Search ga_s2bm_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
2017-10-13 09:52:00	ga_s2bm_ard_3-2-1_55KDP_2017-10-13_final.stac-item
2017-10-13 09:52:00	ga_s2bm_ard_3-2-1_55KDQ_2017-10-13_final.stac-item
2019-09-20 09:46:37	ga_s2bm_ard_3-2-1_55HDB_2019-09-20_final.stac-item
2019-09-20 09:46:48	ga_s2bm_ard_3-2-1_55HDA_2019-09-20_final.stac-item
2019-09-20 09:47:03	ga_s2bm_ard_3-2-1_55HDV_2019-09-20_final.stac-item
2019-09-20 09:47:17	ga_s2bm_ard_3-2-1_55HDU_2019-09-20_final.stac-item
2019-09-20 09:47:32	ga_s2bm_ard_3-2-1_55HDT_2019-09-20_final.stac-item
2019-09-20 09:47:46	ga_s2bm_ard_3-2-1_55HDS_2019-09-20_final.stac-item
2019-09-20 09:48:01	ga_s2bm_ard_3-2-1_55GDR_2019-09-20_final.stac-item
2019-09-20 09:48:15	ga_s2bm_ard_3-2-1_55GDQ_2019-09-20_final.stac-item
2019-09-20 09:48:30	ga_s2bm_ard_3-2-1_55GDP_2019-09-20_final.stac-item
2019-09-20 09:48:44	ga_s2bm_ard_3-2-1_55GDN_2019-09-20_final.stac-item
2019-09-23 09:55:17	ga_s2bm_ard_3-2-1_55JDG_2019-09-23_final.stac-item
2019-09-23 09:55:32	ga_s2bm_ard_3-2-1_55JDF_2019-09-23_final.stac-item
2019-09-23 09:55:46	ga_s2bm_ard_3-2-1_55HDE_2019-09-23_final.stac-item
2019-09-23 09:56:01	ga_s2bm_ard_3-2-1_55HDD_2019-09-23_final.stac-item
2019-09-23 09:56:15	ga_s2bm_ard_3-2-1_55HDC_2019-09-23_final.stac-item
2019-09-23 09:56:30	ga_s2bm_ard_3-2-1_55HDB_2019-09-23_final.stac-item
2019-09-27 09:38:35	ga_s2bm_ard_3-2-1_55GDP_2019-09-27_final.stac-item
2019-09-27 09:38:49	ga_s2bm_ard_3-2-1_55GDN_2019-09-27_final.stac-item
2019-09-30 09:46:21	ga_s2bm_ard_3-2-1_55HDC_2019-09-30_final.stac-item
2019-09-30 09:46:35	ga_s2bm_ard_3-2-1_55HDB_2019-09-30_final.stac-item
2019-09-30 09:46:49	ga_s2bm_ard_3-2-1_55HDA_2019-09-30_final.stac-item
2019-09-30 09:46:59	ga_s2bm_ard_3-2-1_55HDV_2019-09-30_final.stac-item
2019-09-30 09:47:06	ga_s2bm_ard_3-2-1_55HDV_2019-09-30_final.stac-item
2019-09-30 09:47:19	ga_s2bm_ard_3-2-1_55HDU_2019-09-30_final.stac-item
2019-09-30 09:47:33	ga_s2bm_ard_3-2-1_55HDT_2019-09-30_final.stac-item
2019-09-30 09:47:48	ga_s2bm_ard_3-2-1_55HDS_2019-09-30_final.stac-item
2019-09-30 09:48:02	ga_s2bm_ard_3-2-1_55GDR_2019-09-30_final.stac-item
2019-09-30 09:48:17	ga_s2bm_ard_3-2-1_55GDQ_2019-09-30_final.stac-item
2019-09-30 09:48:31	ga_s2bm_ard_3-2-1_55GDP_2019-09-30_final.stac-item
2019-09-30 09:48:45	ga_s2bm_ard_3-2-1_55GDN_2019-09-30_final.stac-item
2019-10-07 09:37:52	ga_s2bm_ard_3-2-1_55HDS_2019-10-07_final.stac-item
2019-10-07 09:38:06	ga_s2bm_ard_3-2-1_55GDR_2019-10-07_final.stac-item
2019-10-07 09:38:20	ga_s2bm_ard_3-2-1_55GDQ_2019-10-07_final.stac-item
2019-10-07 09:38:26	ga_s2bm_ard_3-2-1_55GDP_2019-10-07_final.stac-item
2019-10-07 09:38:27	ga_s2bm_ard_3-2-1_55GDQ_2019-10-07_final.stac-item
2019-10-07 09:38:35	ga_s2bm_ard_3-2-1_55GDP_2019-10-07_final.stac-item
2019-10-07 09:38:50	ga_s2bm_ard_3-2-1_55GDN_2019-10-07_final.stac-item
2019-10-10 09:46:50	ga_s2bm_ard_3-2-1_55HDA_2019-10-10_final.stac-item
2019-10-10 09:48:03	ga_s2bm_ard_3-2-1_55GDR_2019-10-10_final.stac-item
2019-10-10 09:48:17	ga_s2bm_ard_3-2-1_55GDQ_2019-10-10_final.stac-item
2019-10-10 09:48:31	ga_s2bm_ard_3-2-1_55GDP_2019-10-10_final.stac-item
2019-10-10 09:48:46	ga_s2bm_ard_3-2-1_55GDN_2019-10-10_final.stac-item
2019-12-09 09:45:45	ga_s2bm_ard_3-2-1_55HDE_2019-12-09_final.stac-item
2019-12-09 09:46:00	ga_s2bm_ard_3-2-1_55HDD_2019-12-09_final.stac-item
2019-12-09 09:46:14	ga_s2bm_ard_3-2-1_55HDC_2019-12-09_final.stac-item
2019-12-09 09:46:29	ga_s2bm_ard_3-2-1_55HDB_2019-12-09_final.stac-item
2019-12-09 09:46:43	ga_s2bm_ard_3-2-1_55HDA_2019-12-09_final.stac-item
2019-12-09 09:46:58	ga_s2bm_ard_3-2-1_55HDV_2019-12-09_final.stac-item
2019-12-09 09:47:12	ga_s2bm_ard_3-2-1_55HDU_2019-12-09_final.stac-item
2019-12-09 09:47:27	ga_s2bm_ard_3-2-1_55HDT_2019-12-09_final.stac-item
2019-12-09 09:47:41	ga_s2bm_ard_3-2-1_55HDS_2019-12-09_final.stac-item
2019-12-09 09:47:56	ga_s2bm_ard_3-2-1_55GDR_2019-12-09_final.stac-item
2019-12-09 09:48:05	ga_s2bm_ard_3-2-1_55GDQ_2019-12-09_final.stac-item
2019-12-09 09:48:12	ga_s2bm_ard_3-2-1_55GDQ_2019-12-09_final.stac-item
2019-12-09 09:48:25	ga_s2bm_ard_3-2-1_55GDP_2019-12-09_final.stac-item
2019-12-09 09:48:39	ga_s2bm_ard_3-2-1_55GDN_2019-12-09_final.stac-item
2019-12-19 09:46:29	ga_s2bm_ard_3-2-1_55HDB_2019-12-19_final.stac-item
2019-12-19 09:46:44	ga_s2bm_ard_3-2-1_55HDA_2019-12-19_final.stac-item
2019-12-19 09:46:59	ga_s2bm_ard_3-2-1_55HDV_2019-12-19_final.stac-item
2019-12-19 09:47:13	ga_s2bm_ard_3-2-1_55HDU_2019-12-19_final.stac-item
2019-12-19 09:47:28	ga_s2bm_ard_3-2-1_55HDT_2019-12-19_final.stac-item
2019-12-19 09:47:42	ga_s2bm_ard_3-2-1_55HDS_2019-12-19_final.stac-item
2019-12-19 09:47:57	ga_s2bm_ard_3-2-1_55GDR_2019-12-19_final.stac-item
2019-12-19 09:48:06	ga_s2bm_ard_3-2-1_55GDQ_2019-12-19_final.stac-item
2019-12-19 09:48:12	ga_s2bm_ard_3-2-1_55GDQ_2019-12-19_final.stac-item
2019-12-19 09:48:25	ga_s2bm_ard_3-2-1_55GDP_2019-12-19_final.stac-item
2019-12-19 09:48:40	ga_s2bm_ard_3-2-1_55GDN_2019-12-19_final.stac-item
2020-05-17 09:47:18	ga_s2bm_ard_3-2-1_55HDU_2020-05-17_final.stac-item
2020-05-17 09:47:32	ga_s2bm_ard_3-2-1_55HDT_2020-05-17_final.stac-item
2020-05-17 09:47:47	ga_s2bm_ard_3-2-1_55HDS_2020-05-17_final.stac-item
2020-05-17 09:48:01	ga_s2bm_ard_3-2-1_55GDR_2020-05-17_final.stac-item
2020-05-17 09:48:16	ga_s2bm_ard_3-2-1_55GDQ_2020-05-17_final.stac-item
2020-05-17 09:48:30	ga_s2bm_ard_3-2-1_55GDP_2020-05-17_final.stac-item
2020-05-17 09:48:45	ga_s2bm_ard_3-2-1_55GDN_2020-05-17_final.stac-item
2020-05-27 09:45:52	ga_s2bm_ard_3-2-1_55HDE_2020-05-27_final.stac-item
2020-05-27 09:46:07	ga_s2bm_ard_3-2-1_55HDD_2020-05-27_final.stac-item
2020-05-27 09:46:21	ga_s2bm_ard_3-2-1_55HDC_2020-05-27_final.stac-item
2020-05-27 09:46:33	ga_s2bm_ard_3-2-1_55HDB_2020-05-27_final.stac-item
2020-05-27 09:46:39	ga_s2bm_ard_3-2-1_55HDB_2020-05-27_final.stac-item
2020-05-27 09:46:50	ga_s2bm_ard_3-2-1_55HDA_2020-05-27_final.stac-item
2020-05-27 09:47:05	ga_s2bm_ard_3-2-1_55HDV_2020-05-27_final.stac-item
2020-05-27 09:47:19	ga_s2bm_ard_3-2-1_55HDU_2020-05-27_final.stac-item
2020-05-27 09:47:34	ga_s2bm_ard_3-2-1_55HDT_2020-05-27_final.stac-item
2020-05-27 09:47:48	ga_s2bm_ard_3-2-1_55HDS_2020-05-27_final.stac-item
2020-05-27 09:48:03	ga_s2bm_ard_3-2-1_55GDR_2020-05-27_final.stac-item
2020-05-27 09:48:17	ga_s2bm_ard_3-2-1_55GDQ_2020-05-27_final.stac-item
2020-05-27 09:48:31	ga_s2bm_ard_3-2-1_55GDP_2020-05-27_final.stac-item
2020-05-27 09:48:46	ga_s2bm_ard_3-2-1_55GDN_2020-05-27_final.stac-item
2020-06-02 10:02:21	ga_s2bm_ard_3-2-1_55KDU_2020-06-02_final.stac-item
2020-06-02 10:02:35	ga_s2bm_ard_3-2-1_55KDT_2020-06-02_final.stac-item
2020-06-02 10:02:50	ga_s2bm_ard_3-2-1_55KDS_2020-06-02_final.stac-item
2020-06-02 10:03:04	ga_s2bm_ard_3-2-1_55KDR_2020-06-02_final.stac-item
2020-06-02 10:03:18	ga_s2bm_ard_3-2-1_55KDQ_2020-06-02_final.stac-item
2020-06-02 10:03:33	ga_s2bm_ard_3-2-1_55KDP_2020-06-02_final.stac-item
2020-06-02 10:03:48	ga_s2bm_ard_3-2-1_55JDN_2020-06-02_final.stac-item
2020-06-03 09:38:07	ga_s2bm_ard_3-2-1_55GDR_2020-06-03_final.stac-item
2020-06-03 09:38:22	ga_s2bm_ard_3-2-1_55GDQ_2020-06-03_final.stac-item
2020-06-03 09:38:36	ga_s2bm_ard_3-2-1_55GDP_2020-06-03_final.stac-item

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years