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
2019-07-31 11:54:56	ga_s2bm_ard_3-2-1_50JPS_2019-07-31_final.stac-item
2019-07-31 11:54:59	ga_s2bm_ard_3-2-1_50JNS_2019-07-31_final.stac-item
2019-07-31 11:55:03	ga_s2bm_ard_3-2-1_50JMS_2019-07-31_final.stac-item
2019-07-31 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2019-07-31_final.stac-item
2019-08-10 11:54:55	ga_s2bm_ard_3-2-1_50JPS_2019-08-10_final.stac-item
2019-08-10 11:54:58	ga_s2bm_ard_3-2-1_50JNS_2019-08-10_final.stac-item
2019-08-10 11:55:02	ga_s2bm_ard_3-2-1_50JMS_2019-08-10_final.stac-item
2019-08-10 11:55:05	ga_s2bm_ard_3-2-1_50JLS_2019-08-10_final.stac-item
2019-10-14 09:23:56	ga_s2bm_ard_3-2-1_56JNS_2019-10-13_final.stac-item
2019-10-20 11:24:33	ga_s2bm_ard_3-2-1_51JZM_2019-10-20_final.stac-item
2019-10-20 11:24:33	ga_s2bm_ard_3-2-1_52JBS_2019-10-20_final.stac-item
2019-10-20 11:24:38	ga_s2bm_ard_3-2-1_51JYM_2019-10-20_final.stac-item
2019-10-20 11:24:42	ga_s2bm_ard_3-2-1_51JXM_2019-10-20_final.stac-item
2019-10-20 11:24:45	ga_s2bm_ard_3-2-1_52JBR_2019-10-20_final.stac-item
2019-10-20 11:24:45	ga_s2bm_ard_3-2-1_51JWM_2019-10-20_final.stac-item
2019-10-20 11:24:52	ga_s2bm_ard_3-2-1_51JYL_2019-10-20_final.stac-item
2019-10-20 11:24:56	ga_s2bm_ard_3-2-1_51JXL_2019-10-20_final.stac-item
2019-11-02 11:34:40	ga_s2bm_ard_3-2-1_51JWM_2019-11-02_final.stac-item
2019-11-02 11:34:44	ga_s2bm_ard_3-2-1_51JVM_2019-11-02_final.stac-item
2019-11-02 11:34:47	ga_s2bm_ard_3-2-1_51JUM_2019-11-02_final.stac-item
2019-11-02 11:34:50	ga_s2bm_ard_3-2-1_50JRS_2019-11-02_final.stac-item
2019-11-02 11:34:50	ga_s2bm_ard_3-2-1_51JTM_2019-11-02_final.stac-item
2019-11-02 11:35:02	ga_s2bm_ard_3-2-1_51JUL_2019-11-02_final.stac-item
2019-11-02 11:35:04	ga_s2bm_ard_3-2-1_51JTL_2019-11-02_final.stac-item
2019-11-03 09:23:55	ga_s2bm_ard_3-2-1_56JNS_2019-11-02_final.stac-item
2020-07-31 12:14:59	ga_s2bm_ard_3-2-1_49JGM_2020-07-31_final.stac-item
2020-07-31 12:15:02	ga_s2bm_ard_3-2-1_49JFM_2020-07-31_final.stac-item
2020-07-31 12:15:13	ga_s2bm_ard_3-2-1_49JGL_2020-07-31_final.stac-item
2020-08-01 10:04:03	ga_s2bm_ard_3-2-1_55JDM_2020-08-01_final.stac-item
2020-08-01 10:04:07	ga_s2bm_ard_3-2-1_55JCM_2020-08-01_final.stac-item
2020-08-01 10:04:10	ga_s2bm_ard_3-2-1_54JZS_2020-08-01_final.stac-item
2020-08-01 10:04:10	ga_s2bm_ard_3-2-1_55JBM_2020-08-01_final.stac-item
2020-08-01 10:04:14	ga_s2bm_ard_3-2-1_54JYS_2020-08-01_final.stac-item
2020-08-01 10:04:21	ga_s2bm_ard_3-2-1_55JCL_2020-08-01_final.stac-item
2020-08-01 10:04:23	ga_s2bm_ard_3-2-1_55JBL_2020-08-01_final.stac-item
2020-08-01 10:04:25	ga_s2bm_ard_3-2-1_54JYR_2020-08-01_final.stac-item
2020-08-05 09:43:55	ga_s2bm_ard_3-2-1_56JLS_2020-08-05_final.stac-item
2020-08-05 09:43:59	ga_s2bm_ard_3-2-1_55JHM_2020-08-05_final.stac-item
2020-08-05 09:43:59	ga_s2bm_ard_3-2-1_56JKS_2020-08-05_final.stac-item
2020-08-05 09:44:02	ga_s2bm_ard_3-2-1_55JGM_2020-08-05_final.stac-item
2020-08-05 09:44:06	ga_s2bm_ard_3-2-1_55JFM_2020-08-05_final.stac-item
2020-08-05 09:44:09	ga_s2bm_ard_3-2-1_56JLR_2020-08-05_final.stac-item
2020-08-05 09:44:13	ga_s2bm_ard_3-2-1_56JKR_2020-08-05_final.stac-item
2020-08-05 09:44:17	ga_s2bm_ard_3-2-1_55JGL_2020-08-05_final.stac-item
2020-08-05 09:44:20	ga_s2bm_ard_3-2-1_55JFL_2020-08-05_final.stac-item
2020-08-07 10:24:12	ga_s2bm_ard_3-2-1_54JWS_2020-08-07_final.stac-item
2020-08-07 10:24:16	ga_s2bm_ard_3-2-1_54JVS_2020-08-07_final.stac-item
2020-08-07 10:24:19	ga_s2bm_ard_3-2-1_54JUS_2020-08-07_final.stac-item
2020-08-07 10:24:22	ga_s2bm_ard_3-2-1_53JRM_2020-08-07_final.stac-item
2020-08-07 10:24:22	ga_s2bm_ard_3-2-1_54JTS_2020-08-07_final.stac-item
2020-08-07 10:24:34	ga_s2bm_ard_3-2-1_54JUR_2020-08-07_final.stac-item
2020-08-07 10:24:37	ga_s2bm_ard_3-2-1_54JTR_2020-08-07_final.stac-item
2022-03-25 09:33:47	ga_s2bm_ard_3-2-1_56JNS_2022-03-25_final.stac-item
2022-03-25 09:33:51	ga_s2bm_ard_3-2-1_56JMS_2022-03-25_final.stac-item
2022-03-25 09:33:54	ga_s2bm_ard_3-2-1_56JLS_2022-03-25_final.stac-item
2022-03-25 09:33:58	ga_s2bm_ard_3-2-1_55JHM_2022-03-25_final.stac-item
2022-03-25 09:33:58	ga_s2bm_ard_3-2-1_56JKS_2022-03-25_final.stac-item
2022-03-25 09:34:09	ga_s2bm_ard_3-2-1_56JLR_2022-03-25_final.stac-item
2022-03-25 09:34:12	ga_s2bm_ard_3-2-1_56JKR_2022-03-25_final.stac-item
2022-04-12 12:14:53	ga_s2bm_ard_3-2-1_49JGM_2022-04-12_final.stac-item
2022-04-12 12:14:56	ga_s2bm_ard_3-2-1_49JFM_2022-04-12_final.stac-item
2022-04-12 12:15:07	ga_s2bm_ard_3-2-1_49JGL_2022-04-12_final.stac-item
2022-04-13 10:03:57	ga_s2bm_ard_3-2-1_55JDM_2022-04-13_final.stac-item
2022-04-13 10:04:01	ga_s2bm_ard_3-2-1_55JCM_2022-04-13_final.stac-item
2022-04-13 10:04:04	ga_s2bm_ard_3-2-1_54JZS_2022-04-13_final.stac-item
2022-04-13 10:04:04	ga_s2bm_ard_3-2-1_55JBM_2022-04-13_final.stac-item
2022-04-13 10:04:07	ga_s2bm_ard_3-2-1_54JYS_2022-04-13_final.stac-item
2022-04-13 10:04:15	ga_s2bm_ard_3-2-1_55JCL_2022-04-13_final.stac-item
2022-04-13 10:04:18	ga_s2bm_ard_3-2-1_55JBL_2022-04-13_final.stac-item
2022-04-13 10:04:22	ga_s2bm_ard_3-2-1_54JYR_2022-04-13_final.stac-item
2022-04-15 10:44:13	ga_s2bm_ard_3-2-1_53JPM_2022-04-15_final.stac-item
2022-04-15 10:44:17	ga_s2bm_ard_3-2-1_53JNM_2022-04-15_final.stac-item
2022-04-15 10:44:20	ga_s2bm_ard_3-2-1_53JMM_2022-04-15_final.stac-item
2022-04-15 10:44:24	ga_s2bm_ard_3-2-1_53JLM_2022-04-15_final.stac-item
2022-04-26 11:54:45	ga_s2bm_ard_3-2-1_50JNS_2022-04-26_final.stac-item
2022-04-26 11:54:48	ga_s2bm_ard_3-2-1_50JMS_2022-04-26_final.stac-item
2022-04-26 11:54:51	ga_s2bm_ard_3-2-1_50JLS_2022-04-26_final.stac-item
2022-11-12 10:14:24	ga_s2bm_ard_3-2-1_54JXR_2022-11-12_final.stac-item
2022-11-15 10:24:08	ga_s2bm_ard_3-2-1_54JWS_2022-11-15_final.stac-item
2022-11-15 10:24:12	ga_s2bm_ard_3-2-1_54JVS_2022-11-15_final.stac-item
2022-11-15 10:24:15	ga_s2bm_ard_3-2-1_54JUS_2022-11-15_final.stac-item
2022-11-19 10:04:25	ga_s2bm_ard_3-2-1_54JYR_2022-11-19_final.stac-item
2022-11-22 10:14:06	ga_s2bm_ard_3-2-1_54JYS_2022-11-22_final.stac-item
2022-11-22 10:14:10	ga_s2bm_ard_3-2-1_54JXS_2022-11-22_final.stac-item
2022-11-22 10:14:13	ga_s2bm_ard_3-2-1_54JWS_2022-11-22_final.stac-item
2022-11-22 10:14:17	ga_s2bm_ard_3-2-1_54JVS_2022-11-22_final.stac-item
2022-11-22 10:14:20	ga_s2bm_ard_3-2-1_54JYR_2022-11-22_final.stac-item
2022-11-22 10:14:24	ga_s2bm_ard_3-2-1_54JXR_2022-11-22_final.stac-item
2022-11-25 12:04:48	ga_s2bm_ard_3-2-1_50JMS_2022-11-25_final.stac-item
2022-11-25 12:04:53	ga_s2bm_ard_3-2-1_50JLS_2022-11-25_final.stac-item
2022-11-25 12:04:56	ga_s2bm_ard_3-2-1_49JHM_2022-11-25_final.stac-item
2022-11-25 12:04:56	ga_s2bm_ard_3-2-1_50JKS_2022-11-25_final.stac-item
2022-11-25 12:05:00	ga_s2bm_ard_3-2-1_49JGM_2022-11-25_final.stac-item
2022-11-25 12:05:07	ga_s2bm_ard_3-2-1_50JLR_2022-11-25_final.stac-item
2022-11-25 12:05:08	ga_s2bm_ard_3-2-1_49JFM_2022-11-25_final.stac-item
2022-11-25 12:05:11	ga_s2bm_ard_3-2-1_50JKR_2022-11-25_final.stac-item
2022-11-25 12:05:14	ga_s2bm_ard_3-2-1_49JGL_2022-11-25_final.stac-item
2022-11-26 09:53:57	ga_s2bm_ard_3-2-1_55JFM_2022-11-26_final.stac-item
2022-11-26 09:54:01	ga_s2bm_ard_3-2-1_55JEM_2022-11-26_final.stac-item
2022-11-26 09:54:04	ga_s2bm_ard_3-2-1_55JDM_2022-11-26_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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