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
2019-06-30 09:56:06	ga_s2am_ard_3-2-1_55HDD_2019-06-30_final.stac-item
2019-07-27 09:45:31	ga_s2am_ard_3-2-1_55JDG_2019-07-27_final.stac-item
2019-07-27 09:45:42	ga_s2am_ard_3-2-1_55JDF_2019-07-27_final.stac-item
2019-07-27 09:45:56	ga_s2am_ard_3-2-1_55HDE_2019-07-27_final.stac-item
2019-07-27 09:46:10	ga_s2am_ard_3-2-1_55HDD_2019-07-27_final.stac-item
2019-07-27 09:46:25	ga_s2am_ard_3-2-1_55HDC_2019-07-27_final.stac-item
2019-07-27 09:46:39	ga_s2am_ard_3-2-1_55HDB_2019-07-27_final.stac-item
2019-07-27 09:46:54	ga_s2am_ard_3-2-1_55HDA_2019-07-27_final.stac-item
2019-07-30 09:53:00	ga_s2am_ard_3-2-1_55KDS_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
2019-07-30 09:53:26	ga_s2am_ard_3-2-1_55KDQ_2019-07-30_final.stac-item
2019-07-30 09:53:41	ga_s2am_ard_3-2-1_55KDP_2019-07-30_final.stac-item
2019-07-30 09:53:56	ga_s2am_ard_3-2-1_55JDN_2019-07-30_final.stac-item
2019-07-30 09:54:10	ga_s2am_ard_3-2-1_55JDM_2019-07-30_final.stac-item
2019-07-30 09:54:24	ga_s2am_ard_3-2-1_55JDL_2019-07-30_final.stac-item
2019-07-30 09:54:39	ga_s2am_ard_3-2-1_55JDK_2019-07-30_final.stac-item
2019-07-30 09:54:54	ga_s2am_ard_3-2-1_55JDJ_2019-07-30_final.stac-item
2019-07-30 09:55:08	ga_s2am_ard_3-2-1_55JDH_2019-07-30_final.stac-item
2019-07-30 09:55:23	ga_s2am_ard_3-2-1_55JDG_2019-07-30_final.stac-item
2019-07-30 09:55:37	ga_s2am_ard_3-2-1_55JDF_2019-07-30_final.stac-item
2019-07-30 09:55:52	ga_s2am_ard_3-2-1_55HDE_2019-07-30_final.stac-item
2019-08-02 10:01:40	ga_s2am_ard_3-2-1_55KDB_2019-08-02_final.stac-item
2019-08-02 10:01:54	ga_s2am_ard_3-2-1_55KDA_2019-08-02_final.stac-item
2019-08-02 10:02:09	ga_s2am_ard_3-2-1_55KDV_2019-08-02_final.stac-item
2019-08-02 10:02:24	ga_s2am_ard_3-2-1_55KDU_2019-08-02_final.stac-item
2019-08-02 10:02:38	ga_s2am_ard_3-2-1_55KDT_2019-08-02_final.stac-item
2019-08-02 10:02:53	ga_s2am_ard_3-2-1_55KDS_2019-08-02_final.stac-item
2019-08-02 10:03:07	ga_s2am_ard_3-2-1_55KDR_2019-08-02_final.stac-item
2019-08-02 10:03:21	ga_s2am_ard_3-2-1_55KDQ_2019-08-02_final.stac-item
2019-08-03 09:37:44	ga_s2am_ard_3-2-1_55HDT_2019-08-03_final.stac-item
2019-08-03 09:37:56	ga_s2am_ard_3-2-1_55HDS_2019-08-03_final.stac-item
2019-08-03 09:38:06	ga_s2am_ard_3-2-1_55GER_2019-08-03_final.stac-item
2019-08-03 09:38:10	ga_s2am_ard_3-2-1_55GDR_2019-08-03_final.stac-item
2019-08-03 09:38:21	ga_s2am_ard_3-2-1_55GEQ_2019-08-03_final.stac-item
2019-08-03 09:38:24	ga_s2am_ard_3-2-1_55GDQ_2019-08-03_final.stac-item
2019-08-03 09:38:35	ga_s2am_ard_3-2-1_55GEP_2019-08-03_final.stac-item
2019-08-03 09:38:39	ga_s2am_ard_3-2-1_55GDP_2019-08-03_final.stac-item
2019-08-03 09:38:50	ga_s2am_ard_3-2-1_55GEN_2019-08-03_final.stac-item
2019-08-03 09:38:53	ga_s2am_ard_3-2-1_55GDN_2019-08-03_final.stac-item
2019-08-06 09:45:30	ga_s2am_ard_3-2-1_55JDG_2019-08-06_final.stac-item
2019-08-06 09:45:41	ga_s2am_ard_3-2-1_55JDF_2019-08-06_final.stac-item
2019-08-06 09:45:55	ga_s2am_ard_3-2-1_55HDE_2019-08-06_final.stac-item
2019-08-06 09:46:10	ga_s2am_ard_3-2-1_55HDD_2019-08-06_final.stac-item
2019-08-06 09:46:24	ga_s2am_ard_3-2-1_55HDC_2019-08-06_final.stac-item
2019-08-06 09:46:39	ga_s2am_ard_3-2-1_55HDB_2019-08-06_final.stac-item
2019-08-06 09:46:53	ga_s2am_ard_3-2-1_55HDA_2019-08-06_final.stac-item
2019-08-06 09:47:08	ga_s2am_ard_3-2-1_55HDV_2019-08-06_final.stac-item
2019-08-06 09:47:22	ga_s2am_ard_3-2-1_55HDU_2019-08-06_final.stac-item
2019-08-06 09:47:37	ga_s2am_ard_3-2-1_55HDT_2019-08-06_final.stac-item
2019-08-12 10:01:39	ga_s2am_ard_3-2-1_55KDB_2019-08-12_final.stac-item
2019-08-12 10:01:54	ga_s2am_ard_3-2-1_55KDA_2019-08-12_final.stac-item
2019-08-12 10:02:08	ga_s2am_ard_3-2-1_55KDV_2019-08-12_final.stac-item
2019-08-12 10:02:23	ga_s2am_ard_3-2-1_55KDU_2019-08-12_final.stac-item
2019-08-12 10:02:37	ga_s2am_ard_3-2-1_55KDT_2019-08-12_final.stac-item
2019-08-12 10:02:52	ga_s2am_ard_3-2-1_55KDS_2019-08-12_final.stac-item
2019-08-12 10:03:06	ga_s2am_ard_3-2-1_55KDR_2019-08-12_final.stac-item
2019-08-12 10:03:20	ga_s2am_ard_3-2-1_55KDQ_2019-08-12_final.stac-item
2020-01-23 09:48:16	ga_s2am_ard_3-2-1_55GEP_2020-01-23_final.stac-item
2020-01-23 09:48:24	ga_s2am_ard_3-2-1_55GDP_2020-01-23_final.stac-item
2023-06-12 10:02:09	ga_s2am_ard_3-2-1_55KDV_2023-06-12_final
2023-06-12 10:02:23	ga_s2am_ard_3-2-1_55KDU_2023-06-12_final
2023-06-12 10:02:38	ga_s2am_ard_3-2-1_55KDT_2023-06-12_final
2023-06-12 10:02:52	ga_s2am_ard_3-2-1_55KDS_2023-06-12_final
2023-06-12 10:03:07	ga_s2am_ard_3-2-1_55KDR_2023-06-12_final
2023-06-12 10:03:21	ga_s2am_ard_3-2-1_55KDQ_2023-06-12_final
2023-06-13 09:37:44	ga_s2am_ard_3-2-1_55HDT_2023-06-13_final
2023-06-13 09:37:55	ga_s2am_ard_3-2-1_55HDS_2023-06-13_final
2023-06-13 09:38:06	ga_s2am_ard_3-2-1_55GER_2023-06-13_final
2023-06-13 09:38:09	ga_s2am_ard_3-2-1_55GDR_2023-06-13_final
2023-06-13 09:38:20	ga_s2am_ard_3-2-1_55GEQ_2023-06-13_final
2023-06-13 09:38:24	ga_s2am_ard_3-2-1_55GDQ_2023-06-13_final
2023-06-13 09:38:35	ga_s2am_ard_3-2-1_55GEP_2023-06-13_final
2023-06-13 09:38:37	ga_s2am_ard_3-2-1_55GDP_2023-06-13_final
2023-06-13 09:38:42	ga_s2am_ard_3-2-1_55GEP_2023-06-13_final
2023-06-13 09:38:42	ga_s2am_ard_3-2-1_55GEN_2023-06-13_final
2023-06-13 09:38:44	ga_s2am_ard_3-2-1_55GDP_2023-06-13_final
2023-06-13 09:38:49	ga_s2am_ard_3-2-1_55GEN_2023-06-13_final
2023-06-13 09:38:53	ga_s2am_ard_3-2-1_55GDN_2023-06-13_final
2023-06-13 09:39:04	ga_s2am_ard_3-2-1_55GEM_2023-06-13_final
2023-06-13 09:39:06	ga_s2am_ard_3-2-1_55GDM_2023-06-13_final
2023-06-15 10:09:53	ga_s2am_ard_3-2-1_55LDJ_2023-06-15_nrt
2023-06-15 10:10:07	ga_s2am_ard_3-2-1_55LDH_2023-06-15_nrt
2023-06-15 10:10:22	ga_s2am_ard_3-2-1_55LDG_2023-06-15_nrt
2023-06-16 09:45:30	ga_s2am_ard_3-2-1_55JDG_2023-06-16_final
2023-06-16 09:45:41	ga_s2am_ard_3-2-1_55JDF_2023-06-16_final
2023-06-16 09:45:55	ga_s2am_ard_3-2-1_55HDE_2023-06-16_final
2023-06-16 09:46:10	ga_s2am_ard_3-2-1_55HDD_2023-06-16_final
2023-06-16 09:46:24	ga_s2am_ard_3-2-1_55HDC_2023-06-16_final
2023-06-16 09:46:39	ga_s2am_ard_3-2-1_55HDB_2023-06-16_final
2023-06-16 09:46:53	ga_s2am_ard_3-2-1_55HDA_2023-06-16_final
2023-06-16 09:47:08	ga_s2am_ard_3-2-1_55HDV_2023-06-16_final
2023-06-16 09:47:22	ga_s2am_ard_3-2-1_55HDU_2023-06-16_final
2023-06-16 09:48:20	ga_s2am_ard_3-2-1_55GDQ_2023-06-16_final
2023-06-16 09:48:26	ga_s2am_ard_3-2-1_55GEP_2023-06-16_final
2023-06-16 09:48:35	ga_s2am_ard_3-2-1_55GDP_2023-06-16_final
2023-07-06 09:46:40	ga_s2am_ard_3-2-1_55HDB_2023-07-06_final
2023-07-06 09:46:54	ga_s2am_ard_3-2-1_55HDA_2023-07-06_final
2023-07-06 09:47:09	ga_s2am_ard_3-2-1_55HDV_2023-07-06_final
2023-07-06 09:47:23	ga_s2am_ard_3-2-1_55HDU_2023-07-06_final
2023-07-06 09:47:38	ga_s2am_ard_3-2-1_55HDT_2023-07-06_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