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
2019-02-04 10:24:19	ga_s2bm_ard_3-2-1_53JRM_2019-02-04_final.stac-item
2019-02-04 10:24:19	ga_s2bm_ard_3-2-1_54JTS_2019-02-04_final.stac-item
2019-02-04 10:24:34	ga_s2bm_ard_3-2-1_54JTR_2019-02-04_final.stac-item
2019-02-04 10:24:48	ga_s2bm_ard_3-2-1_54JTQ_2019-02-04_final.stac-item
2019-02-04 10:25:03	ga_s2bm_ard_3-2-1_54JTP_2019-02-04_final.stac-item
2019-02-04 10:25:15	ga_s2bm_ard_3-2-1_54JTN_2019-02-04_final.stac-item
2019-02-04 10:25:20	ga_s2bm_ard_3-2-1_54JUN_2019-02-04_final.stac-item
2019-02-04 10:25:21	ga_s2bm_ard_3-2-1_54JTN_2019-02-04_final.stac-item
2019-02-04 10:25:29	ga_s2bm_ard_3-2-1_54JUM_2019-02-04_final.stac-item
2019-02-04 10:25:32	ga_s2bm_ard_3-2-1_54JTM_2019-02-04_final.stac-item
2019-02-04 10:25:43	ga_s2bm_ard_3-2-1_54JUL_2019-02-04_final.stac-item
2019-02-04 10:25:47	ga_s2bm_ard_3-2-1_54JTL_2019-02-04_final.stac-item
2019-02-04 10:25:58	ga_s2bm_ard_3-2-1_54HUK_2019-02-04_final.stac-item
2019-02-04 10:26:01	ga_s2bm_ard_3-2-1_54HTK_2019-02-04_final.stac-item
2019-02-04 10:26:13	ga_s2bm_ard_3-2-1_54HUJ_2019-02-04_final.stac-item
2019-02-04 10:26:16	ga_s2bm_ard_3-2-1_54HTJ_2019-02-04_final.stac-item
2019-02-04 10:26:27	ga_s2bm_ard_3-2-1_54HUH_2019-02-04_final.stac-item
2019-02-04 10:26:31	ga_s2bm_ard_3-2-1_54HTH_2019-02-04_final.stac-item
2019-02-04 10:26:40	ga_s2bm_ard_3-2-1_54HUG_2019-02-04_final.stac-item
2019-02-04 10:26:45	ga_s2bm_ard_3-2-1_54HTG_2019-02-04_final.stac-item
2019-06-11 10:16:53	ga_s2bm_ard_3-2-1_54HUG_2019-06-11_final.stac-item
2019-06-11 10:16:56	ga_s2bm_ard_3-2-1_54HTG_2019-06-11_final.stac-item
2019-06-11 10:17:08	ga_s2bm_ard_3-2-1_54HUF_2019-06-11_final.stac-item
2019-06-21 10:16:54	ga_s2bm_ard_3-2-1_54HUG_2019-06-21_final.stac-item
2019-06-21 10:16:57	ga_s2bm_ard_3-2-1_54HTG_2019-06-21_final.stac-item
2019-06-21 10:17:08	ga_s2bm_ard_3-2-1_54HUF_2019-06-21_final.stac-item
2021-05-07 10:34:12	ga_s2bm_ard_3-2-1_53JRM_2021-05-07_final.stac-item
2021-05-27 10:33:31	ga_s2bm_ard_3-2-1_54KTV_2021-05-27_final.stac-item
2021-05-27 10:33:32	ga_s2bm_ard_3-2-1_53KRQ_2021-05-27_final.stac-item
2021-05-27 10:33:46	ga_s2bm_ard_3-2-1_54KTU_2021-05-27_final.stac-item
2021-05-27 10:33:46	ga_s2bm_ard_3-2-1_53KRP_2021-05-27_final.stac-item
2021-05-27 10:34:00	ga_s2bm_ard_3-2-1_53JRN_2021-05-27_final.stac-item
2021-05-27 10:34:00	ga_s2bm_ard_3-2-1_54JTT_2021-05-27_final.stac-item
2021-06-03 10:23:38	ga_s2bm_ard_3-2-1_54KTV_2021-06-03_final.stac-item
2021-06-03 10:23:41	ga_s2bm_ard_3-2-1_53KRQ_2021-06-03_final.stac-item
2021-06-03 10:23:51	ga_s2bm_ard_3-2-1_54KTU_2021-06-03_final.stac-item
2021-06-03 10:23:51	ga_s2bm_ard_3-2-1_53KRP_2021-06-03_final.stac-item
2021-06-03 10:24:05	ga_s2bm_ard_3-2-1_53JRN_2021-06-03_final.stac-item
2021-06-03 10:24:05	ga_s2bm_ard_3-2-1_54JTT_2021-06-03_final.stac-item
2021-06-03 10:24:20	ga_s2bm_ard_3-2-1_53JRM_2021-06-03_final.stac-item
2021-06-03 10:24:20	ga_s2bm_ard_3-2-1_54JTS_2021-06-03_final.stac-item
2023-01-11 10:17:11	ga_s2bm_ard_3-2-1_54HUE_2023-01-11_final
2023-01-11 10:17:25	ga_s2bm_ard_3-2-1_54HUD_2023-01-11_final
2023-01-11 10:17:35	ga_s2bm_ard_3-2-1_54HUC_2023-01-11_nrt.stac-item
2023-01-14 10:25:42	ga_s2bm_ard_3-2-1_54JTL_2023-01-14_final.stac-item
2023-01-14 10:25:53	ga_s2bm_ard_3-2-1_54HUK_2023-01-14_final.stac-item
2023-01-14 10:25:57	ga_s2bm_ard_3-2-1_54HTK_2023-01-14_final.stac-item
2023-01-14 10:26:05	ga_s2bm_ard_3-2-1_54HUJ_2023-01-14_final.stac-item
2023-01-14 10:26:07	ga_s2bm_ard_3-2-1_54HTJ_2023-01-14_final.stac-item
2023-01-14 10:26:12	ga_s2bm_ard_3-2-1_54HUJ_2023-01-14_final.stac-item
2023-01-14 10:26:13	ga_s2bm_ard_3-2-1_54HTJ_2023-01-14_final.stac-item
2023-01-14 10:26:23	ga_s2bm_ard_3-2-1_54HUH_2023-01-14_final.stac-item
2023-01-14 10:26:26	ga_s2bm_ard_3-2-1_54HTH_2023-01-14_final.stac-item
2023-01-14 10:26:36	ga_s2bm_ard_3-2-1_54HUG_2023-01-14_final.stac-item
2023-01-14 10:26:41	ga_s2bm_ard_3-2-1_54HTG_2023-01-14_final.stac-item
2023-03-28 10:32:21	ga_s2bm_ard_3-2-1_54KTE_2023-03-28_final
2023-03-28 10:32:36	ga_s2bm_ard_3-2-1_54KTD_2023-03-28_final
2023-03-28 10:32:46	ga_s2bm_ard_3-2-1_54KTC_2023-03-28_final
2023-03-28 10:32:53	ga_s2bm_ard_3-2-1_54KTC_2023-03-28_final
2023-03-28 10:32:53	ga_s2bm_ard_3-2-1_53KRT_2023-03-28_final
2023-03-28 10:33:05	ga_s2bm_ard_3-2-1_54KTB_2023-03-28_final
2023-03-28 10:33:05	ga_s2bm_ard_3-2-1_53KRS_2023-03-28_final
2023-03-28 10:33:19	ga_s2bm_ard_3-2-1_54KTA_2023-03-28_final
2023-03-28 10:33:20	ga_s2bm_ard_3-2-1_53KRR_2023-03-28_final
2023-03-28 10:33:34	ga_s2bm_ard_3-2-1_54KTV_2023-03-28_final
2023-03-28 10:33:34	ga_s2bm_ard_3-2-1_53KRQ_2023-03-28_final
2023-03-28 10:33:48	ga_s2bm_ard_3-2-1_54KTU_2023-03-28_final
2023-03-28 10:33:48	ga_s2bm_ard_3-2-1_53KRP_2023-03-28_final
2023-03-28 10:34:03	ga_s2bm_ard_3-2-1_53JRN_2023-03-28_final
2023-03-28 10:34:03	ga_s2bm_ard_3-2-1_54JTT_2023-03-28_final
2023-03-31 10:40:06	ga_s2bm_ard_3-2-1_54LTP_2023-03-31_nrt
2023-03-31 10:40:20	ga_s2bm_ard_3-2-1_54LTN_2023-03-31_nrt
2023-03-31 10:40:35	ga_s2bm_ard_3-2-1_54LTM_2023-03-31_nrt
2023-03-31 10:40:47	ga_s2bm_ard_3-2-1_54LTL_2023-03-31_nrt
2023-03-31 10:40:54	ga_s2bm_ard_3-2-1_54LTL_2023-03-31_nrt
2023-03-31 10:41:04	ga_s2bm_ard_3-2-1_54LTK_2023-03-31_nrt
2023-04-01 10:16:05	ga_s2bm_ard_3-2-1_54HUK_2023-04-01_final
2023-04-01 10:16:20	ga_s2bm_ard_3-2-1_54HUJ_2023-04-01_final
2023-04-01 10:16:24	ga_s2bm_ard_3-2-1_54HTJ_2023-04-01_final
2023-04-01 10:16:34	ga_s2bm_ard_3-2-1_54HUH_2023-04-01_final
2023-04-01 10:16:37	ga_s2bm_ard_3-2-1_54HTH_2023-04-01_final
2023-04-01 10:16:49	ga_s2bm_ard_3-2-1_54HUG_2023-04-01_final
2023-04-01 10:16:52	ga_s2bm_ard_3-2-1_54HTG_2023-04-01_final
2023-04-01 10:17:03	ga_s2bm_ard_3-2-1_54HUF_2023-04-01_final
2023-04-01 10:17:18	ga_s2bm_ard_3-2-1_54HUE_2023-04-01_final
2023-04-01 10:17:33	ga_s2bm_ard_3-2-1_54HUD_2023-04-01_final
2023-04-01 10:17:43	ga_s2bm_ard_3-2-1_54HUC_2023-04-01_nrt
2023-04-04 10:25:17	ga_s2bm_ard_3-2-1_54JUN_2023-04-04_final
2023-04-04 10:25:21	ga_s2bm_ard_3-2-1_54JTN_2023-04-04_final
2023-04-04 10:25:32	ga_s2bm_ard_3-2-1_54JUM_2023-04-04_final
2023-04-04 10:25:35	ga_s2bm_ard_3-2-1_54JTM_2023-04-04_final
2023-04-04 10:25:46	ga_s2bm_ard_3-2-1_54JUL_2023-04-04_final
2023-04-04 10:25:50	ga_s2bm_ard_3-2-1_54JTL_2023-04-04_final
2023-04-04 10:26:01	ga_s2bm_ard_3-2-1_54HUK_2023-04-04_final
2023-04-04 10:26:04	ga_s2bm_ard_3-2-1_54HTK_2023-04-04_final
2023-04-04 10:26:16	ga_s2bm_ard_3-2-1_54HUJ_2023-04-04_final
2023-04-04 10:26:19	ga_s2bm_ard_3-2-1_54HTJ_2023-04-04_final
2023-04-04 10:26:30	ga_s2bm_ard_3-2-1_54HUH_2023-04-04_final
2023-04-04 10:26:33	ga_s2bm_ard_3-2-1_54HTH_2023-04-04_final
2023-04-04 10:26:43	ga_s2bm_ard_3-2-1_54HUG_2023-04-04_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

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