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
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KWQ_2016-04-23_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KXQ_2016-04-23_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KXR_2016-04-23_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KYQ_2016-04-23_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KYR_2016-04-23_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KZQ_2016-04-23_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KZR_2016-04-23_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_52KBA_2016-04-23_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_52KBV_2016-04-23_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_54KTA_2016-04-28_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_54KTV_2016-04-28_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_54KUA_2016-04-28_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_53KPQ_2016-04-28_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_53KPR_2016-04-28_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_53KQQ_2016-04-28_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_53KQR_2016-04-28_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_53KRQ_2016-04-28_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_53KRR_2016-04-28_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_54KZA_2016-04-29_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_54KZV_2016-04-29_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_55KBQ_2016-04-29_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_55KBR_2016-04-29_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_55KCQ_2016-04-29_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_55KCR_2016-04-29_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_55KDQ_2016-04-29_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_55KDR_2016-04-29_final.stac-item
2016-04-29 10:00:36	ga_s2am_ard_3-2-1_55KER_2016-04-29_final.stac-item
2016-05-20 09:32:24	ga_s2am_ard_3-2-1_56KNA_2016-05-20_final.stac-item
2016-05-20 09:32:24	ga_s2am_ard_3-2-1_56KLA_2016-05-20_final.stac-item
2016-05-20 09:32:24	ga_s2am_ard_3-2-1_56KLV_2016-05-20_final.stac-item
2016-05-20 09:32:24	ga_s2am_ard_3-2-1_56KMA_2016-05-20_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KTV_2016-05-25_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KUA_2016-05-25_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KUV_2016-05-25_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KVA_2016-05-25_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KVV_2016-05-25_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KWA_2016-05-25_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KWV_2016-05-25_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KXA_2016-05-25_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54KXV_2016-05-25_final.stac-item
2018-02-05 09:52:53	ga_s2am_ard_3-2-1_55KDR_2018-02-05_final.stac-item
2018-02-05 09:52:53	ga_s2am_ard_3-2-1_55KEQ_2018-02-05_final.stac-item
2018-02-05 09:52:53	ga_s2am_ard_3-2-1_55KER_2018-02-05_final.stac-item
2018-02-05 09:52:53	ga_s2am_ard_3-2-1_55KFQ_2018-02-05_final.stac-item
2018-02-05 09:52:53	ga_s2am_ard_3-2-1_55KFR_2018-02-05_final.stac-item
2018-02-05 09:52:53	ga_s2am_ard_3-2-1_55KGQ_2018-02-05_final.stac-item
2018-02-05 09:52:53	ga_s2am_ard_3-2-1_55KGR_2018-02-05_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KEA_2018-02-06_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KEV_2018-02-06_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KFA_2018-02-06_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KFV_2018-02-06_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KGA_2018-02-06_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KGV_2018-02-06_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KHA_2018-02-06_final.stac-item
2018-02-06 11:02:07	ga_s2am_ard_3-2-1_52KHV_2018-02-06_final.stac-item
2018-02-16 10:58:46	ga_s2am_ard_3-2-1_52KEA_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_52KFA_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_52KGA_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
2018-02-16 10:58:46	ga_s2am_ard_3-2-1_52KHA_2018-02-16_final.stac-item
2018-02-16 10:58:46	ga_s2am_ard_3-2-1_52KHV_2018-02-16_final.stac-item
2018-02-19 09:32:37	ga_s2am_ard_3-2-1_56KLA_2018-02-19_final.stac-item
2018-02-19 09:32:37	ga_s2am_ard_3-2-1_56KLV_2018-02-19_final.stac-item
2018-02-19 09:32:37	ga_s2am_ard_3-2-1_56KMA_2018-02-19_final.stac-item
2019-04-21 09:52:59	ga_s2am_ard_3-2-1_55KGR_2019-04-21_final.stac-item
2019-04-21 09:53:03	ga_s2am_ard_3-2-1_55KFR_2019-04-21_final.stac-item
2019-04-21 09:53:07	ga_s2am_ard_3-2-1_55KER_2019-04-21_final.stac-item
2019-04-21 09:53:10	ga_s2am_ard_3-2-1_55KDR_2019-04-21_final.stac-item
2019-04-21 09:53:14	ga_s2am_ard_3-2-1_55KGQ_2019-04-21_final.stac-item
2019-04-21 09:53:18	ga_s2am_ard_3-2-1_55KFQ_2019-04-21_final.stac-item
2019-04-21 09:53:21	ga_s2am_ard_3-2-1_55KEQ_2019-04-21_final.stac-item
2019-04-28 09:42:53	ga_s2am_ard_3-2-1_56KMA_2019-04-28_final.stac-item
2019-04-28 09:42:58	ga_s2am_ard_3-2-1_56KLA_2019-04-28_final.stac-item
2019-04-28 09:43:01	ga_s2am_ard_3-2-1_56KKA_2019-04-28_final.stac-item
2019-04-28 09:43:01	ga_s2am_ard_3-2-1_55KHR_2019-04-28_final.stac-item
2019-04-28 09:43:05	ga_s2am_ard_3-2-1_55KGR_2019-04-28_final.stac-item
2019-04-28 09:43:12	ga_s2am_ard_3-2-1_56KLV_2019-04-28_final.stac-item
2019-04-28 09:43:15	ga_s2am_ard_3-2-1_56KKV_2019-04-28_final.stac-item
2019-04-28 09:43:16	ga_s2am_ard_3-2-1_55KHQ_2019-04-28_final.stac-item
2019-04-28 09:43:19	ga_s2am_ard_3-2-1_55KGQ_2019-04-28_final.stac-item
2019-04-29 10:53:25	ga_s2am_ard_3-2-1_53KMR_2019-04-29_final.stac-item
2019-04-29 10:53:28	ga_s2am_ard_3-2-1_53KLR_2019-04-29_final.stac-item
2019-04-29 10:53:31	ga_s2am_ard_3-2-1_53KKR_2019-04-29_final.stac-item
2019-04-29 10:53:32	ga_s2am_ard_3-2-1_52KHA_2019-04-29_final.stac-item
2019-04-29 10:53:36	ga_s2am_ard_3-2-1_52KGA_2019-04-29_final.stac-item
2019-04-29 10:53:39	ga_s2am_ard_3-2-1_53KMQ_2019-04-29_final.stac-item
2019-04-29 10:53:43	ga_s2am_ard_3-2-1_53KLQ_2019-04-29_final.stac-item
2019-04-29 10:53:46	ga_s2am_ard_3-2-1_53KKQ_2019-04-29_final.stac-item
2019-04-29 10:53:46	ga_s2am_ard_3-2-1_52KHV_2019-04-29_final.stac-item
2019-04-29 10:53:50	ga_s2am_ard_3-2-1_52KGV_2019-04-29_final.stac-item
2019-05-01 09:53:00	ga_s2am_ard_3-2-1_55KGR_2019-05-01_final.stac-item
2019-05-01 09:53:04	ga_s2am_ard_3-2-1_55KFR_2019-05-01_final.stac-item
2019-05-01 09:53:07	ga_s2am_ard_3-2-1_55KER_2019-05-01_final.stac-item
2019-05-01 09:53:11	ga_s2am_ard_3-2-1_55KDR_2019-05-01_final.stac-item
2019-05-01 09:53:15	ga_s2am_ard_3-2-1_55KGQ_2019-05-01_final.stac-item
2019-05-01 09:53:18	ga_s2am_ard_3-2-1_55KFQ_2019-05-01_final.stac-item
2019-05-01 09:53:22	ga_s2am_ard_3-2-1_55KEQ_2019-05-01_final.stac-item
2019-05-03 12:13:58	ga_s2am_ard_3-2-1_50KKA_2019-05-03_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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