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
2019-07-09 12:03:57	ga_s2am_ard_3-2-1_50KMA_2019-07-09_final.stac-item
2019-07-09 12:04:01	ga_s2am_ard_3-2-1_50KLA_2019-07-09_final.stac-item
2019-07-09 12:04:04	ga_s2am_ard_3-2-1_50KKA_2019-07-09_final.stac-item
2019-07-09 12:04:04	ga_s2am_ard_3-2-1_49KHR_2019-07-09_final.stac-item
2019-07-09 12:04:09	ga_s2am_ard_3-2-1_50KLA_2019-07-09_final.stac-item
2019-07-09 12:04:10	ga_s2am_ard_3-2-1_50KKA_2019-07-09_final.stac-item
2019-07-09 12:04:10	ga_s2am_ard_3-2-1_49KHR_2019-07-09_final.stac-item
2019-07-09 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2019-07-09_final.stac-item
2019-07-09 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2019-07-09_final.stac-item
2019-07-09 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2019-07-09_final.stac-item
2019-07-17 11:23:40	ga_s2am_ard_3-2-1_52KBA_2019-07-17_final.stac-item
2019-07-17 11:23:41	ga_s2am_ard_3-2-1_51KZR_2019-07-17_final.stac-item
2019-07-17 11:23:44	ga_s2am_ard_3-2-1_51KYR_2019-07-17_final.stac-item
2019-07-17 11:23:48	ga_s2am_ard_3-2-1_51KXR_2019-07-17_final.stac-item
2019-07-17 11:23:55	ga_s2am_ard_3-2-1_51KZQ_2019-07-17_final.stac-item
2019-07-17 11:23:59	ga_s2am_ard_3-2-1_51KYQ_2019-07-17_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
2019-08-12 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
2019-08-12 11:44:09	ga_s2am_ard_3-2-1_50KQV_2019-08-12_final.stac-item
2019-12-27 11:33:33	ga_s2am_ard_3-2-1_51KXR_2019-12-27_final.stac-item
2019-12-27 11:33:36	ga_s2am_ard_3-2-1_51KWR_2019-12-27_final.stac-item
2019-12-27 11:33:39	ga_s2am_ard_3-2-1_51KVR_2019-12-27_final.stac-item
2019-12-27 11:33:42	ga_s2am_ard_3-2-1_51KUR_2019-12-27_final.stac-item
2020-09-23 11:03:27	ga_s2am_ard_3-2-1_52KHA_2020-09-23_final.stac-item
2020-09-23 11:03:32	ga_s2am_ard_3-2-1_52KGA_2020-09-23_final.stac-item
2020-09-23 11:03:36	ga_s2am_ard_3-2-1_52KFA_2020-09-23_final.stac-item
2020-09-23 11:03:38	ga_s2am_ard_3-2-1_52KHV_2020-09-23_final.stac-item
2020-09-23 11:03:40	ga_s2am_ard_3-2-1_52KEA_2020-09-23_final.stac-item
2020-09-23 11:03:47	ga_s2am_ard_3-2-1_52KGV_2020-09-23_final.stac-item
2020-09-28 10:13:10	ga_s2am_ard_3-2-1_55KBR_2020-09-28_final.stac-item
2020-09-28 10:13:10	ga_s2am_ard_3-2-1_54KZA_2020-09-28_final.stac-item
2020-09-28 10:13:14	ga_s2am_ard_3-2-1_54KYA_2020-09-28_final.stac-item
2020-09-28 10:13:17	ga_s2am_ard_3-2-1_54KXA_2020-09-28_final.stac-item
2020-09-28 10:13:21	ga_s2am_ard_3-2-1_54KWA_2020-09-28_final.stac-item
2020-09-28 10:13:25	ga_s2am_ard_3-2-1_54KZV_2020-09-28_final.stac-item
2020-09-28 10:13:28	ga_s2am_ard_3-2-1_54KYV_2020-09-28_final.stac-item
2020-10-05 10:03:04	ga_s2am_ard_3-2-1_55KER_2020-10-05_final.stac-item
2020-10-05 10:03:08	ga_s2am_ard_3-2-1_55KDR_2020-10-05_final.stac-item
2020-10-05 10:03:12	ga_s2am_ard_3-2-1_55KCR_2020-10-05_final.stac-item
2020-10-05 10:03:15	ga_s2am_ard_3-2-1_55KBR_2020-10-05_final.stac-item
2020-10-05 10:03:15	ga_s2am_ard_3-2-1_54KZA_2020-10-05_final.stac-item
2020-10-05 10:03:30	ga_s2am_ard_3-2-1_54KZV_2020-10-05_final.stac-item
2020-10-07 10:43:20	ga_s2am_ard_3-2-1_53KQR_2020-10-07_final.stac-item
2020-10-07 10:43:25	ga_s2am_ard_3-2-1_53KPR_2020-10-07_final.stac-item
2020-10-07 10:43:28	ga_s2am_ard_3-2-1_53KNR_2020-10-07_final.stac-item
2020-10-07 10:43:32	ga_s2am_ard_3-2-1_53KMR_2020-10-07_final.stac-item
2020-10-10 10:53:27	ga_s2am_ard_3-2-1_53KMR_2020-10-10_final.stac-item
2020-10-10 10:53:31	ga_s2am_ard_3-2-1_53KLR_2020-10-10_final.stac-item
2020-10-10 10:53:34	ga_s2am_ard_3-2-1_53KKR_2020-10-10_final.stac-item
2020-10-10 10:53:34	ga_s2am_ard_3-2-1_52KHA_2020-10-10_final.stac-item
2020-10-10 10:53:38	ga_s2am_ard_3-2-1_52KGA_2020-10-10_final.stac-item
2020-10-10 10:53:49	ga_s2am_ard_3-2-1_52KHV_2020-10-10_final.stac-item
2020-10-10 10:53:52	ga_s2am_ard_3-2-1_52KGV_2020-10-10_final.stac-item
2020-10-13 11:03:28	ga_s2am_ard_3-2-1_52KHA_2020-10-13_final.stac-item
2020-10-13 11:03:33	ga_s2am_ard_3-2-1_52KGA_2020-10-13_final.stac-item
2020-10-13 11:03:37	ga_s2am_ard_3-2-1_52KFA_2020-10-13_final.stac-item
2020-10-13 11:03:39	ga_s2am_ard_3-2-1_52KHV_2020-10-13_final.stac-item
2020-10-13 11:03:40	ga_s2am_ard_3-2-1_52KEA_2020-10-13_final.stac-item
2020-10-13 11:03:47	ga_s2am_ard_3-2-1_52KGV_2020-10-13_final.stac-item
2020-10-16 11:13:36	ga_s2am_ard_3-2-1_52KEA_2020-10-16_final.stac-item
2020-10-16 11:13:39	ga_s2am_ard_3-2-1_52KDA_2020-10-16_final.stac-item
2020-10-16 11:13:42	ga_s2am_ard_3-2-1_52KCA_2020-10-16_final.stac-item
2020-10-16 11:13:45	ga_s2am_ard_3-2-1_52KBA_2020-10-16_final.stac-item
2020-10-16 11:13:46	ga_s2am_ard_3-2-1_51KZR_2020-10-16_final.stac-item
2020-10-16 11:14:00	ga_s2am_ard_3-2-1_51KZQ_2020-10-16_final.stac-item
2020-11-05 11:13:35	ga_s2am_ard_3-2-1_52KEA_2020-11-05_final.stac-item
2020-11-05 11:13:38	ga_s2am_ard_3-2-1_52KDA_2020-11-05_final.stac-item
2020-11-05 11:13:41	ga_s2am_ard_3-2-1_52KCA_2020-11-05_final.stac-item
2020-11-05 11:13:44	ga_s2am_ard_3-2-1_52KBA_2020-11-05_final.stac-item
2020-11-05 11:13:45	ga_s2am_ard_3-2-1_51KZR_2020-11-05_final.stac-item
2020-11-05 11:13:59	ga_s2am_ard_3-2-1_51KZQ_2020-11-05_final.stac-item
2022-03-18 10:33:17	ga_s2am_ard_3-2-1_54KUA_2022-03-18_final.stac-item
2022-03-18 10:33:20	ga_s2am_ard_3-2-1_54KTA_2022-03-18_final.stac-item
2022-03-18 10:33:20	ga_s2am_ard_3-2-1_53KRR_2022-03-18_final.stac-item
2022-03-18 10:33:24	ga_s2am_ard_3-2-1_53KQR_2022-03-18_final.stac-item
2022-03-18 10:33:28	ga_s2am_ard_3-2-1_53KPR_2022-03-18_final.stac-item
2022-03-18 10:33:35	ga_s2am_ard_3-2-1_53KRQ_2022-03-18_final.stac-item
2022-03-18 10:33:38	ga_s2am_ard_3-2-1_53KQQ_2022-03-18_final.stac-item
2022-03-18 12:13:58	ga_s2am_ard_3-2-1_50KKA_2022-03-18_final.stac-item
2022-03-18 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-03-18_final.stac-item
2022-03-18 12:14:02	ga_s2am_ard_3-2-1_49KGR_2022-03-18_final.stac-item
2022-03-18 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2022-03-18_final.stac-item
2022-03-18 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-03-18_final.stac-item
2022-03-22 10:13:08	ga_s2am_ard_3-2-1_55KBR_2022-03-22_final.stac-item
2022-03-22 10:13:08	ga_s2am_ard_3-2-1_54KZA_2022-03-22_final.stac-item
2022-03-22 10:13:12	ga_s2am_ard_3-2-1_54KYA_2022-03-22_final.stac-item
2022-03-22 10:13:15	ga_s2am_ard_3-2-1_54KXA_2022-03-22_final.stac-item
2022-03-22 10:13:19	ga_s2am_ard_3-2-1_54KWA_2022-03-22_final.stac-item
2022-03-22 10:13:22	ga_s2am_ard_3-2-1_54KZV_2022-03-22_final.stac-item
2022-03-22 10:13:26	ga_s2am_ard_3-2-1_54KYV_2022-03-22_final.stac-item
2022-03-27 11:03:25	ga_s2am_ard_3-2-1_52KHA_2022-03-27_final.stac-item
2022-03-27 11:03:30	ga_s2am_ard_3-2-1_52KGA_2022-03-27_final.stac-item
2022-03-27 11:03:34	ga_s2am_ard_3-2-1_52KFA_2022-03-27_final.stac-item
2022-03-27 11:03:36	ga_s2am_ard_3-2-1_52KHV_2022-03-27_final.stac-item
2022-03-27 11:03:37	ga_s2am_ard_3-2-1_52KEA_2022-03-27_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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