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
2018-11-06 12:03:24	ga_s2bm_ard_3-2-1_50KLC_2018-11-06_final.stac-item
2018-11-06 12:03:39	ga_s2bm_ard_3-2-1_50KLB_2018-11-06_final.stac-item
2018-11-06 12:03:53	ga_s2bm_ard_3-2-1_50KLA_2018-11-06_final.stac-item
2018-11-06 12:04:08	ga_s2bm_ard_3-2-1_50KLV_2018-11-06_final.stac-item
2018-11-06 12:04:22	ga_s2bm_ard_3-2-1_50KLU_2018-11-06_final.stac-item
2018-11-06 12:04:37	ga_s2bm_ard_3-2-1_50JLT_2018-11-06_final.stac-item
2018-11-06 12:04:51	ga_s2bm_ard_3-2-1_50JLS_2018-11-06_final.stac-item
2018-11-06 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2018-11-06_final.stac-item
2018-11-10 11:47:07	ga_s2bm_ard_3-2-1_50HMH_2018-11-10_final.stac-item
2018-11-10 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2018-11-10_final.stac-item
2018-11-16 12:03:24	ga_s2bm_ard_3-2-1_50KLC_2018-11-16_final.stac-item
2018-11-16 12:03:38	ga_s2bm_ard_3-2-1_50KLB_2018-11-16_final.stac-item
2018-11-16 12:03:53	ga_s2bm_ard_3-2-1_50KLA_2018-11-16_final.stac-item
2018-11-16 12:04:07	ga_s2bm_ard_3-2-1_50KLV_2018-11-16_final.stac-item
2018-11-16 12:04:22	ga_s2bm_ard_3-2-1_50KLU_2018-11-16_final.stac-item
2018-11-16 12:04:36	ga_s2bm_ard_3-2-1_50JLT_2018-11-16_final.stac-item
2018-11-16 12:04:51	ga_s2bm_ard_3-2-1_50JLS_2018-11-16_final.stac-item
2018-11-16 12:05:05	ga_s2bm_ard_3-2-1_50JLR_2018-11-16_final.stac-item
2018-11-20 11:47:07	ga_s2bm_ard_3-2-1_50HMH_2018-11-20_final.stac-item
2018-11-20 11:47:11	ga_s2bm_ard_3-2-1_50HLH_2018-11-20_final.stac-item
2018-11-23 11:54:41	ga_s2bm_ard_3-2-1_50JLT_2018-11-23_final.stac-item
2018-11-23 11:54:54	ga_s2bm_ard_3-2-1_50JLS_2018-11-23_final.stac-item
2018-11-23 11:55:09	ga_s2bm_ard_3-2-1_50JLR_2018-11-23_final.stac-item
2018-11-23 11:55:24	ga_s2bm_ard_3-2-1_50JLQ_2018-11-23_final.stac-item
2018-11-23 11:55:38	ga_s2bm_ard_3-2-1_50JLP_2018-11-23_final.stac-item
2018-11-23 11:55:53	ga_s2bm_ard_3-2-1_50JLN_2018-11-23_final.stac-item
2018-11-23 11:56:08	ga_s2bm_ard_3-2-1_50JLM_2018-11-23_final.stac-item
2018-11-23 11:56:22	ga_s2bm_ard_3-2-1_50JLL_2018-11-23_final.stac-item
2018-11-23 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2018-11-23_final.stac-item
2018-11-23 11:56:51	ga_s2bm_ard_3-2-1_50HLJ_2018-11-23_final.stac-item
2018-11-23 11:57:02	ga_s2bm_ard_3-2-1_50HMH_2018-11-23_final.stac-item
2018-11-23 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2018-11-23_final.stac-item
2019-03-23 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2019-03-23_final.stac-item
2019-03-23 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2019-03-23_final.stac-item
2019-03-23 11:57:09	ga_s2bm_ard_3-2-1_50HLH_2019-03-23_final.stac-item
2019-03-26 12:03:27	ga_s2bm_ard_3-2-1_50KLC_2019-03-26_final.stac-item
2019-03-26 12:03:42	ga_s2bm_ard_3-2-1_50KLB_2019-03-26_final.stac-item
2019-03-26 12:03:56	ga_s2bm_ard_3-2-1_50KLA_2019-03-26_final.stac-item
2019-03-26 12:04:11	ga_s2bm_ard_3-2-1_50KLV_2019-03-26_final.stac-item
2019-03-26 12:04:26	ga_s2bm_ard_3-2-1_50KLU_2019-03-26_final.stac-item
2019-03-26 12:04:40	ga_s2bm_ard_3-2-1_50JLT_2019-03-26_final.stac-item
2019-03-26 12:04:54	ga_s2bm_ard_3-2-1_50JLS_2019-03-26_final.stac-item
2019-03-26 12:05:09	ga_s2bm_ard_3-2-1_50JLR_2019-03-26_final.stac-item
2019-04-05 12:03:30	ga_s2bm_ard_3-2-1_50KLC_2019-04-05_final.stac-item
2019-04-05 12:03:44	ga_s2bm_ard_3-2-1_50KLB_2019-04-05_final.stac-item
2019-04-05 12:03:59	ga_s2bm_ard_3-2-1_50KLA_2019-04-05_final.stac-item
2019-04-05 12:04:13	ga_s2bm_ard_3-2-1_50KLV_2019-04-05_final.stac-item
2019-04-05 12:04:28	ga_s2bm_ard_3-2-1_50KLU_2019-04-05_final.stac-item
2019-04-05 12:04:43	ga_s2bm_ard_3-2-1_50JLT_2019-04-05_final.stac-item
2019-04-05 12:04:57	ga_s2bm_ard_3-2-1_50JLS_2019-04-05_final.stac-item
2019-04-05 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2019-04-05_final.stac-item
2019-06-04 12:03:35	ga_s2bm_ard_3-2-1_50KLC_2019-06-04_final.stac-item
2019-06-04 12:03:49	ga_s2bm_ard_3-2-1_50KLB_2019-06-04_final.stac-item
2019-06-04 12:04:04	ga_s2bm_ard_3-2-1_50KLA_2019-06-04_final.stac-item
2019-06-04 12:04:18	ga_s2bm_ard_3-2-1_50KLV_2019-06-04_final.stac-item
2019-06-04 12:04:33	ga_s2bm_ard_3-2-1_50KLU_2019-06-04_final.stac-item
2019-06-04 12:04:47	ga_s2bm_ard_3-2-1_50JLT_2019-06-04_final.stac-item
2020-03-17 11:54:42	ga_s2bm_ard_3-2-1_50JLT_2020-03-17_final.stac-item
2020-03-17 11:54:56	ga_s2bm_ard_3-2-1_50JLS_2020-03-17_final.stac-item
2020-03-17 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2020-03-17_final.stac-item
2020-03-17 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2020-03-17_final.stac-item
2020-03-17 11:55:40	ga_s2bm_ard_3-2-1_50JLP_2020-03-17_final.stac-item
2020-03-17 11:55:54	ga_s2bm_ard_3-2-1_50JLN_2020-03-17_final.stac-item
2020-03-17 11:56:09	ga_s2bm_ard_3-2-1_50JLM_2020-03-17_final.stac-item
2020-03-17 11:56:23	ga_s2bm_ard_3-2-1_50JLL_2020-03-17_final.stac-item
2020-03-17 11:56:38	ga_s2bm_ard_3-2-1_50HLK_2020-03-17_final.stac-item
2020-03-17 11:56:53	ga_s2bm_ard_3-2-1_50HLJ_2020-03-17_final.stac-item
2020-03-17 11:57:04	ga_s2bm_ard_3-2-1_50HMH_2020-03-17_final.stac-item
2020-03-17 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2020-03-17_final.stac-item
2020-03-24 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2020-03-24_final.stac-item
2020-03-27 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2020-03-27_final.stac-item
2020-03-27 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2020-03-27_final.stac-item
2020-04-06 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2020-04-06_final.stac-item
2020-04-06 11:56:52	ga_s2bm_ard_3-2-1_50HLJ_2020-04-06_final.stac-item
2020-04-06 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2020-04-06_final.stac-item
2020-04-06 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2020-04-06_final.stac-item
2020-04-16 11:56:07	ga_s2bm_ard_3-2-1_50JLM_2020-04-16_final.stac-item
2020-04-16 11:56:21	ga_s2bm_ard_3-2-1_50JLL_2020-04-16_final.stac-item
2020-04-16 11:56:36	ga_s2bm_ard_3-2-1_50HLK_2020-04-16_final.stac-item
2020-04-16 11:56:50	ga_s2bm_ard_3-2-1_50HLJ_2020-04-16_final.stac-item
2020-04-16 11:57:01	ga_s2bm_ard_3-2-1_50HMH_2020-04-16_final.stac-item
2020-04-16 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2020-04-16_final.stac-item
2020-04-19 12:03:22	ga_s2bm_ard_3-2-1_50KLC_2020-04-19_final.stac-item
2020-04-19 12:03:36	ga_s2bm_ard_3-2-1_50KLB_2020-04-19_final.stac-item
2020-04-19 12:03:51	ga_s2bm_ard_3-2-1_50KLA_2020-04-19_final.stac-item
2020-04-19 12:04:05	ga_s2bm_ard_3-2-1_50KLV_2020-04-19_final.stac-item
2020-04-19 12:04:20	ga_s2bm_ard_3-2-1_50KLU_2020-04-19_final.stac-item
2020-04-19 12:04:34	ga_s2bm_ard_3-2-1_50JLT_2020-04-19_final.stac-item
2020-04-19 12:04:49	ga_s2bm_ard_3-2-1_50JLS_2020-04-19_final.stac-item
2020-04-19 12:05:03	ga_s2bm_ard_3-2-1_50JLR_2020-04-19_final.stac-item
2021-10-28 11:54:46	ga_s2bm_ard_3-2-1_50JLT_2021-10-28_final.stac-item
2021-10-28 11:54:58	ga_s2bm_ard_3-2-1_50JLS_2021-10-28_final.stac-item
2021-10-28 11:55:04	ga_s2bm_ard_3-2-1_50JLS_2021-10-28_final.stac-item
2021-10-28 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2021-10-28_final.stac-item
2021-10-28 11:55:06	ga_s2bm_ard_3-2-1_50JLR_2021-10-28_final.stac-item
2021-10-28 11:55:14	ga_s2bm_ard_3-2-1_50JLR_2021-10-28_final.stac-item
2021-10-28 11:55:29	ga_s2bm_ard_3-2-1_50JLQ_2021-10-28_final.stac-item
2021-10-28 11:55:43	ga_s2bm_ard_3-2-1_50JLP_2021-10-28_final.stac-item
2021-10-28 11:55:58	ga_s2bm_ard_3-2-1_50JLN_2021-10-28_final.stac-item
2021-10-28 11:56:12	ga_s2bm_ard_3-2-1_50JLM_2021-10-28_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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