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
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JKH_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JKJ_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JLJ_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JMJ_2017-11-17_final.stac-item
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JNJ_2017-11-17_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JUP_2017-11-18_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JVP_2017-11-18_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JWP_2017-11-18_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JXP_2017-11-18_final.stac-item
2017-11-18 10:13:29	ga_s2bm_ard_3-2-1_54JYP_2017-11-18_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JCJ_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JDJ_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JEJ_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55JFJ_2017-11-22_final.stac-item
2017-11-29 11:25:05	ga_s2bm_ard_3-2-1_51JVJ_2017-11-29_final.stac-item
2017-11-29 11:25:05	ga_s2bm_ard_3-2-1_51JWJ_2017-11-29_final.stac-item
2017-11-29 11:25:05	ga_s2bm_ard_3-2-1_51JXJ_2017-11-29_final.stac-item
2017-11-29 11:25:05	ga_s2bm_ard_3-2-1_51JYH_2017-11-29_final.stac-item
2017-11-29 11:25:05	ga_s2bm_ard_3-2-1_51JYJ_2017-11-29_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JCJ_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JDJ_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JEJ_2017-12-02_final.stac-item
2017-12-02 09:52:46	ga_s2bm_ard_3-2-1_55JFJ_2017-12-02_final.stac-item
2017-12-11 12:02:37	ga_s2bm_ard_3-2-1_49JGJ_2017-12-11_final.stac-item
2017-12-11 12:02:37	ga_s2bm_ard_3-2-1_50JKN_2017-12-11_final.stac-item
2017-12-11 12:02:37	ga_s2bm_ard_3-2-1_50JKP_2017-12-11_final.stac-item
2017-12-11 12:02:37	ga_s2bm_ard_3-2-1_50JLP_2017-12-11_final.stac-item
2017-12-12 11:30:28	ga_s2bm_ard_3-2-1_51JTH_2017-12-12_final.stac-item
2017-12-12 11:30:28	ga_s2bm_ard_3-2-1_51JTJ_2017-12-12_final.stac-item
2017-12-12 11:30:28	ga_s2bm_ard_3-2-1_51JUJ_2017-12-12_final.stac-item
2017-12-12 11:30:28	ga_s2bm_ard_3-2-1_51JVJ_2017-12-12_final.stac-item
2017-12-12 11:30:28	ga_s2bm_ard_3-2-1_50JQN_2017-12-12_final.stac-item
2017-12-12 11:30:28	ga_s2bm_ard_3-2-1_50JQP_2017-12-12_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JKN_2017-12-18_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JKP_2017-12-18_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JLP_2017-12-18_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JMP_2017-12-18_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JNP_2017-12-18_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_49JGJ_2017-12-21_final.stac-item
2018-09-05 09:40:59	ga_s2bm_ard_3-2-1_56JKN_2018-09-05_final.stac-item
2018-09-05 09:40:59	ga_s2bm_ard_3-2-1_56JKP_2018-09-05_final.stac-item
2018-09-05 09:40:59	ga_s2bm_ard_3-2-1_55JEJ_2018-09-05_final.stac-item
2018-09-05 09:40:59	ga_s2bm_ard_3-2-1_55JFJ_2018-09-05_final.stac-item
2018-09-05 09:40:59	ga_s2bm_ard_3-2-1_55JGH_2018-09-05_final.stac-item
2018-09-05 09:40:59	ga_s2bm_ard_3-2-1_55JGJ_2018-09-05_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JVJ_2018-09-05_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JWJ_2018-09-05_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JXJ_2018-09-05_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JYH_2018-09-05_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JYJ_2018-09-05_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_51JTH_2018-09-08_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_51JTJ_2018-09-08_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_51JUJ_2018-09-08_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_51JVJ_2018-09-08_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_50JQN_2018-09-08_final.stac-item
2018-09-08 11:30:45	ga_s2bm_ard_3-2-1_50JQP_2018-09-08_final.stac-item
2019-06-01 10:14:56	ga_s2bm_ard_3-2-1_54JYP_2019-06-01_final.stac-item
2019-06-01 10:15:02	ga_s2bm_ard_3-2-1_54JXP_2019-06-01_final.stac-item
2019-06-01 10:15:05	ga_s2bm_ard_3-2-1_54JWP_2019-06-01_final.stac-item
2019-06-01 10:15:09	ga_s2bm_ard_3-2-1_54JVP_2019-06-01_final.stac-item
2019-06-01 10:15:16	ga_s2bm_ard_3-2-1_54JUP_2019-06-01_final.stac-item
2019-06-07 10:35:05	ga_s2bm_ard_3-2-1_54JTP_2019-06-07_final.stac-item
2019-06-07 10:35:09	ga_s2bm_ard_3-2-1_53JQJ_2019-06-07_final.stac-item
2019-06-07 10:35:13	ga_s2bm_ard_3-2-1_53JPJ_2019-06-07_final.stac-item
2019-06-07 10:35:16	ga_s2bm_ard_3-2-1_54JTN_2019-06-07_final.stac-item
2019-06-11 10:14:55	ga_s2bm_ard_3-2-1_54JYP_2019-06-11_final.stac-item
2019-06-11 10:15:01	ga_s2bm_ard_3-2-1_54JXP_2019-06-11_final.stac-item
2019-06-11 10:15:05	ga_s2bm_ard_3-2-1_54JWP_2019-06-11_final.stac-item
2019-06-11 10:15:08	ga_s2bm_ard_3-2-1_54JVP_2019-06-11_final.stac-item
2019-06-11 10:15:15	ga_s2bm_ard_3-2-1_54JUP_2019-06-11_final.stac-item
2019-06-13 10:55:12	ga_s2bm_ard_3-2-1_53JLJ_2019-06-13_final.stac-item
2019-06-21 10:14:55	ga_s2bm_ard_3-2-1_54JYP_2019-06-21_final.stac-item
2019-06-21 10:15:01	ga_s2bm_ard_3-2-1_54JXP_2019-06-21_final.stac-item
2019-06-21 10:15:05	ga_s2bm_ard_3-2-1_54JWP_2019-06-21_final.stac-item
2019-06-21 10:15:08	ga_s2bm_ard_3-2-1_54JVP_2019-06-21_final.stac-item
2019-06-21 10:15:16	ga_s2bm_ard_3-2-1_54JUP_2019-06-21_final.stac-item
2019-06-27 10:35:05	ga_s2bm_ard_3-2-1_54JTP_2019-06-27_final.stac-item
2019-06-27 10:35:09	ga_s2bm_ard_3-2-1_53JQJ_2019-06-27_final.stac-item
2019-06-27 10:35:13	ga_s2bm_ard_3-2-1_53JPJ_2019-06-27_final.stac-item
2019-06-27 10:35:16	ga_s2bm_ard_3-2-1_54JTN_2019-06-27_final.stac-item
2019-06-27 10:35:17	ga_s2bm_ard_3-2-1_53JNJ_2019-06-27_final.stac-item
2019-06-27 10:35:23	ga_s2bm_ard_3-2-1_53JMJ_2019-06-27_final.stac-item
2019-08-24 11:35:31	ga_s2bm_ard_3-2-1_51JVJ_2019-08-24_final.stac-item
2019-08-24 11:35:35	ga_s2bm_ard_3-2-1_51JUJ_2019-08-24_final.stac-item
2019-08-24 11:35:38	ga_s2bm_ard_3-2-1_51JTJ_2019-08-24_final.stac-item
2019-08-24 11:35:42	ga_s2bm_ard_3-2-1_50JQP_2019-08-24_final.stac-item
2019-08-24 11:35:50	ga_s2bm_ard_3-2-1_51JTH_2019-08-24_final.stac-item
2019-08-24 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-08-24_final.stac-item
2019-09-13 11:35:27	ga_s2bm_ard_3-2-1_51JVJ_2019-09-13_final.stac-item
2019-09-13 11:35:31	ga_s2bm_ard_3-2-1_51JUJ_2019-09-13_final.stac-item
2019-09-13 11:35:34	ga_s2bm_ard_3-2-1_51JTJ_2019-09-13_final.stac-item
2019-09-13 11:35:38	ga_s2bm_ard_3-2-1_50JQP_2019-09-13_final.stac-item
2019-09-13 11:35:48	ga_s2bm_ard_3-2-1_51JTH_2019-09-13_final.stac-item
2019-09-13 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-09-13_final.stac-item
2019-09-14 09:24:41	ga_s2bm_ard_3-2-1_56JMP_2019-09-13_final.stac-item
2019-09-16 11:45:29	ga_s2bm_ard_3-2-1_51JTJ_2019-09-16_final.stac-item
2019-09-16 11:45:32	ga_s2bm_ard_3-2-1_50JQP_2019-09-16_final.stac-item
2019-09-16 11:45:36	ga_s2bm_ard_3-2-1_50JPP_2019-09-16_final.stac-item
2019-09-16 11:45:39	ga_s2bm_ard_3-2-1_50JNP_2019-09-16_final.stac-item
2019-09-16 11:45:43	ga_s2bm_ard_3-2-1_51JTH_2019-09-16_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