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
2019-02-12 09:44:42	ga_s2bm_ard_3-2-1_55JGJ_2019-02-12_final.stac-item
2019-02-12 09:44:46	ga_s2bm_ard_3-2-1_55JFJ_2019-02-12_final.stac-item
2019-02-12 09:44:49	ga_s2bm_ard_3-2-1_55JEJ_2019-02-12_final.stac-item
2019-02-12 09:44:54	ga_s2bm_ard_3-2-1_56JKN_2019-02-12_final.stac-item
2019-02-12 09:44:57	ga_s2bm_ard_3-2-1_55JGH_2019-02-12_final.stac-item
2019-02-12 09:45:01	ga_s2bm_ard_3-2-1_55JFH_2019-02-12_final.stac-item
2019-02-12 09:45:04	ga_s2bm_ard_3-2-1_55JEH_2019-02-12_final.stac-item
2019-03-04 09:44:40	ga_s2bm_ard_3-2-1_55JGJ_2019-03-04_final.stac-item
2019-03-04 09:44:44	ga_s2bm_ard_3-2-1_55JFJ_2019-03-04_final.stac-item
2019-03-04 09:44:47	ga_s2bm_ard_3-2-1_55JEJ_2019-03-04_final.stac-item
2019-03-04 09:44:49	ga_s2bm_ard_3-2-1_56JKN_2019-03-04_final.stac-item
2019-03-04 09:44:50	ga_s2bm_ard_3-2-1_55JGH_2019-03-04_final.stac-item
2019-03-04 09:44:52	ga_s2bm_ard_3-2-1_55JFH_2019-03-04_final.stac-item
2019-03-04 09:44:52	ga_s2bm_ard_3-2-1_55JFJ_2019-03-04_final.stac-item
2019-03-04 09:44:53	ga_s2bm_ard_3-2-1_55JEJ_2019-03-04_final.stac-item
2019-03-04 09:44:53	ga_s2bm_ard_3-2-1_55JEH_2019-03-04_final.stac-item
2019-03-04 09:44:59	ga_s2bm_ard_3-2-1_55JFH_2019-03-04_final.stac-item
2019-03-04 09:45:02	ga_s2bm_ard_3-2-1_55JEH_2019-03-04_final.stac-item
2019-03-04 11:25:18	ga_s2bm_ard_3-2-1_51JYJ_2019-03-04_final.stac-item
2019-03-04 11:25:22	ga_s2bm_ard_3-2-1_51JXJ_2019-03-04_final.stac-item
2019-03-04 11:25:26	ga_s2bm_ard_3-2-1_51JWJ_2019-03-04_final.stac-item
2019-03-04 11:25:29	ga_s2bm_ard_3-2-1_51JVJ_2019-03-04_final.stac-item
2019-03-04 11:25:32	ga_s2bm_ard_3-2-1_51JYH_2019-03-04_final.stac-item
2019-03-04 11:25:36	ga_s2bm_ard_3-2-1_51JXH_2019-03-04_final.stac-item
2019-03-04 11:25:40	ga_s2bm_ard_3-2-1_51JWH_2019-03-04_final.stac-item
2019-03-04 11:25:43	ga_s2bm_ard_3-2-1_51JVH_2019-03-04_final.stac-item
2019-03-06 10:24:54	ga_s2bm_ard_3-2-1_54JVP_2019-03-06_final.stac-item
2019-03-06 10:24:57	ga_s2bm_ard_3-2-1_54JUP_2019-03-06_final.stac-item
2019-03-06 10:25:00	ga_s2bm_ard_3-2-1_54JTP_2019-03-06_final.stac-item
2019-03-06 10:25:08	ga_s2bm_ard_3-2-1_54JVN_2019-03-06_final.stac-item
2019-03-06 10:25:12	ga_s2bm_ard_3-2-1_54JUN_2019-03-06_final.stac-item
2019-03-06 10:25:15	ga_s2bm_ard_3-2-1_54JTN_2019-03-06_final.stac-item
2019-03-06 10:25:18	ga_s2bm_ard_3-2-1_53JQH_2019-03-06_final.stac-item
2019-03-16 10:24:54	ga_s2bm_ard_3-2-1_54JVP_2019-03-16_final.stac-item
2019-03-16 10:24:57	ga_s2bm_ard_3-2-1_54JUP_2019-03-16_final.stac-item
2019-03-16 10:25:01	ga_s2bm_ard_3-2-1_54JTP_2019-03-16_final.stac-item
2019-03-16 10:25:09	ga_s2bm_ard_3-2-1_54JVN_2019-03-16_final.stac-item
2019-03-16 10:25:12	ga_s2bm_ard_3-2-1_54JUN_2019-03-16_final.stac-item
2019-03-16 10:25:15	ga_s2bm_ard_3-2-1_54JTN_2019-03-16_final.stac-item
2019-03-16 10:25:18	ga_s2bm_ard_3-2-1_53JQH_2019-03-16_final.stac-item
2019-03-18 11:05:25	ga_s2bm_ard_3-2-1_52JFN_2019-03-18_final.stac-item
2019-03-18 11:05:29	ga_s2bm_ard_3-2-1_52JEN_2019-03-18_final.stac-item
2019-03-18 11:05:33	ga_s2bm_ard_3-2-1_52JDN_2019-03-18_final.stac-item
2019-03-18 11:05:36	ga_s2bm_ard_3-2-1_52JCN_2019-03-18_final.stac-item
2019-03-19 10:35:08	ga_s2bm_ard_3-2-1_53JNJ_2019-03-19_final.stac-item
2019-03-19 10:35:14	ga_s2bm_ard_3-2-1_53JMJ_2019-03-19_final.stac-item
2019-03-19 10:35:14	ga_s2bm_ard_3-2-1_53JQH_2019-03-19_final.stac-item
2019-03-19 10:35:18	ga_s2bm_ard_3-2-1_53JPH_2019-03-19_final.stac-item
2019-03-19 10:35:22	ga_s2bm_ard_3-2-1_53JNH_2019-03-19_final.stac-item
2019-03-19 10:35:26	ga_s2bm_ard_3-2-1_53JMH_2019-03-19_final.stac-item
2019-07-29 09:34:45	ga_s2bm_ard_3-2-1_56JMP_2019-07-29_final.stac-item
2019-07-29 09:34:49	ga_s2bm_ard_3-2-1_56JLP_2019-07-29_final.stac-item
2019-07-29 09:34:52	ga_s2bm_ard_3-2-1_56JNN_2019-07-29_final.stac-item
2019-07-29 09:34:52	ga_s2bm_ard_3-2-1_56JKP_2019-07-29_final.stac-item
2019-07-29 09:35:00	ga_s2bm_ard_3-2-1_56JMN_2019-07-29_final.stac-item
2019-07-29 09:35:03	ga_s2bm_ard_3-2-1_56JLN_2019-07-29_final.stac-item
2019-07-29 09:35:06	ga_s2bm_ard_3-2-1_56JKN_2019-07-29_final.stac-item
2019-07-29 09:35:09	ga_s2bm_ard_3-2-1_55JGH_2019-07-29_final.stac-item
2019-08-08 09:34:44	ga_s2bm_ard_3-2-1_56JMP_2019-08-08_final.stac-item
2019-08-08 09:34:48	ga_s2bm_ard_3-2-1_56JLP_2019-08-08_final.stac-item
2019-08-08 09:34:51	ga_s2bm_ard_3-2-1_56JNN_2019-08-08_final.stac-item
2019-08-08 09:34:51	ga_s2bm_ard_3-2-1_56JKP_2019-08-08_final.stac-item
2019-08-08 09:34:59	ga_s2bm_ard_3-2-1_56JMN_2019-08-08_final.stac-item
2019-08-08 09:35:02	ga_s2bm_ard_3-2-1_56JLN_2019-08-08_final.stac-item
2019-08-08 09:35:06	ga_s2bm_ard_3-2-1_56JKN_2019-08-08_final.stac-item
2019-08-08 09:35:09	ga_s2bm_ard_3-2-1_55JGH_2019-08-08_final.stac-item
2019-08-10 11:55:42	ga_s2bm_ard_3-2-1_50JNP_2019-08-10_final.stac-item
2019-08-10 11:55:46	ga_s2bm_ard_3-2-1_50JMP_2019-08-10_final.stac-item
2019-08-10 11:55:49	ga_s2bm_ard_3-2-1_50JLP_2019-08-10_final.stac-item
2019-08-10 11:55:53	ga_s2bm_ard_3-2-1_50JKP_2019-08-10_final.stac-item
2019-08-10 11:55:56	ga_s2bm_ard_3-2-1_50JNN_2019-08-10_final.stac-item
2019-08-10 11:56:00	ga_s2bm_ard_3-2-1_50JMN_2019-08-10_final.stac-item
2019-08-10 11:56:03	ga_s2bm_ard_3-2-1_50JLN_2019-08-10_final.stac-item
2019-08-10 11:56:06	ga_s2bm_ard_3-2-1_50JKN_2019-08-10_final.stac-item
2019-08-23 12:05:57	ga_s2bm_ard_3-2-1_50JLN_2019-08-23_final.stac-item
2019-08-23 12:06:00	ga_s2bm_ard_3-2-1_50JKN_2019-08-23_final.stac-item
2019-08-24 09:54:45	ga_s2bm_ard_3-2-1_55JFJ_2019-08-24_final.stac-item
2019-08-24 09:54:50	ga_s2bm_ard_3-2-1_55JEJ_2019-08-24_final.stac-item
2019-08-24 09:54:54	ga_s2bm_ard_3-2-1_55JDJ_2019-08-24_final.stac-item
2019-08-24 09:54:56	ga_s2bm_ard_3-2-1_55JFH_2019-08-24_final.stac-item
2019-08-24 09:54:57	ga_s2bm_ard_3-2-1_55JCJ_2019-08-24_final.stac-item
2019-08-24 09:55:05	ga_s2bm_ard_3-2-1_55JEH_2019-08-24_final.stac-item
2019-08-24 09:55:08	ga_s2bm_ard_3-2-1_55JDH_2019-08-24_final.stac-item
2019-08-24 09:55:12	ga_s2bm_ard_3-2-1_55JCH_2019-08-24_final.stac-item
2019-08-24 09:55:16	ga_s2bm_ard_3-2-1_55JBH_2019-08-24_final.stac-item
2019-08-27 10:04:55	ga_s2bm_ard_3-2-1_55JBJ_2019-08-27_final.stac-item
2019-08-27 10:05:02	ga_s2bm_ard_3-2-1_54JXP_2019-08-27_final.stac-item
2019-08-27 10:05:07	ga_s2bm_ard_3-2-1_55JCH_2019-08-27_final.stac-item
2019-08-27 10:05:10	ga_s2bm_ard_3-2-1_55JBH_2019-08-27_final.stac-item
2019-08-27 10:05:13	ga_s2bm_ard_3-2-1_54JYN_2019-08-27_final.stac-item
2019-08-27 10:05:17	ga_s2bm_ard_3-2-1_54JXN_2019-08-27_final.stac-item
2019-09-09 10:14:49	ga_s2bm_ard_3-2-1_54JYP_2019-09-09_final.stac-item
2019-09-09 10:14:55	ga_s2bm_ard_3-2-1_54JXP_2019-09-09_final.stac-item
2019-09-09 10:14:59	ga_s2bm_ard_3-2-1_54JWP_2019-09-09_final.stac-item
2019-09-09 10:14:59	ga_s2bm_ard_3-2-1_54JYN_2019-09-09_final.stac-item
2019-09-09 10:15:02	ga_s2bm_ard_3-2-1_54JVP_2019-09-09_final.stac-item
2019-09-09 10:15:09	ga_s2bm_ard_3-2-1_54JXN_2019-09-09_final.stac-item
2019-09-09 10:15:09	ga_s2bm_ard_3-2-1_54JUP_2019-09-09_final.stac-item
2019-09-09 10:15:13	ga_s2bm_ard_3-2-1_54JWN_2019-09-09_final.stac-item
2019-09-09 10:15:16	ga_s2bm_ard_3-2-1_54JVN_2019-09-09_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