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
2018-09-12 11:14:23	ga_s2bm_ard_3-2-1_52JBP_2018-09-12_final.stac-item
2018-09-12 11:14:23	ga_s2bm_ard_3-2-1_52JBQ_2018-09-12_final.stac-item
2018-09-12 11:14:23	ga_s2bm_ard_3-2-1_52JCP_2018-09-12_final.stac-item
2018-09-13 10:41:38	ga_s2bm_ard_3-2-1_53JKJ_2018-09-13_final.stac-item
2018-09-13 10:41:38	ga_s2bm_ard_3-2-1_53JKK_2018-09-13_final.stac-item
2018-09-13 10:41:38	ga_s2bm_ard_3-2-1_53JLJ_2018-09-13_final.stac-item
2018-09-13 10:41:38	ga_s2bm_ard_3-2-1_53JLK_2018-09-13_final.stac-item
2018-09-13 10:41:38	ga_s2bm_ard_3-2-1_53JMK_2018-09-13_final.stac-item
2018-09-13 10:41:38	ga_s2bm_ard_3-2-1_53JNK_2018-09-13_final.stac-item
2018-09-14 10:13:35	ga_s2bm_ard_3-2-1_54JVQ_2018-09-14_final.stac-item
2018-09-14 10:13:35	ga_s2bm_ard_3-2-1_54JWQ_2018-09-14_final.stac-item
2018-09-14 10:13:35	ga_s2bm_ard_3-2-1_54JXP_2018-09-14_final.stac-item
2018-09-14 10:13:35	ga_s2bm_ard_3-2-1_54JXQ_2018-09-14_final.stac-item
2018-09-14 10:13:35	ga_s2bm_ard_3-2-1_54JYP_2018-09-14_final.stac-item
2018-09-14 10:13:35	ga_s2bm_ard_3-2-1_54JYQ_2018-09-14_final.stac-item
2018-09-15 11:21:46	ga_s2bm_ard_3-2-1_51JVK_2018-09-15_final.stac-item
2018-09-15 11:21:46	ga_s2bm_ard_3-2-1_51JWK_2018-09-15_final.stac-item
2018-09-15 11:21:46	ga_s2bm_ard_3-2-1_51JXJ_2018-09-15_final.stac-item
2018-09-15 11:21:46	ga_s2bm_ard_3-2-1_51JXK_2018-09-15_final.stac-item
2018-09-15 11:21:46	ga_s2bm_ard_3-2-1_51JYJ_2018-09-15_final.stac-item
2018-09-15 11:21:46	ga_s2bm_ard_3-2-1_51JYK_2018-09-15_final.stac-item
2018-09-24 10:13:38	ga_s2bm_ard_3-2-1_54JVQ_2018-09-24_final.stac-item
2018-09-24 10:13:38	ga_s2bm_ard_3-2-1_54JWQ_2018-09-24_final.stac-item
2018-09-24 10:13:38	ga_s2bm_ard_3-2-1_54JXP_2018-09-24_final.stac-item
2018-09-24 10:13:38	ga_s2bm_ard_3-2-1_54JXQ_2018-09-24_final.stac-item
2018-09-24 10:13:38	ga_s2bm_ard_3-2-1_54JYP_2018-09-24_final.stac-item
2018-09-24 10:13:38	ga_s2bm_ard_3-2-1_54JYQ_2018-09-24_final.stac-item
2018-09-25 09:41:02	ga_s2bm_ard_3-2-1_56JKP_2018-09-25_final.stac-item
2018-09-25 09:41:02	ga_s2bm_ard_3-2-1_56JKQ_2018-09-25_final.stac-item
2018-09-25 09:41:02	ga_s2bm_ard_3-2-1_55JEK_2018-09-25_final.stac-item
2018-09-25 09:41:02	ga_s2bm_ard_3-2-1_55JFJ_2018-09-25_final.stac-item
2018-09-25 09:41:02	ga_s2bm_ard_3-2-1_55JFK_2018-09-25_final.stac-item
2018-09-25 09:41:02	ga_s2bm_ard_3-2-1_55JGJ_2018-09-25_final.stac-item
2018-09-25 09:41:02	ga_s2bm_ard_3-2-1_55JGK_2018-09-25_final.stac-item
2018-09-25 11:23:23	ga_s2bm_ard_3-2-1_51JVK_2018-09-25_final.stac-item
2018-09-25 11:23:23	ga_s2bm_ard_3-2-1_51JWK_2018-09-25_final.stac-item
2018-09-25 11:23:23	ga_s2bm_ard_3-2-1_51JXJ_2018-09-25_final.stac-item
2018-09-25 11:23:23	ga_s2bm_ard_3-2-1_51JXK_2018-09-25_final.stac-item
2018-09-25 11:23:23	ga_s2bm_ard_3-2-1_51JYJ_2018-09-25_final.stac-item
2018-09-25 11:23:23	ga_s2bm_ard_3-2-1_51JYK_2018-09-25_final.stac-item
2018-09-29 09:22:39	ga_s2bm_ard_3-2-1_56JMQ_2018-09-28_final.stac-item
2019-07-04 12:05:33	ga_s2bm_ard_3-2-1_50JLQ_2019-07-04_final.stac-item
2019-07-04 12:05:35	ga_s2bm_ard_3-2-1_50JKQ_2019-07-04_final.stac-item
2019-07-04 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-07-04_final.stac-item
2019-07-04 12:05:46	ga_s2bm_ard_3-2-1_50JLP_2019-07-04_final.stac-item
2019-07-04 12:05:49	ga_s2bm_ard_3-2-1_50JKP_2019-07-04_final.stac-item
2019-07-04 12:05:52	ga_s2bm_ard_3-2-1_49JGJ_2019-07-04_final.stac-item
2019-07-05 09:54:36	ga_s2bm_ard_3-2-1_55JFK_2019-07-05_final.stac-item
2019-07-05 09:54:40	ga_s2bm_ard_3-2-1_55JEK_2019-07-05_final.stac-item
2019-07-05 09:54:43	ga_s2bm_ard_3-2-1_55JDK_2019-07-05_final.stac-item
2019-07-05 09:54:46	ga_s2bm_ard_3-2-1_55JCK_2019-07-05_final.stac-item
2019-07-06 11:05:06	ga_s2bm_ard_3-2-1_52JFQ_2019-07-06_final.stac-item
2019-07-06 11:05:10	ga_s2bm_ard_3-2-1_52JEQ_2019-07-06_final.stac-item
2019-07-06 11:05:14	ga_s2bm_ard_3-2-1_52JDQ_2019-07-06_final.stac-item
2019-07-06 11:05:17	ga_s2bm_ard_3-2-1_52JCQ_2019-07-06_final.stac-item
2019-07-13 10:55:01	ga_s2bm_ard_3-2-1_53JLK_2019-07-13_final.stac-item
2019-07-13 10:55:04	ga_s2bm_ard_3-2-1_53JKK_2019-07-13_final.stac-item
2019-07-13 10:55:07	ga_s2bm_ard_3-2-1_52JGQ_2019-07-13_final.stac-item
2019-07-13 10:55:11	ga_s2bm_ard_3-2-1_52JFQ_2019-07-13_final.stac-item
2019-07-13 10:55:14	ga_s2bm_ard_3-2-1_53JLJ_2019-07-13_final.stac-item
2019-07-13 10:55:19	ga_s2bm_ard_3-2-1_53JKJ_2019-07-13_final.stac-item
2019-07-13 10:55:22	ga_s2bm_ard_3-2-1_52JGP_2019-07-13_final.stac-item
2019-07-13 10:55:25	ga_s2bm_ard_3-2-1_52JFP_2019-07-13_final.stac-item
2019-07-14 10:24:50	ga_s2bm_ard_3-2-1_54JVQ_2019-07-14_final.stac-item
2019-07-14 10:24:54	ga_s2bm_ard_3-2-1_54JUQ_2019-07-14_final.stac-item
2019-07-14 10:24:57	ga_s2bm_ard_3-2-1_54JTQ_2019-07-14_final.stac-item
2019-07-14 10:25:00	ga_s2bm_ard_3-2-1_53JQK_2019-07-14_final.stac-item
2019-07-14 10:25:08	ga_s2bm_ard_3-2-1_54JUP_2019-07-14_final.stac-item
2019-07-14 10:25:11	ga_s2bm_ard_3-2-1_54JTP_2019-07-14_final.stac-item
2019-07-14 10:25:14	ga_s2bm_ard_3-2-1_53JQJ_2019-07-14_final.stac-item
2019-07-15 11:35:17	ga_s2bm_ard_3-2-1_51JWK_2019-07-15_final.stac-item
2019-07-15 11:35:21	ga_s2bm_ard_3-2-1_51JVK_2019-07-15_final.stac-item
2019-07-15 11:35:24	ga_s2bm_ard_3-2-1_51JUK_2019-07-15_final.stac-item
2019-07-15 11:35:28	ga_s2bm_ard_3-2-1_51JTK_2019-07-15_final.stac-item
2019-07-15 11:35:39	ga_s2bm_ard_3-2-1_51JUJ_2019-07-15_final.stac-item
2019-07-15 11:35:42	ga_s2bm_ard_3-2-1_51JTJ_2019-07-15_final.stac-item
2019-07-15 11:35:46	ga_s2bm_ard_3-2-1_50JQP_2019-07-15_final.stac-item
2019-08-02 10:55:00	ga_s2bm_ard_3-2-1_53JLK_2019-08-02_final.stac-item
2019-08-02 10:55:03	ga_s2bm_ard_3-2-1_53JKK_2019-08-02_final.stac-item
2019-08-02 10:55:06	ga_s2bm_ard_3-2-1_52JGQ_2019-08-02_final.stac-item
2019-08-02 10:55:10	ga_s2bm_ard_3-2-1_52JFQ_2019-08-02_final.stac-item
2019-08-02 10:55:13	ga_s2bm_ard_3-2-1_53JLJ_2019-08-02_final.stac-item
2019-08-02 10:55:18	ga_s2bm_ard_3-2-1_53JKJ_2019-08-02_final.stac-item
2019-08-02 10:55:21	ga_s2bm_ard_3-2-1_52JGP_2019-08-02_final.stac-item
2019-08-02 10:55:25	ga_s2bm_ard_3-2-1_52JFP_2019-08-02_final.stac-item
2019-08-07 10:04:40	ga_s2bm_ard_3-2-1_55JCK_2019-08-07_final.stac-item
2019-08-07 10:04:44	ga_s2bm_ard_3-2-1_55JBK_2019-08-07_final.stac-item
2019-08-07 10:04:47	ga_s2bm_ard_3-2-1_54JYQ_2019-08-07_final.stac-item
2019-08-07 10:04:51	ga_s2bm_ard_3-2-1_54JXQ_2019-08-07_final.stac-item
2019-08-07 10:04:55	ga_s2bm_ard_3-2-1_55JCJ_2019-08-07_final.stac-item
2019-08-07 10:04:58	ga_s2bm_ard_3-2-1_55JBJ_2019-08-07_final.stac-item
2019-08-07 10:05:01	ga_s2bm_ard_3-2-1_54JYP_2019-08-07_final.stac-item
2019-08-07 10:05:05	ga_s2bm_ard_3-2-1_54JXP_2019-08-07_final.stac-item
2019-08-17 10:04:39	ga_s2bm_ard_3-2-1_55JCK_2019-08-17_final.stac-item
2019-08-17 10:04:43	ga_s2bm_ard_3-2-1_55JBK_2019-08-17_final.stac-item
2019-08-17 10:04:46	ga_s2bm_ard_3-2-1_54JYQ_2019-08-17_final.stac-item
2019-08-17 10:04:50	ga_s2bm_ard_3-2-1_54JXQ_2019-08-17_final.stac-item
2019-08-17 10:04:54	ga_s2bm_ard_3-2-1_55JCJ_2019-08-17_final.stac-item
2019-08-17 10:04:57	ga_s2bm_ard_3-2-1_55JBJ_2019-08-17_final.stac-item
2019-08-17 10:05:00	ga_s2bm_ard_3-2-1_54JYP_2019-08-17_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

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