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
2017-07-21 11:56:07	ga_s2bm_ard_3-2-1_50HLK_2017-07-21_final.stac-item
2017-07-21 11:56:07	ga_s2bm_ard_3-2-1_50JLL_2017-07-21_final.stac-item
2017-07-21 11:56:07	ga_s2bm_ard_3-2-1_50JLM_2017-07-21_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50JLP_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50JLQ_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50JLR_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50JLS_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50JLT_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50KLA_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50KLB_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50KLC_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50KLU_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_50KLV_2017-07-24_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_50JLP_2018-03-01_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_50JLQ_2018-03-01_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50HLH_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50HLJ_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50HLK_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JLL_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JLM_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JLN_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JLP_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JLQ_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JLR_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JLS_2018-03-18_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JLP_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JLQ_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JLR_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JLS_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JLT_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KLA_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KLB_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KLC_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KLU_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KLV_2018-03-21_final.stac-item
2019-09-22 12:03:26	ga_s2bm_ard_3-2-1_50KLC_2019-09-22_final.stac-item
2019-09-22 12:03:40	ga_s2bm_ard_3-2-1_50KLB_2019-09-22_final.stac-item
2019-09-22 12:03:55	ga_s2bm_ard_3-2-1_50KLA_2019-09-22_final.stac-item
2019-09-22 12:04:10	ga_s2bm_ard_3-2-1_50KLV_2019-09-22_final.stac-item
2019-09-22 12:04:24	ga_s2bm_ard_3-2-1_50KLU_2019-09-22_final.stac-item
2019-09-22 12:04:39	ga_s2bm_ard_3-2-1_50JLT_2019-09-22_final.stac-item
2019-09-22 12:04:53	ga_s2bm_ard_3-2-1_50JLS_2019-09-22_final.stac-item
2019-09-22 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2019-09-22_final.stac-item
2019-09-22 12:05:22	ga_s2bm_ard_3-2-1_50JLQ_2019-09-22_final.stac-item
2019-09-22 12:05:37	ga_s2bm_ard_3-2-1_50JLP_2019-09-22_final.stac-item
2019-09-29 11:57:09	ga_s2bm_ard_3-2-1_50HLH_2019-09-29_final.stac-item
2019-10-09 11:56:26	ga_s2bm_ard_3-2-1_50JLL_2019-10-09_final.stac-item
2019-10-09 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2019-10-09_final.stac-item
2019-10-09 11:56:56	ga_s2bm_ard_3-2-1_50HLJ_2019-10-09_final.stac-item
2019-10-09 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2019-10-09_final.stac-item
2019-10-12 12:03:28	ga_s2bm_ard_3-2-1_50KLC_2019-10-12_final.stac-item
2019-10-12 12:03:42	ga_s2bm_ard_3-2-1_50KLB_2019-10-12_final.stac-item
2019-10-12 12:03:57	ga_s2bm_ard_3-2-1_50KLA_2019-10-12_final.stac-item
2019-10-12 12:04:11	ga_s2bm_ard_3-2-1_50KLV_2019-10-12_final.stac-item
2019-10-12 12:04:26	ga_s2bm_ard_3-2-1_50KLU_2019-10-12_final.stac-item
2019-10-12 12:04:40	ga_s2bm_ard_3-2-1_50JLT_2019-10-12_final.stac-item
2019-12-08 11:55:07	ga_s2bm_ard_3-2-1_50JLR_2019-12-08_final.stac-item
2019-12-08 11:55:21	ga_s2bm_ard_3-2-1_50JLQ_2019-12-08_final.stac-item
2019-12-08 11:55:36	ga_s2bm_ard_3-2-1_50JLP_2019-12-08_final.stac-item
2019-12-08 11:55:50	ga_s2bm_ard_3-2-1_50JLN_2019-12-08_final.stac-item
2019-12-08 11:56:05	ga_s2bm_ard_3-2-1_50JLM_2019-12-08_final.stac-item
2019-12-08 11:56:20	ga_s2bm_ard_3-2-1_50JLL_2019-12-08_final.stac-item
2019-12-08 11:56:34	ga_s2bm_ard_3-2-1_50HLK_2019-12-08_final.stac-item
2019-12-08 11:56:49	ga_s2bm_ard_3-2-1_50HLJ_2019-12-08_final.stac-item
2019-12-08 11:57:03	ga_s2bm_ard_3-2-1_50HLH_2019-12-08_final.stac-item
2019-12-21 12:03:21	ga_s2bm_ard_3-2-1_50KLC_2019-12-21_final.stac-item
2019-12-21 12:03:36	ga_s2bm_ard_3-2-1_50KLB_2019-12-21_final.stac-item
2019-12-21 12:03:51	ga_s2bm_ard_3-2-1_50KLA_2019-12-21_final.stac-item
2019-12-21 12:04:05	ga_s2bm_ard_3-2-1_50KLV_2019-12-21_final.stac-item
2019-12-21 12:04:20	ga_s2bm_ard_3-2-1_50KLU_2019-12-21_final.stac-item
2019-12-21 12:04:34	ga_s2bm_ard_3-2-1_50JLT_2019-12-21_final.stac-item
2019-12-21 12:04:49	ga_s2bm_ard_3-2-1_50JLS_2019-12-21_final.stac-item
2019-12-21 12:05:03	ga_s2bm_ard_3-2-1_50JLR_2019-12-21_final.stac-item
2023-05-28 11:47:31	ga_s2bm_ard_3-2-1_50HLG_2023-05-28_final
2023-05-31 11:55:02	ga_s2bm_ard_3-2-1_50JLS_2023-05-31_final
2023-05-31 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2023-05-31_final
2023-05-31 11:55:31	ga_s2bm_ard_3-2-1_50JLQ_2023-05-31_final
2023-05-31 11:55:46	ga_s2bm_ard_3-2-1_50JLP_2023-05-31_final
2023-05-31 11:56:00	ga_s2bm_ard_3-2-1_50JLN_2023-05-31_final
2023-05-31 11:56:15	ga_s2bm_ard_3-2-1_50JLM_2023-05-31_final
2023-05-31 11:56:29	ga_s2bm_ard_3-2-1_50JLL_2023-05-31_final
2023-05-31 11:56:44	ga_s2bm_ard_3-2-1_50HLK_2023-05-31_final
2023-05-31 11:56:59	ga_s2bm_ard_3-2-1_50HLJ_2023-05-31_final
2023-05-31 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2023-05-31_final
2023-05-31 11:57:26	ga_s2bm_ard_3-2-1_50HLG_2023-05-31_final
2023-06-03 12:03:30	ga_s2bm_ard_3-2-1_50KLC_2023-06-03_final
2023-06-03 12:03:45	ga_s2bm_ard_3-2-1_50KLB_2023-06-03_final
2023-06-03 12:04:00	ga_s2bm_ard_3-2-1_50KLA_2023-06-03_final
2023-06-03 12:04:14	ga_s2bm_ard_3-2-1_50KLV_2023-06-03_final
2023-06-03 12:04:28	ga_s2bm_ard_3-2-1_50KLU_2023-06-03_final
2023-06-03 12:04:35	ga_s2bm_ard_3-2-1_50KLU_2023-06-03_final
2023-06-03 12:04:43	ga_s2bm_ard_3-2-1_50JLT_2023-06-03_final
2023-06-03 12:04:58	ga_s2bm_ard_3-2-1_50JLS_2023-06-03_final
2023-06-03 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2023-06-03_final
2023-06-03 12:05:27	ga_s2bm_ard_3-2-1_50JLQ_2023-06-03_final
2023-06-03 12:05:41	ga_s2bm_ard_3-2-1_50JLP_2023-06-03_final
2023-06-07 11:47:31	ga_s2bm_ard_3-2-1_50HLG_2023-06-07_final
2023-06-20 11:56:44	ga_s2bm_ard_3-2-1_50HLK_2023-06-20_final
2023-06-20 11:56:59	ga_s2bm_ard_3-2-1_50HLJ_2023-06-20_final
2023-06-20 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2023-06-20_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

All years