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
2017-07-11 11:49:46	ga_s2bm_ard_3-2-1_50KQA_2017-07-11_final.stac-item
2017-07-11 11:49:46	ga_s2bm_ard_3-2-1_50KQB_2017-07-11_final.stac-item
2017-07-11 11:49:46	ga_s2bm_ard_3-2-1_50KQC_2017-07-11_final.stac-item
2017-07-11 11:49:46	ga_s2bm_ard_3-2-1_50KQU_2017-07-11_final.stac-item
2017-07-11 11:49:46	ga_s2bm_ard_3-2-1_50KQV_2017-07-11_final.stac-item
2018-06-26 11:47:27	ga_s2bm_ard_3-2-1_50KQA_2018-06-26_final.stac-item
2018-06-26 11:47:27	ga_s2bm_ard_3-2-1_50KQB_2018-06-26_final.stac-item
2018-06-26 11:47:27	ga_s2bm_ard_3-2-1_50KQC_2018-06-26_final.stac-item
2018-06-26 11:47:27	ga_s2bm_ard_3-2-1_50KQU_2018-06-26_final.stac-item
2018-06-26 11:47:27	ga_s2bm_ard_3-2-1_50KQV_2018-06-26_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_50HPH_2018-07-10_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_50HPJ_2018-07-10_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_50HPK_2018-07-10_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_50HQJ_2018-07-10_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_50HQK_2018-07-10_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_50JPL_2018-07-10_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_50JQL_2018-07-10_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JQS_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JQT_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50KQA_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50KQU_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50KQV_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50HPH_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50HPJ_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50HPK_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50HQJ_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50HQK_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JPL_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JPM_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JPN_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JPP_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JPQ_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JQL_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JQM_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JQN_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JQP_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JQQ_2018-07-13_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JQR_2018-07-13_final.stac-item
2018-07-13 11:46:48	ga_s2bm_ard_3-2-1_50HPH_2018-07-13_final.stac-item
2018-07-13 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_2018-07-13_final.stac-item
2019-08-27 11:45:26	ga_s2bm_ard_3-2-1_50JPQ_2019-08-27_final.stac-item
2019-08-27 11:45:40	ga_s2bm_ard_3-2-1_50JPP_2019-08-27_final.stac-item
2019-08-27 11:45:55	ga_s2bm_ard_3-2-1_50JPN_2019-08-27_final.stac-item
2019-08-27 11:46:09	ga_s2bm_ard_3-2-1_50JPM_2019-08-27_final.stac-item
2019-08-27 11:46:23	ga_s2bm_ard_3-2-1_50JPL_2019-08-27_final.stac-item
2019-08-27 11:46:34	ga_s2bm_ard_3-2-1_50HQK_2019-08-27_final.stac-item
2019-08-27 11:46:38	ga_s2bm_ard_3-2-1_50HPK_2019-08-27_final.stac-item
2019-08-27 11:46:47	ga_s2bm_ard_3-2-1_50HQJ_2019-08-27_final.stac-item
2019-08-27 11:46:52	ga_s2bm_ard_3-2-1_50HPJ_2019-08-27_final.stac-item
2019-08-27 11:47:07	ga_s2bm_ard_3-2-1_50HPH_2019-08-27_final.stac-item
2019-09-03 11:36:23	ga_s2bm_ard_3-2-1_50JQL_2019-09-03_final.stac-item
2019-09-03 11:36:29	ga_s2bm_ard_3-2-1_50JPL_2019-09-03_final.stac-item
2019-09-03 11:36:37	ga_s2bm_ard_3-2-1_50HQK_2019-09-03_final.stac-item
2019-09-03 11:36:41	ga_s2bm_ard_3-2-1_50HPK_2019-09-03_final.stac-item
2019-09-03 11:36:51	ga_s2bm_ard_3-2-1_50HQJ_2019-09-03_final.stac-item
2019-09-03 11:36:55	ga_s2bm_ard_3-2-1_50HPJ_2019-09-03_final.stac-item
2019-09-03 11:37:10	ga_s2bm_ard_3-2-1_50HPH_2019-09-03_final.stac-item
2019-09-09 11:53:19	ga_s2bm_ard_3-2-1_50KQC_2019-09-09_final.stac-item
2019-09-09 11:53:33	ga_s2bm_ard_3-2-1_50KQB_2019-09-09_final.stac-item
2019-09-09 11:53:48	ga_s2bm_ard_3-2-1_50KQA_2019-09-09_final.stac-item
2019-09-09 11:54:02	ga_s2bm_ard_3-2-1_50KQV_2019-09-09_final.stac-item
2019-09-09 11:54:15	ga_s2bm_ard_3-2-1_50KQU_2019-09-09_final.stac-item
2019-09-16 11:43:51	ga_s2bm_ard_3-2-1_50KQA_2019-09-16_final.stac-item
2019-09-16 11:44:05	ga_s2bm_ard_3-2-1_50KQV_2019-09-16_final.stac-item
2019-09-16 11:44:19	ga_s2bm_ard_3-2-1_50KQU_2019-09-16_final.stac-item
2024-03-06 11:53:42	ga_s2bm_ard_3-2-1_50KQA_2024-03-06_final
2024-03-06 11:53:56	ga_s2bm_ard_3-2-1_50KQV_2024-03-06_final
2024-03-06 11:54:09	ga_s2bm_ard_3-2-1_50KQU_2024-03-06_final
2024-03-10 11:36:15	ga_s2bm_ard_3-2-1_50JQL_2024-03-10_final
2024-03-10 11:36:22	ga_s2bm_ard_3-2-1_50JPL_2024-03-10_final
2024-03-10 11:36:29	ga_s2bm_ard_3-2-1_50HQK_2024-03-10_final
2024-03-10 11:36:33	ga_s2bm_ard_3-2-1_50HPK_2024-03-10_final
2024-03-10 11:36:44	ga_s2bm_ard_3-2-1_50HQJ_2024-03-10_final
2024-03-10 11:36:47	ga_s2bm_ard_3-2-1_50HPJ_2024-03-10_final
2024-03-10 11:37:02	ga_s2bm_ard_3-2-1_50HPH_2024-03-10_final
2024-03-10 11:37:15	ga_s2bm_ard_3-2-1_50HPG_2024-03-10_final
2024-03-10 11:37:21	ga_s2bm_ard_3-2-1_50HPG_2024-03-10_final
2024-03-10 11:37:26	ga_s2bm_ard_3-2-1_50HPF_2024-03-10_nrt
2024-03-13 11:43:48	ga_s2bm_ard_3-2-1_50KQA_2024-03-13_final
2024-03-13 11:44:02	ga_s2bm_ard_3-2-1_50KQV_2024-03-13_final
2024-03-13 11:44:17	ga_s2bm_ard_3-2-1_50KQU_2024-03-13_final
2024-03-13 11:44:31	ga_s2bm_ard_3-2-1_50JQT_2024-03-13_final
2024-03-13 11:44:42	ga_s2bm_ard_3-2-1_50JQS_2024-03-13_final
2024-03-13 11:44:49	ga_s2bm_ard_3-2-1_50JQS_2024-03-13_final
2024-03-13 11:45:00	ga_s2bm_ard_3-2-1_50JQR_2024-03-13_final
2024-03-13 11:45:15	ga_s2bm_ard_3-2-1_50JQQ_2024-03-13_final
2024-03-13 11:45:18	ga_s2bm_ard_3-2-1_50JPQ_2024-03-13_final
2024-03-13 11:45:29	ga_s2bm_ard_3-2-1_50JQP_2024-03-13_final
2024-03-13 11:45:33	ga_s2bm_ard_3-2-1_50JPP_2024-03-13_final
2024-03-13 11:45:43	ga_s2bm_ard_3-2-1_50JQN_2024-03-13_final
2024-03-20 11:36:19	ga_s2bm_ard_3-2-1_50JQL_2024-03-20_final
2024-03-20 11:36:26	ga_s2bm_ard_3-2-1_50JPL_2024-03-20_final
2024-03-20 11:36:34	ga_s2bm_ard_3-2-1_50HQK_2024-03-20_final
2024-03-20 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2024-03-20_final
2024-03-26 11:52:20	ga_s2bm_ard_3-2-1_50KQG_2024-03-26_final
2024-03-26 11:52:34	ga_s2bm_ard_3-2-1_50KQF_2024-03-26_final
2024-03-26 11:52:49	ga_s2bm_ard_3-2-1_50KQE_2024-03-26_final
2024-03-26 11:53:03	ga_s2bm_ard_3-2-1_50KQD_2024-03-26_final
2024-03-26 11:53:18	ga_s2bm_ard_3-2-1_50KQC_2024-03-26_final
2024-03-26 11:53:32	ga_s2bm_ard_3-2-1_50KQB_2024-03-26_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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