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
2019-08-08 09:36:58	ga_s2bm_ard_3-2-1_55HEA_2019-08-08_final.stac-item
2019-08-08 09:37:11	ga_s2bm_ard_3-2-1_55HEV_2019-08-08_final.stac-item
2019-08-08 09:37:26	ga_s2bm_ard_3-2-1_55HEU_2019-08-08_final.stac-item
2019-08-08 09:37:40	ga_s2bm_ard_3-2-1_55HET_2019-08-08_final.stac-item
2019-08-08 09:37:53	ga_s2bm_ard_3-2-1_55HES_2019-08-08_final.stac-item
2019-08-08 09:38:00	ga_s2bm_ard_3-2-1_55GER_2019-08-08_final.stac-item
2019-08-08 09:38:00	ga_s2bm_ard_3-2-1_55HES_2019-08-08_final.stac-item
2019-08-08 09:38:09	ga_s2bm_ard_3-2-1_55GER_2019-08-08_final.stac-item
2019-08-18 09:36:56	ga_s2bm_ard_3-2-1_55HEA_2019-08-18_final.stac-item
2019-08-18 09:37:10	ga_s2bm_ard_3-2-1_55HEV_2019-08-18_final.stac-item
2019-11-06 09:36:50	ga_s2bm_ard_3-2-1_55HEA_2019-11-06_final.stac-item
2019-11-06 09:37:04	ga_s2bm_ard_3-2-1_55HEV_2019-11-06_final.stac-item
2019-11-06 09:37:18	ga_s2bm_ard_3-2-1_55HEU_2019-11-06_final.stac-item
2019-11-06 09:37:33	ga_s2bm_ard_3-2-1_55HET_2019-11-06_final.stac-item
2019-11-06 09:37:47	ga_s2bm_ard_3-2-1_55HES_2019-11-06_final.stac-item
2019-11-06 09:38:02	ga_s2bm_ard_3-2-1_55GER_2019-11-06_final.stac-item
2019-11-06 09:38:16	ga_s2bm_ard_3-2-1_55GEQ_2019-11-06_final.stac-item
2019-11-06 09:38:31	ga_s2bm_ard_3-2-1_55GEP_2019-11-06_final.stac-item
2019-11-09 09:44:35	ga_s2bm_ard_3-2-1_55JEK_2019-11-09_final.stac-item
2019-11-09 09:44:49	ga_s2bm_ard_3-2-1_55JEJ_2019-11-09_final.stac-item
2019-11-09 09:45:04	ga_s2bm_ard_3-2-1_55JEH_2019-11-09_final.stac-item
2019-11-09 09:45:18	ga_s2bm_ard_3-2-1_55JEG_2019-11-09_final.stac-item
2019-11-09 09:45:33	ga_s2bm_ard_3-2-1_55JEF_2019-11-09_final.stac-item
2019-11-09 09:45:47	ga_s2bm_ard_3-2-1_55HEE_2019-11-09_final.stac-item
2019-11-09 09:46:02	ga_s2bm_ard_3-2-1_55HED_2019-11-09_final.stac-item
2019-11-09 09:46:16	ga_s2bm_ard_3-2-1_55HEC_2019-11-09_final.stac-item
2019-11-09 09:46:31	ga_s2bm_ard_3-2-1_55HEB_2019-11-09_final.stac-item
2019-11-09 09:46:38	ga_s2bm_ard_3-2-1_55HEB_2019-11-09_final.stac-item
2019-11-09 09:46:38	ga_s2bm_ard_3-2-1_55HEA_2019-11-09_final.stac-item
2019-11-09 09:46:45	ga_s2bm_ard_3-2-1_55HEA_2019-11-09_final.stac-item
2019-11-13 09:28:48	ga_s2bm_ard_3-2-1_55GEN_2019-11-12_final.stac-item
2019-11-16 09:36:49	ga_s2bm_ard_3-2-1_55HEA_2019-11-16_final.stac-item
2019-11-16 09:37:02	ga_s2bm_ard_3-2-1_55HEV_2019-11-16_final.stac-item
2019-11-16 09:37:17	ga_s2bm_ard_3-2-1_55HEU_2019-11-16_final.stac-item
2019-11-16 09:37:31	ga_s2bm_ard_3-2-1_55HET_2019-11-16_final.stac-item
2019-11-16 09:37:46	ga_s2bm_ard_3-2-1_55HES_2019-11-16_final.stac-item
2019-11-16 09:38:00	ga_s2bm_ard_3-2-1_55GER_2019-11-16_final.stac-item
2019-11-16 09:38:15	ga_s2bm_ard_3-2-1_55GEQ_2019-11-16_final.stac-item
2019-11-16 09:38:29	ga_s2bm_ard_3-2-1_55GEP_2019-11-16_final.stac-item
2019-11-19 09:44:34	ga_s2bm_ard_3-2-1_55JEK_2019-11-19_final.stac-item
2019-11-19 09:44:47	ga_s2bm_ard_3-2-1_55JEJ_2019-11-19_final.stac-item
2019-11-19 09:45:02	ga_s2bm_ard_3-2-1_55JEH_2019-11-19_final.stac-item
2019-11-19 09:45:17	ga_s2bm_ard_3-2-1_55JEG_2019-11-19_final.stac-item
2019-11-19 09:45:31	ga_s2bm_ard_3-2-1_55JEF_2019-11-19_final.stac-item
2019-11-19 09:45:45	ga_s2bm_ard_3-2-1_55HEE_2019-11-19_final.stac-item
2019-11-19 09:46:00	ga_s2bm_ard_3-2-1_55HED_2019-11-19_final.stac-item
2019-11-25 10:01:10	ga_s2bm_ard_3-2-1_55LFC_2019-11-25_final.stac-item
2019-11-25 10:01:14	ga_s2bm_ard_3-2-1_55LEC_2019-11-25_final.stac-item
2019-11-25 10:01:25	ga_s2bm_ard_3-2-1_55KFB_2019-11-25_final.stac-item
2019-11-25 10:01:29	ga_s2bm_ard_3-2-1_55KEB_2019-11-25_final.stac-item
2019-11-25 10:01:39	ga_s2bm_ard_3-2-1_55KFA_2019-11-25_final.stac-item
2019-11-25 10:01:57	ga_s2bm_ard_3-2-1_55KEV_2019-11-25_final.stac-item
2019-11-25 10:02:12	ga_s2bm_ard_3-2-1_55KEU_2019-11-25_final.stac-item
2019-11-29 09:44:31	ga_s2bm_ard_3-2-1_55JEK_2019-11-29_final.stac-item
2019-11-29 09:44:45	ga_s2bm_ard_3-2-1_55JEJ_2019-11-29_final.stac-item
2019-11-29 09:45:00	ga_s2bm_ard_3-2-1_55JEH_2019-11-29_final.stac-item
2019-11-29 09:45:14	ga_s2bm_ard_3-2-1_55JEG_2019-11-29_final.stac-item
2019-11-29 09:45:29	ga_s2bm_ard_3-2-1_55JEF_2019-11-29_final.stac-item
2019-11-29 09:45:43	ga_s2bm_ard_3-2-1_55HEE_2019-11-29_final.stac-item
2019-11-29 09:45:58	ga_s2bm_ard_3-2-1_55HED_2019-11-29_final.stac-item
2019-11-29 09:46:12	ga_s2bm_ard_3-2-1_55HEC_2019-11-29_final.stac-item
2019-11-29 09:46:27	ga_s2bm_ard_3-2-1_55HEB_2019-11-29_final.stac-item
2019-11-29 09:46:41	ga_s2bm_ard_3-2-1_55HEA_2019-11-29_final.stac-item
2019-11-29 09:46:56	ga_s2bm_ard_3-2-1_55HEV_2019-11-29_final.stac-item
2019-11-29 09:47:10	ga_s2bm_ard_3-2-1_55HEU_2019-11-29_final.stac-item
2019-11-29 09:47:24	ga_s2bm_ard_3-2-1_55HET_2019-11-29_final.stac-item
2019-11-29 09:47:39	ga_s2bm_ard_3-2-1_55HES_2019-11-29_final.stac-item
2024-05-12 09:59:47	ga_s2bm_ard_3-2-1_55LFJ_2024-05-12_nrt
2024-05-12 09:59:51	ga_s2bm_ard_3-2-1_55LEJ_2024-05-12_nrt
2024-05-12 10:00:02	ga_s2bm_ard_3-2-1_55LFH_2024-05-12_nrt
2024-05-12 10:00:05	ga_s2bm_ard_3-2-1_55LEH_2024-05-12_nrt
2024-05-12 10:00:16	ga_s2bm_ard_3-2-1_55LFG_2024-05-12_nrt
2024-05-12 10:00:20	ga_s2bm_ard_3-2-1_55LEG_2024-05-12_nrt
2024-05-12 10:00:31	ga_s2bm_ard_3-2-1_55LFF_2024-05-12_nrt
2024-05-13 09:37:33	ga_s2bm_ard_3-2-1_55HET_2024-05-13_final
2024-05-13 09:37:47	ga_s2bm_ard_3-2-1_55HES_2024-05-13_final
2024-05-13 09:38:02	ga_s2bm_ard_3-2-1_55GER_2024-05-13_final
2024-05-13 09:38:16	ga_s2bm_ard_3-2-1_55GEQ_2024-05-13_final
2024-05-13 09:38:30	ga_s2bm_ard_3-2-1_55GEP_2024-05-13_final
2024-05-13 09:38:45	ga_s2bm_ard_3-2-1_55GEN_2024-05-13_final
2024-05-13 09:38:59	ga_s2bm_ard_3-2-1_55GEM_2024-05-13_final
2024-05-16 09:44:34	ga_s2bm_ard_3-2-1_55JEK_2024-05-16_final
2024-05-16 09:44:47	ga_s2bm_ard_3-2-1_55JEJ_2024-05-16_final
2024-05-16 09:45:02	ga_s2bm_ard_3-2-1_55JEH_2024-05-16_final
2024-05-16 09:46:29	ga_s2bm_ard_3-2-1_55HEB_2024-05-16_final
2024-05-16 09:46:44	ga_s2bm_ard_3-2-1_55HEA_2024-05-16_final
2024-05-16 09:46:58	ga_s2bm_ard_3-2-1_55HEV_2024-05-16_final
2024-05-16 09:47:12	ga_s2bm_ard_3-2-1_55HEU_2024-05-16_final
2024-05-16 09:47:27	ga_s2bm_ard_3-2-1_55HET_2024-05-16_final
2024-05-16 09:47:41	ga_s2bm_ard_3-2-1_55HES_2024-05-16_final
2024-06-05 09:44:38	ga_s2bm_ard_3-2-1_55JEK_2024-06-05_nrt
2024-06-05 09:44:52	ga_s2bm_ard_3-2-1_55JEJ_2024-06-05_nrt
2024-06-05 09:45:06	ga_s2bm_ard_3-2-1_55JEH_2024-06-05_nrt
2024-06-05 09:45:21	ga_s2bm_ard_3-2-1_55JEG_2024-06-05_nrt
2024-06-05 09:45:35	ga_s2bm_ard_3-2-1_55JEF_2024-06-05_nrt
2024-06-05 09:45:50	ga_s2bm_ard_3-2-1_55HEE_2024-06-05_nrt
2024-06-05 09:46:04	ga_s2bm_ard_3-2-1_55HED_2024-06-05_nrt
2024-06-05 09:46:19	ga_s2bm_ard_3-2-1_55HEC_2024-06-05_nrt
2024-06-05 09:46:33	ga_s2bm_ard_3-2-1_55HEB_2024-06-05_nrt
2024-06-05 09:46:48	ga_s2bm_ard_3-2-1_55HEA_2024-06-05_nrt

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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