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
2017-12-16 09:32:28	ga_s2bm_ard_3-2-1_56JKN_2017-12-16_final.stac-item
2017-12-16 09:32:28	ga_s2bm_ard_3-2-1_56JKP_2017-12-16_final.stac-item
2017-12-16 09:32:28	ga_s2bm_ard_3-2-1_56JLP_2017-12-16_final.stac-item
2017-12-16 09:32:28	ga_s2bm_ard_3-2-1_56JMP_2017-12-16_final.stac-item
2017-12-16 09:32:28	ga_s2bm_ard_3-2-1_55JGH_2017-12-16_final.stac-item
2017-12-16 09:32:28	ga_s2bm_ard_3-2-1_55JGJ_2017-12-16_final.stac-item
2019-07-29 09:34:45	ga_s2bm_ard_3-2-1_56JMP_2019-07-29_final.stac-item
2019-07-29 09:34:49	ga_s2bm_ard_3-2-1_56JLP_2019-07-29_final.stac-item
2019-07-29 09:34:52	ga_s2bm_ard_3-2-1_56JKP_2019-07-29_final.stac-item
2019-07-29 09:34:58	ga_s2bm_ard_3-2-1_55JGJ_2019-07-29_final.stac-item
2019-07-29 09:35:06	ga_s2bm_ard_3-2-1_56JKN_2019-07-29_final.stac-item
2019-07-29 09:35:09	ga_s2bm_ard_3-2-1_55JGH_2019-07-29_final.stac-item
2019-07-31 11:55:43	ga_s2bm_ard_3-2-1_50JNP_2019-07-31_final.stac-item
2019-07-31 11:55:47	ga_s2bm_ard_3-2-1_50JMP_2019-07-31_final.stac-item
2019-07-31 11:55:50	ga_s2bm_ard_3-2-1_50JLP_2019-07-31_final.stac-item
2019-07-31 11:55:54	ga_s2bm_ard_3-2-1_50JKP_2019-07-31_final.stac-item
2019-07-31 11:56:07	ga_s2bm_ard_3-2-1_50JKN_2019-07-31_final.stac-item
2019-08-08 09:34:44	ga_s2bm_ard_3-2-1_56JMP_2019-08-08_final.stac-item
2019-08-08 09:34:48	ga_s2bm_ard_3-2-1_56JLP_2019-08-08_final.stac-item
2019-08-08 09:34:51	ga_s2bm_ard_3-2-1_56JKP_2019-08-08_final.stac-item
2019-08-08 09:34:57	ga_s2bm_ard_3-2-1_55JGJ_2019-08-08_final.stac-item
2019-08-08 09:35:06	ga_s2bm_ard_3-2-1_56JKN_2019-08-08_final.stac-item
2019-08-08 09:35:09	ga_s2bm_ard_3-2-1_55JGH_2019-08-08_final.stac-item
2019-08-10 11:55:42	ga_s2bm_ard_3-2-1_50JNP_2019-08-10_final.stac-item
2019-08-10 11:55:46	ga_s2bm_ard_3-2-1_50JMP_2019-08-10_final.stac-item
2019-08-10 11:55:49	ga_s2bm_ard_3-2-1_50JLP_2019-08-10_final.stac-item
2019-08-10 11:55:53	ga_s2bm_ard_3-2-1_50JKP_2019-08-10_final.stac-item
2019-08-10 11:56:06	ga_s2bm_ard_3-2-1_50JKN_2019-08-10_final.stac-item
2019-08-18 09:34:43	ga_s2bm_ard_3-2-1_56JMP_2019-08-18_final.stac-item
2019-08-18 09:34:46	ga_s2bm_ard_3-2-1_56JLP_2019-08-18_final.stac-item
2019-08-18 09:34:50	ga_s2bm_ard_3-2-1_56JKP_2019-08-18_final.stac-item
2019-08-18 09:34:56	ga_s2bm_ard_3-2-1_55JGJ_2019-08-18_final.stac-item
2019-08-18 09:35:04	ga_s2bm_ard_3-2-1_56JKN_2019-08-18_final.stac-item
2019-08-18 09:35:07	ga_s2bm_ard_3-2-1_55JGH_2019-08-18_final.stac-item
2019-10-14 09:24:42	ga_s2bm_ard_3-2-1_56JMP_2019-10-13_final.stac-item
2019-10-17 11:15:13	ga_s2bm_ard_3-2-1_52JDP_2019-10-17_final.stac-item
2019-10-17 11:15:19	ga_s2bm_ard_3-2-1_52JCP_2019-10-17_final.stac-item
2019-10-17 11:15:23	ga_s2bm_ard_3-2-1_52JBP_2019-10-17_final.stac-item
2019-10-17 11:15:26	ga_s2bm_ard_3-2-1_51JYJ_2019-10-17_final.stac-item
2019-10-17 11:15:31	ga_s2bm_ard_3-2-1_51JXJ_2019-10-17_final.stac-item
2019-10-17 11:15:38	ga_s2bm_ard_3-2-1_52JBN_2019-10-17_final.stac-item
2019-10-17 11:15:40	ga_s2bm_ard_3-2-1_51JYH_2019-10-17_final.stac-item
2019-10-17 11:15:44	ga_s2bm_ard_3-2-1_51JXH_2019-10-17_final.stac-item
2019-11-01 12:05:38	ga_s2bm_ard_3-2-1_50JLP_2019-11-01_final.stac-item
2019-11-01 12:05:41	ga_s2bm_ard_3-2-1_50JKP_2019-11-01_final.stac-item
2019-11-01 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2019-11-01_final.stac-item
2019-11-01 12:05:56	ga_s2bm_ard_3-2-1_50JKN_2019-11-01_final.stac-item
2019-11-03 09:24:41	ga_s2bm_ard_3-2-1_56JMP_2019-11-02_final.stac-item
2023-10-03 11:05:13	ga_s2bm_ard_3-2-1_52JFP_2023-10-03_final
2023-10-03 11:05:17	ga_s2bm_ard_3-2-1_52JEP_2023-10-03_final
2023-10-03 11:05:20	ga_s2bm_ard_3-2-1_52JDP_2023-10-03_final
2023-10-03 11:05:23	ga_s2bm_ard_3-2-1_52JCP_2023-10-03_final
2023-10-04 10:34:58	ga_s2bm_ard_3-2-1_54JTP_2023-10-04_final
2023-10-04 10:35:02	ga_s2bm_ard_3-2-1_53JQJ_2023-10-04_final
2023-10-04 10:35:06	ga_s2bm_ard_3-2-1_53JPJ_2023-10-04_final
2023-10-04 10:35:09	ga_s2bm_ard_3-2-1_54JTN_2023-10-04_final
2023-10-04 10:35:09	ga_s2bm_ard_3-2-1_53JNJ_2023-10-04_final
2023-10-04 10:35:16	ga_s2bm_ard_3-2-1_53JMJ_2023-10-04_final
2023-10-04 10:35:16	ga_s2bm_ard_3-2-1_53JQH_2023-10-04_final
2023-10-04 10:35:20	ga_s2bm_ard_3-2-1_53JPH_2023-10-04_final
2023-10-05 08:24:25	ga_s2bm_ard_3-2-1_59JKH_2023-10-04_final
2023-10-05 08:24:26	ga_s2bm_ard_3-2-1_58JGN_2023-10-04_final
2023-10-05 10:04:48	ga_s2bm_ard_3-2-1_55JCJ_2023-10-05_final
2023-10-05 10:04:51	ga_s2bm_ard_3-2-1_55JBJ_2023-10-05_final
2023-10-05 10:04:54	ga_s2bm_ard_3-2-1_54JYP_2023-10-05_final
2023-10-05 10:04:57	ga_s2bm_ard_3-2-1_54JXP_2023-10-05_final
2023-10-05 10:05:06	ga_s2bm_ard_3-2-1_55JBH_2023-10-05_final
2023-10-05 10:05:09	ga_s2bm_ard_3-2-1_54JYN_2023-10-05_final
2023-10-05 10:05:12	ga_s2bm_ard_3-2-1_54JXN_2023-10-05_final
2023-10-13 11:05:15	ga_s2bm_ard_3-2-1_52JFP_2023-10-13_final
2023-10-13 11:05:18	ga_s2bm_ard_3-2-1_52JEP_2023-10-13_final
2023-10-13 11:05:22	ga_s2bm_ard_3-2-1_52JDP_2023-10-13_final
2023-10-13 11:05:25	ga_s2bm_ard_3-2-1_52JCP_2023-10-13_final
2023-10-15 08:24:27	ga_s2bm_ard_3-2-1_59JKH_2023-10-14_final
2023-10-15 08:24:28	ga_s2bm_ard_3-2-1_58JGN_2023-10-14_final
2023-10-15 10:04:50	ga_s2bm_ard_3-2-1_55JCJ_2023-10-15_final
2023-10-15 10:04:53	ga_s2bm_ard_3-2-1_55JBJ_2023-10-15_final
2023-10-15 10:04:56	ga_s2bm_ard_3-2-1_54JYP_2023-10-15_final
2023-10-15 10:05:00	ga_s2bm_ard_3-2-1_54JXP_2023-10-15_final
2023-10-15 10:05:08	ga_s2bm_ard_3-2-1_55JBH_2023-10-15_final
2023-10-15 10:05:11	ga_s2bm_ard_3-2-1_54JYN_2023-10-15_final
2023-10-15 10:05:14	ga_s2bm_ard_3-2-1_54JXN_2023-10-15_final
2023-11-18 09:44:37	ga_s2bm_ard_3-2-1_56JKP_2023-11-18_final
2023-11-18 09:44:41	ga_s2bm_ard_3-2-1_55JGJ_2023-11-18_final
2023-11-18 09:44:44	ga_s2bm_ard_3-2-1_55JFJ_2023-11-18_final
2023-11-18 09:44:48	ga_s2bm_ard_3-2-1_55JEJ_2023-11-18_final
2023-11-18 09:44:52	ga_s2bm_ard_3-2-1_56JKN_2023-11-18_final
2023-11-18 09:44:55	ga_s2bm_ard_3-2-1_55JGH_2023-11-18_final
2023-11-18 09:44:59	ga_s2bm_ard_3-2-1_55JFH_2023-11-18_final
2024-03-27 11:25:21	ga_s2bm_ard_3-2-1_51JYJ_2024-03-27_final
2024-03-27 11:25:24	ga_s2bm_ard_3-2-1_51JXJ_2024-03-27_final
2024-03-27 11:25:28	ga_s2bm_ard_3-2-1_51JWJ_2024-03-27_final
2024-03-27 11:25:31	ga_s2bm_ard_3-2-1_51JVJ_2024-03-27_final
2024-03-27 11:25:34	ga_s2bm_ard_3-2-1_51JYH_2024-03-27_final
2024-03-27 11:25:39	ga_s2bm_ard_3-2-1_51JXH_2024-03-27_final
2024-03-28 09:14:43	ga_s2bm_ard_3-2-1_56JPP_2024-03-27_nrt
2024-03-28 09:14:54	ga_s2bm_ard_3-2-1_56JPN_2024-03-27_nrt
2024-03-31 11:05:12	ga_s2bm_ard_3-2-1_52JFP_2024-03-31_final
2024-03-31 11:05:15	ga_s2bm_ard_3-2-1_52JEP_2024-03-31_final
2024-03-31 11:05:19	ga_s2bm_ard_3-2-1_52JDP_2024-03-31_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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