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
2019-08-06 10:33:59	ga_s2bm_ard_3-2-1_54JUT_2019-08-06_final.stac-item
2019-08-06 10:34:07	ga_s2bm_ard_3-2-1_53JRN_2019-08-06_final.stac-item
2019-08-06 10:34:07	ga_s2bm_ard_3-2-1_54JTT_2019-08-06_final.stac-item
2019-08-06 10:34:11	ga_s2bm_ard_3-2-1_53JQN_2019-08-06_final.stac-item
2019-08-06 10:34:15	ga_s2bm_ard_3-2-1_53JPN_2019-08-06_final.stac-item
2019-08-06 10:34:21	ga_s2bm_ard_3-2-1_53JNN_2019-08-06_final.stac-item
2019-08-15 09:23:46	ga_s2bm_ard_3-2-1_56JNT_2019-08-14_final.stac-item
2019-08-15 11:04:17	ga_s2bm_ard_3-2-1_52JGT_2019-08-15_final.stac-item
2019-08-15 11:04:21	ga_s2bm_ard_3-2-1_52JFT_2019-08-15_final.stac-item
2019-08-15 11:04:24	ga_s2bm_ard_3-2-1_52JET_2019-08-15_final.stac-item
2019-08-15 11:04:27	ga_s2bm_ard_3-2-1_52JDT_2019-08-15_final.stac-item
2019-10-13 09:53:39	ga_s2bm_ard_3-2-1_55JGN_2019-10-13_final.stac-item
2019-10-13 09:53:45	ga_s2bm_ard_3-2-1_55JFN_2019-10-13_final.stac-item
2019-10-13 09:53:48	ga_s2bm_ard_3-2-1_55JEN_2019-10-13_final.stac-item
2019-10-13 09:53:52	ga_s2bm_ard_3-2-1_55JDN_2019-10-13_final.stac-item
2019-10-14 09:23:41	ga_s2bm_ard_3-2-1_56JNT_2019-10-13_final.stac-item
2019-10-14 11:04:12	ga_s2bm_ard_3-2-1_52JGT_2019-10-14_final.stac-item
2019-10-14 11:04:16	ga_s2bm_ard_3-2-1_52JFT_2019-10-14_final.stac-item
2019-10-14 11:04:19	ga_s2bm_ard_3-2-1_52JET_2019-10-14_final.stac-item
2019-10-14 11:04:22	ga_s2bm_ard_3-2-1_52JDT_2019-10-14_final.stac-item
2019-10-28 10:44:04	ga_s2bm_ard_3-2-1_53JPN_2019-10-28_final.stac-item
2019-10-28 10:44:07	ga_s2bm_ard_3-2-1_53JNN_2019-10-28_final.stac-item
2019-10-28 10:44:11	ga_s2bm_ard_3-2-1_53JMN_2019-10-28_final.stac-item
2019-10-28 10:44:13	ga_s2bm_ard_3-2-1_53JLN_2019-10-28_final.stac-item
2019-11-02 11:34:16	ga_s2bm_ard_3-2-1_51JXN_2019-11-02_final.stac-item
2019-11-02 11:34:25	ga_s2bm_ard_3-2-1_51JWN_2019-11-02_final.stac-item
2019-11-02 11:34:29	ga_s2bm_ard_3-2-1_51JVN_2019-11-02_final.stac-item
2019-11-02 11:34:32	ga_s2bm_ard_3-2-1_51JUN_2019-11-02_final.stac-item
2019-11-02 11:34:36	ga_s2bm_ard_3-2-1_51JTN_2019-11-02_final.stac-item
2019-11-02 11:34:37	ga_s2bm_ard_3-2-1_50JRT_2019-11-02_final.stac-item
2019-11-03 09:23:40	ga_s2bm_ard_3-2-1_56JNT_2019-11-02_final.stac-item
2019-11-03 11:04:11	ga_s2bm_ard_3-2-1_52JGT_2019-11-03_final.stac-item
2019-11-03 11:04:15	ga_s2bm_ard_3-2-1_52JFT_2019-11-03_final.stac-item
2019-11-03 11:04:18	ga_s2bm_ard_3-2-1_52JET_2019-11-03_final.stac-item
2019-11-03 11:04:21	ga_s2bm_ard_3-2-1_52JDT_2019-11-03_final.stac-item
2019-11-04 10:33:52	ga_s2bm_ard_3-2-1_54JUT_2019-11-04_final.stac-item
2019-11-04 10:34:00	ga_s2bm_ard_3-2-1_53JRN_2019-11-04_final.stac-item
2019-11-04 10:34:00	ga_s2bm_ard_3-2-1_54JTT_2019-11-04_final.stac-item
2019-11-04 10:34:04	ga_s2bm_ard_3-2-1_53JQN_2019-11-04_final.stac-item
2019-11-04 10:34:07	ga_s2bm_ard_3-2-1_53JPN_2019-11-04_final.stac-item
2023-05-27 10:33:56	ga_s2bm_ard_3-2-1_54JUT_2023-05-27_final
2023-05-27 10:34:04	ga_s2bm_ard_3-2-1_53JRN_2023-05-27_final
2023-05-27 10:34:04	ga_s2bm_ard_3-2-1_54JTT_2023-05-27_final
2023-05-27 10:34:08	ga_s2bm_ard_3-2-1_53JQN_2023-05-27_final
2023-05-27 10:34:12	ga_s2bm_ard_3-2-1_53JPN_2023-05-27_final
2023-05-27 10:34:18	ga_s2bm_ard_3-2-1_53JNN_2023-05-27_final
2023-05-27 12:14:46	ga_s2bm_ard_3-2-1_49JGN_2023-05-27_final
2023-05-27 12:14:50	ga_s2bm_ard_3-2-1_49JFN_2023-05-27_final
2023-05-28 10:03:51	ga_s2bm_ard_3-2-1_55JDN_2023-05-28_final
2023-05-28 10:03:54	ga_s2bm_ard_3-2-1_55JCN_2023-05-28_final
2023-05-28 10:03:57	ga_s2bm_ard_3-2-1_54JZT_2023-05-28_final
2023-05-28 10:03:57	ga_s2bm_ard_3-2-1_55JBN_2023-05-28_final
2023-05-28 10:04:00	ga_s2bm_ard_3-2-1_54JYT_2023-05-28_final
2023-05-29 09:33:34	ga_s2bm_ard_3-2-1_56JPT_2023-05-29_nrt
2023-05-29 09:33:40	ga_s2bm_ard_3-2-1_56JNT_2023-05-29_final
2023-05-29 09:33:43	ga_s2bm_ard_3-2-1_56JMT_2023-05-29_final
2023-05-29 09:33:47	ga_s2bm_ard_3-2-1_56JLT_2023-05-29_final
2023-05-30 10:44:07	ga_s2bm_ard_3-2-1_53JPN_2023-05-30_final
2023-05-30 10:44:10	ga_s2bm_ard_3-2-1_53JNN_2023-05-30_final
2023-05-30 10:44:14	ga_s2bm_ard_3-2-1_53JMN_2023-05-30_final
2023-05-30 10:44:17	ga_s2bm_ard_3-2-1_53JLN_2023-05-30_final
2023-05-31 10:13:48	ga_s2bm_ard_3-2-1_55JBN_2023-05-31_final
2023-06-01 09:43:42	ga_s2bm_ard_3-2-1_56JLT_2023-06-01_final
2023-06-01 09:43:45	ga_s2bm_ard_3-2-1_55JHN_2023-06-01_final
2023-06-01 09:43:45	ga_s2bm_ard_3-2-1_56JKT_2023-06-01_final
2023-06-01 09:43:48	ga_s2bm_ard_3-2-1_55JGN_2023-06-01_final
2023-06-01 09:43:52	ga_s2bm_ard_3-2-1_55JFN_2023-06-01_final
2023-06-01 11:24:23	ga_s2bm_ard_3-2-1_52JBT_2023-06-01_final
2023-06-01 11:24:23	ga_s2bm_ard_3-2-1_51JZN_2023-06-01_final
2023-06-01 11:24:26	ga_s2bm_ard_3-2-1_51JYN_2023-06-01_final
2023-06-01 11:24:30	ga_s2bm_ard_3-2-1_51JXN_2023-06-01_final
2023-06-01 11:24:33	ga_s2bm_ard_3-2-1_51JWN_2023-06-01_final
2023-06-02 10:54:12	ga_s2bm_ard_3-2-1_53JLN_2023-06-02_final
2023-06-02 10:54:15	ga_s2bm_ard_3-2-1_52JHT_2023-06-02_final
2023-06-02 10:54:15	ga_s2bm_ard_3-2-1_53JKN_2023-06-02_final
2023-06-02 10:54:19	ga_s2bm_ard_3-2-1_52JGT_2023-06-02_final
2023-06-02 10:54:25	ga_s2bm_ard_3-2-1_52JFT_2023-06-02_final
2023-06-04 09:53:42	ga_s2bm_ard_3-2-1_55JGN_2023-06-04_final
2023-06-04 09:53:48	ga_s2bm_ard_3-2-1_55JFN_2023-06-04_final
2023-06-04 09:53:52	ga_s2bm_ard_3-2-1_55JEN_2023-06-04_final
2023-06-04 09:53:55	ga_s2bm_ard_3-2-1_55JDN_2023-06-04_final
2023-06-04 11:34:29	ga_s2bm_ard_3-2-1_51JWN_2023-06-04_final
2023-06-04 11:34:33	ga_s2bm_ard_3-2-1_51JVN_2023-06-04_final
2023-06-04 11:34:36	ga_s2bm_ard_3-2-1_51JUN_2023-06-04_final
2023-06-04 11:34:40	ga_s2bm_ard_3-2-1_51JTN_2023-06-04_final
2023-06-04 11:34:41	ga_s2bm_ard_3-2-1_50JRT_2023-06-04_final
2023-06-05 11:04:15	ga_s2bm_ard_3-2-1_52JGT_2023-06-05_final
2023-06-05 11:04:19	ga_s2bm_ard_3-2-1_52JFT_2023-06-05_final
2023-06-10 10:13:49	ga_s2bm_ard_3-2-1_55JBN_2023-06-10_final
2023-06-10 10:13:50	ga_s2bm_ard_3-2-1_54JZT_2023-06-10_final
2023-06-10 10:13:57	ga_s2bm_ard_3-2-1_54JYT_2023-06-10_final
2023-06-10 10:14:01	ga_s2bm_ard_3-2-1_54JXT_2023-06-10_final
2023-06-10 10:14:04	ga_s2bm_ard_3-2-1_54JWT_2023-06-10_final
2023-06-10 11:54:38	ga_s2bm_ard_3-2-1_50JPT_2023-06-10_final
2023-06-10 11:54:42	ga_s2bm_ard_3-2-1_50JNT_2023-06-10_final
2023-06-10 11:54:45	ga_s2bm_ard_3-2-1_50JMT_2023-06-10_final
2023-06-10 11:54:49	ga_s2bm_ard_3-2-1_50JLT_2023-06-10_final
2023-06-26 10:33:56	ga_s2bm_ard_3-2-1_54JUT_2023-06-26_final
2023-06-26 10:34:04	ga_s2bm_ard_3-2-1_53JRN_2023-06-26_final
2023-06-26 10:34:04	ga_s2bm_ard_3-2-1_54JTT_2023-06-26_final

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