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
2016-05-26 09:51:11	ga_s2am_ard_3-2-1_55KEU_2016-05-26_final.stac-item
2016-05-26 09:51:11	ga_s2am_ard_3-2-1_55KFU_2016-05-26_final.stac-item
2016-05-26 09:51:11	ga_s2am_ard_3-2-1_55KGT_2016-05-26_final.stac-item
2016-05-26 09:51:11	ga_s2am_ard_3-2-1_55KGU_2016-05-26_final.stac-item
2016-05-29 10:00:38	ga_s2am_ard_3-2-1_54KZC_2016-05-29_final.stac-item
2016-05-29 10:00:38	ga_s2am_ard_3-2-1_55KBU_2016-05-29_final.stac-item
2016-05-29 10:00:38	ga_s2am_ard_3-2-1_55KCU_2016-05-29_final.stac-item
2016-05-29 10:00:38	ga_s2am_ard_3-2-1_55KDU_2016-05-29_final.stac-item
2016-05-29 10:00:38	ga_s2am_ard_3-2-1_55KEU_2016-05-29_final.stac-item
2016-05-31 10:38:44	ga_s2am_ard_3-2-1_53KMU_2016-05-31_final.stac-item
2016-05-31 10:38:44	ga_s2am_ard_3-2-1_53KNU_2016-05-31_final.stac-item
2016-05-31 10:38:44	ga_s2am_ard_3-2-1_53KPU_2016-05-31_final.stac-item
2016-05-31 10:38:44	ga_s2am_ard_3-2-1_53KQU_2016-05-31_final.stac-item
2016-06-22 09:42:14	ga_s2am_ard_3-2-1_56KLD_2016-06-22_final.stac-item
2016-06-22 09:42:14	ga_s2am_ard_3-2-1_55KGT_2016-06-22_final.stac-item
2016-06-25 09:51:06	ga_s2am_ard_3-2-1_55KEU_2016-06-25_final.stac-item
2016-06-25 09:51:06	ga_s2am_ard_3-2-1_55KFU_2016-06-25_final.stac-item
2016-06-25 09:51:06	ga_s2am_ard_3-2-1_55KGT_2016-06-25_final.stac-item
2016-06-25 09:51:06	ga_s2am_ard_3-2-1_55KGU_2016-06-25_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_51KVU_2016-06-25_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_51KYU_2016-06-25_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_51KXU_2016-06-25_final
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_51KWU_2016-06-25_final
2016-07-15 09:51:09	ga_s2am_ard_3-2-1_55KEU_2016-07-15_final.stac-item
2016-07-15 09:51:09	ga_s2am_ard_3-2-1_55KFU_2016-07-15_final.stac-item
2016-07-15 09:51:09	ga_s2am_ard_3-2-1_55KGT_2016-07-15_final.stac-item
2016-07-15 09:51:09	ga_s2am_ard_3-2-1_55KGU_2016-07-15_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_54KTD_2016-07-27_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_54KUD_2016-07-27_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_54KVD_2016-07-27_final.stac-item
2016-07-28 10:00:36	ga_s2am_ard_3-2-1_55KBU_2016-07-28_final.stac-item
2016-07-28 10:00:36	ga_s2am_ard_3-2-1_55KCU_2016-07-28_final.stac-item
2016-07-28 10:00:36	ga_s2am_ard_3-2-1_55KDU_2016-07-28_final.stac-item
2016-07-28 10:00:36	ga_s2am_ard_3-2-1_55KEU_2016-07-28_final.stac-item
2016-07-30 10:38:47	ga_s2am_ard_3-2-1_53KMU_2016-07-30_final.stac-item
2016-07-30 10:38:47	ga_s2am_ard_3-2-1_53KNU_2016-07-30_final.stac-item
2016-07-30 10:38:47	ga_s2am_ard_3-2-1_53KPU_2016-07-30_final.stac-item
2016-07-30 10:38:47	ga_s2am_ard_3-2-1_53KQU_2016-07-30_final.stac-item
2019-03-18 10:12:14	ga_s2am_ard_3-2-1_55KCU_2019-03-18_final.stac-item
2019-03-18 10:12:18	ga_s2am_ard_3-2-1_55KBU_2019-03-18_final.stac-item
2019-03-18 10:12:19	ga_s2am_ard_3-2-1_54KZD_2019-03-18_final.stac-item
2019-03-18 10:12:22	ga_s2am_ard_3-2-1_54KYD_2019-03-18_final.stac-item
2019-03-18 10:12:25	ga_s2am_ard_3-2-1_54KXD_2019-03-18_final.stac-item
2019-03-18 10:12:33	ga_s2am_ard_3-2-1_54KZC_2019-03-18_final.stac-item
2019-03-18 10:12:37	ga_s2am_ard_3-2-1_54KYC_2019-03-18_final.stac-item
2019-03-20 10:52:31	ga_s2am_ard_3-2-1_53KNU_2019-03-20_final.stac-item
2019-03-20 10:52:35	ga_s2am_ard_3-2-1_53KMU_2019-03-20_final.stac-item
2019-03-20 10:52:39	ga_s2am_ard_3-2-1_53KLU_2019-03-20_final.stac-item
2019-03-20 10:52:42	ga_s2am_ard_3-2-1_53KKU_2019-03-20_final.stac-item
2019-03-20 10:52:42	ga_s2am_ard_3-2-1_52KHD_2019-03-20_final.stac-item
2019-03-20 10:52:57	ga_s2am_ard_3-2-1_52KHC_2019-03-20_final.stac-item
2019-03-24 10:32:24	ga_s2am_ard_3-2-1_54KVD_2019-03-24_final.stac-item
2019-03-24 10:32:28	ga_s2am_ard_3-2-1_54KUD_2019-03-24_final.stac-item
2019-03-24 10:32:31	ga_s2am_ard_3-2-1_54KTD_2019-03-24_final.stac-item
2019-03-24 10:32:32	ga_s2am_ard_3-2-1_53KRU_2019-03-24_final.stac-item
2019-03-24 10:32:35	ga_s2am_ard_3-2-1_53KQU_2019-03-24_final.stac-item
2019-03-24 10:32:46	ga_s2am_ard_3-2-1_53KRT_2019-03-24_final.stac-item
2019-03-24 10:32:50	ga_s2am_ard_3-2-1_53KQT_2019-03-24_final.stac-item
2019-03-29 09:42:10	ga_s2am_ard_3-2-1_56KLD_2019-03-29_final.stac-item
2019-03-29 09:42:33	ga_s2am_ard_3-2-1_55KGT_2019-03-29_final.stac-item
2019-03-29 11:22:48	ga_s2am_ard_3-2-1_52KCD_2019-03-29_final.stac-item
2019-03-29 11:22:51	ga_s2am_ard_3-2-1_52KBD_2019-03-29_final.stac-item
2019-03-29 11:22:52	ga_s2am_ard_3-2-1_51KZU_2019-03-29_final.stac-item
2019-03-29 11:22:55	ga_s2am_ard_3-2-1_51KYU_2019-03-29_final.stac-item
2019-03-29 11:23:00	ga_s2am_ard_3-2-1_51KXU_2019-03-29_final.stac-item
2019-03-29 11:23:06	ga_s2am_ard_3-2-1_51KZT_2019-03-29_final.stac-item
2019-03-29 11:23:10	ga_s2am_ard_3-2-1_51KYT_2019-03-29_final.stac-item
2019-03-31 10:22:24	ga_s2am_ard_3-2-1_54KXD_2019-03-31_final.stac-item
2019-03-31 10:22:28	ga_s2am_ard_3-2-1_54KWD_2019-03-31_final.stac-item
2019-03-31 10:22:31	ga_s2am_ard_3-2-1_54KVD_2019-03-31_final.stac-item
2019-03-31 10:22:35	ga_s2am_ard_3-2-1_54KUD_2019-03-31_final.stac-item
2019-04-08 11:22:50	ga_s2am_ard_3-2-1_52KCD_2019-04-08_final.stac-item
2019-04-08 11:22:53	ga_s2am_ard_3-2-1_52KBD_2019-04-08_final.stac-item
2019-04-08 11:22:54	ga_s2am_ard_3-2-1_51KZU_2019-04-08_final.stac-item
2019-04-08 11:22:57	ga_s2am_ard_3-2-1_51KYU_2019-04-08_final.stac-item
2019-04-08 11:23:02	ga_s2am_ard_3-2-1_51KXU_2019-04-08_final.stac-item
2019-04-08 11:23:08	ga_s2am_ard_3-2-1_51KZT_2019-04-08_final.stac-item
2019-04-08 11:23:11	ga_s2am_ard_3-2-1_51KYT_2019-04-08_final.stac-item
2019-04-10 10:22:25	ga_s2am_ard_3-2-1_54KXD_2019-04-10_final.stac-item
2019-04-10 10:22:29	ga_s2am_ard_3-2-1_54KWD_2019-04-10_final.stac-item
2019-04-10 10:22:32	ga_s2am_ard_3-2-1_54KVD_2019-04-10_final.stac-item
2019-04-10 10:22:36	ga_s2am_ard_3-2-1_54KUD_2019-04-10_final.stac-item
2019-07-22 10:32:30	ga_s2am_ard_3-2-1_54KVD_2019-07-22_final.stac-item
2019-07-22 10:32:34	ga_s2am_ard_3-2-1_54KUD_2019-07-22_final.stac-item
2019-07-22 10:32:38	ga_s2am_ard_3-2-1_54KTD_2019-07-22_final.stac-item
2019-07-22 10:32:38	ga_s2am_ard_3-2-1_53KRU_2019-07-22_final.stac-item
2019-07-22 10:32:42	ga_s2am_ard_3-2-1_53KQU_2019-07-22_final.stac-item
2019-08-01 10:32:30	ga_s2am_ard_3-2-1_54KVD_2019-08-01_final.stac-item
2019-08-01 10:32:34	ga_s2am_ard_3-2-1_54KUD_2019-08-01_final.stac-item
2019-08-01 10:32:37	ga_s2am_ard_3-2-1_54KTD_2019-08-01_final.stac-item
2019-08-01 10:32:38	ga_s2am_ard_3-2-1_53KRU_2019-08-01_final.stac-item
2019-08-01 10:32:41	ga_s2am_ard_3-2-1_53KQU_2019-08-01_final.stac-item
2019-08-01 10:32:52	ga_s2am_ard_3-2-1_53KRT_2019-08-01_final.stac-item
2019-08-01 10:32:56	ga_s2am_ard_3-2-1_53KQT_2019-08-01_final.stac-item
2019-08-11 10:32:29	ga_s2am_ard_3-2-1_54KVD_2019-08-11_final.stac-item
2019-08-11 10:32:33	ga_s2am_ard_3-2-1_54KUD_2019-08-11_final.stac-item
2019-08-11 10:32:36	ga_s2am_ard_3-2-1_54KTD_2019-08-11_final.stac-item
2019-08-11 10:32:37	ga_s2am_ard_3-2-1_53KRU_2019-08-11_final.stac-item
2019-08-11 10:32:40	ga_s2am_ard_3-2-1_53KQU_2019-08-11_final.stac-item
2019-08-11 10:32:51	ga_s2am_ard_3-2-1_53KRT_2019-08-11_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

All years