05-03_final
2023-05-06 11:53:47	ga_s2am_ard_3-2-1_50KQA_2023-05-06_final
2023-05-06 11:53:50	ga_s2am_ard_3-2-1_50KPA_2023-05-06_final
2023-05-06 11:53:54	ga_s2am_ard_3-2-1_50KNA_2023-05-06_final
2023-05-06 11:53:57	ga_s2am_ard_3-2-1_50KMA_2023-05-06_final
2023-05-07 11:23:35	ga_s2am_ard_3-2-1_52KBA_2023-05-07_final
2023-05-07 11:23:35	ga_s2am_ard_3-2-1_51KZR_2023-05-07_final
2023-05-07 11:23:39	ga_s2am_ard_3-2-1_51KYR_2023-05-07_final
2023-05-07 11:23:43	ga_s2am_ard_3-2-1_51KXR_2023-05-07_final
2023-05-07 11:23:49	ga_s2am_ard_3-2-1_52KBV_2023-05-07_final
2023-05-07 11:23:50	ga_s2am_ard_3-2-1_51KZQ_2023-05-07_final
2023-05-07 11:23:54	ga_s2am_ard_3-2-1_51KYQ_2023-05-07_final
2023-05-08 10:53:21	ga_s2am_ard_3-2-1_53KMR_2023-05-08_final
2023-05-08 10:53:25	ga_s2am_ard_3-2-1_53KLR_2023-05-08_final
2023-05-08 10:53:28	ga_s2am_ard_3-2-1_53KKR_2023-05-08_final
2023-05-08 10:53:28	ga_s2am_ard_3-2-1_52KHA_2023-05-08_final
2023-05-08 10:53:32	ga_s2am_ard_3-2-1_52KGA_2023-05-08_final
2023-05-08 10:53:43	ga_s2am_ard_3-2-1_53KKQ_2023-05-08_final
2023-05-11 09:22:52	ga_s2am_ard_3-2-1_56KPA_2023-05-10_nrt
2023-05-12 10:33:12	ga_s2am_ard_3-2-1_54KUA_2023-05-12_final
2023-05-12 10:33:15	ga_s2am_ard_3-2-1_54KTA_2023-05-12_final
2023-05-12 10:33:16	ga_s2am_ard_3-2-1_53KRR_2023-05-12_final
2023-05-12 10:33:19	ga_s2am_ard_3-2-1_53KQR_2023-05-12_final
2023-05-12 10:33:23	ga_s2am_ard_3-2-1_53KPR_2023-05-12_final
2023-05-12 10:33:26	ga_s2am_ard_3-2-1_53KRQ_2023-05-12_final
2023-05-12 10:33:26	ga_s2am_ard_3-2-1_54KTV_2023-05-12_final
2023-05-12 10:33:28	ga_s2am_ard_3-2-1_53KQQ_2023-05-12_final
2023-05-12 10:33:29	ga_s2am_ard_3-2-1_53KPR_2023-05-12_final
2023-05-12 12:13:53	ga_s2am_ard_3-2-1_50KKA_2023-05-12_final
2023-05-28 10:53:37	ga_s2am_ard_3-2-1_53KLR_2023-05-28_final
2023-05-28 10:53:38	ga_s2am_ard_3-2-1_52KHA_2023-05-28_final
2023-05-28 10:53:39	ga_s2am_ard_3-2-1_52KGA_2023-05-28_final
2023-05-28 10:53:50	ga_s2am_ard_3-2-1_52KGV_2023-05-28_final
2023-05-30 09:53:00	ga_s2am_ard_3-2-1_55KGR_2023-05-30_final
2023-05-30 09:53:04	ga_s2am_ard_3-2-1_55KFR_2023-05-30_final
2023-05-30 09:53:07	ga_s2am_ard_3-2-1_55KER_2023-05-30_final
2023-05-30 09:53:11	ga_s2am_ard_3-2-1_55KDR_2023-05-30_final
2023-05-30 11:33:42	ga_s2am_ard_3-2-1_51KXR_2023-05-30_final
2023-05-30 11:33:45	ga_s2am_ard_3-2-1_51KWR_2023-05-30_final
2023-05-30 11:33:49	ga_s2am_ard_3-2-1_51KVR_2023-05-30_final

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

All years