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
2018-01-07 11:50:37	ga_s2bm_ard_3-2-1_50JLL_2018-01-07_final.stac-item
2018-01-07 11:56:02	ga_s2bm_ard_3-2-1_50HLJ_2018-01-07_final.stac-item
2018-01-14 11:46:06	ga_s2bm_ard_3-2-1_50HPJ_2018-01-14_final.stac-item
2018-01-17 11:49:12	ga_s2bm_ard_3-2-1_50HMK_2018-01-17_final.stac-item
2018-01-17 11:49:12	ga_s2bm_ard_3-2-1_50HMH_2018-01-17_final.stac-item
2018-01-17 11:49:12	ga_s2bm_ard_3-2-1_50HMJ_2018-01-17_final.stac-item
2018-01-24 11:37:42	ga_s2bm_ard_3-2-1_50HMK_2018-01-24_final.stac-item
2018-01-24 11:37:42	ga_s2bm_ard_3-2-1_50HMJ_2018-01-24_final.stac-item
2018-01-27 11:56:04	ga_s2bm_ard_3-2-1_50HMK_2018-01-27_final.stac-item
2018-01-27 11:56:04	ga_s2bm_ard_3-2-1_50HLJ_2018-01-27_final.stac-item
2018-01-27 11:56:04	ga_s2bm_ard_3-2-1_50JMM_2018-01-27_final.stac-item
2018-01-31 11:27:22	ga_s2bm_ard_3-2-1_50HPJ_2018-01-31_final.stac-item
2018-01-31 11:27:22	ga_s2bm_ard_3-2-1_50HPK_2018-01-31_final.stac-item
2018-01-31 11:27:22	ga_s2bm_ard_3-2-1_50HQH_2018-01-31_final.stac-item
2019-08-04 11:31:46	ga_s2bm_ard_3-2-1_51LYD_2019-08-04_final.stac-item
2019-08-17 11:47:23	ga_s2bm_ard_3-2-1_50HMH_2019-08-17_final.stac-item
2019-10-02 12:04:24	ga_s2bm_ard_3-2-1_49KHP_2019-10-02_final.stac-item
2019-10-03 11:32:58	ga_s2bm_ard_3-2-1_51KWU_2019-10-03_final.stac-item
2019-10-03 11:32:59	ga_s2bm_ard_3-2-1_51KVU_2019-10-03_final.stac-item
2019-10-03 11:33:03	ga_s2bm_ard_3-2-1_51KWT_2019-10-03_final.stac-item
2019-10-04 11:05:53	ga_s2bm_ard_3-2-1_52JCM_2019-10-04_final.stac-item
2019-10-05 12:13:55	ga_s2bm_ard_3-2-1_50KKA_2019-10-05_final.stac-item
2019-10-05 12:13:59	ga_s2bm_ard_3-2-1_49KGR_2019-10-05_final.stac-item
2019-10-06 11:41:59	ga_s2bm_ard_3-2-1_51LVC_2019-10-06_final.stac-item
2019-10-06 11:42:14	ga_s2bm_ard_3-2-1_51KVB_2019-10-06_final.stac-item
2019-10-07 11:16:21	ga_s2bm_ard_3-2-1_52HBK_2019-10-07_final.stac-item
2019-10-13 11:32:21	ga_s2bm_ard_3-2-1_51KVB_2019-10-13_final.stac-item
2019-10-13 11:32:48	ga_s2bm_ard_3-2-1_51KVV_2019-10-13_final.stac-item
2019-10-13 11:33:03	ga_s2bm_ard_3-2-1_51KVU_2019-10-13_final.stac-item
2019-10-14 11:05:50	ga_s2bm_ard_3-2-1_52JCM_2019-10-14_final.stac-item
2019-10-14 11:06:25	ga_s2bm_ard_3-2-1_52HBK_2019-10-14_final.stac-item
2019-10-15 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2019-10-15_final.stac-item
2019-10-15 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2019-10-15_final.stac-item
2019-10-16 11:42:58	ga_s2bm_ard_3-2-1_51KVU_2019-10-16_final.stac-item
2019-10-17 11:15:49	ga_s2bm_ard_3-2-1_52JCM_2019-10-17_final.stac-item
2019-10-17 11:16:21	ga_s2bm_ard_3-2-1_52HBK_2019-10-17_final.stac-item
2019-10-19 11:53:00	ga_s2bm_ard_3-2-1_50KRD_2019-10-19_final.stac-item
2019-10-23 11:33:02	ga_s2bm_ard_3-2-1_51KVU_2019-10-23_final.stac-item
2019-10-24 11:06:04	ga_s2bm_ard_3-2-1_52JDL_2019-10-24_final.stac-item
2019-10-24 11:06:07	ga_s2bm_ard_3-2-1_52JCL_2019-10-24_final.stac-item
2019-10-25 12:14:14	ga_s2bm_ard_3-2-1_49KGQ_2019-10-25_final.stac-item
2019-10-25 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2019-10-25_final.stac-item
2019-10-26 11:42:00	ga_s2bm_ard_3-2-1_51LVC_2019-10-26_final.stac-item
2019-10-26 11:42:14	ga_s2bm_ard_3-2-1_51KVB_2019-10-26_final.stac-item
2019-10-26 11:43:05	ga_s2bm_ard_3-2-1_50KRD_2019-10-26_final.stac-item
2019-10-27 11:15:54	ga_s2bm_ard_3-2-1_52JCL_2019-10-27_final.stac-item
2019-10-27 11:16:03	ga_s2bm_ard_3-2-1_52JCL_2019-10-27_final.stac-item
2019-10-27 11:16:38	ga_s2bm_ard_3-2-1_51HYD_2019-10-27_final.stac-item
2019-11-02 11:35:08	ga_s2bm_ard_3-2-1_51JWK_2019-11-02_final.stac-item
2019-11-02 11:36:29	ga_s2bm_ard_3-2-1_51HUE_2019-11-02_final.stac-item
2019-11-05 11:44:45	ga_s2bm_ard_3-2-1_51JTM_2019-11-05_final.stac-item
2019-11-06 11:15:48	ga_s2bm_ard_3-2-1_52JCM_2019-11-06_final.stac-item
2019-11-09 11:24:26	ga_s2bm_ard_3-2-1_51JXN_2019-11-09_final.stac-item
2019-11-09 11:24:55	ga_s2bm_ard_3-2-1_51JXL_2019-11-09_final.stac-item
2019-11-09 11:25:27	ga_s2bm_ard_3-2-1_51JWJ_2019-11-09_final.stac-item
2019-11-12 11:35:29	ga_s2bm_ard_3-2-1_51JUJ_2019-11-12_final.stac-item
2019-11-12 11:35:40	ga_s2bm_ard_3-2-1_51JVH_2019-11-12_final.stac-item
2019-11-13 11:06:23	ga_s2bm_ard_3-2-1_52HBK_2019-11-13_final.stac-item
2019-11-15 11:44:58	ga_s2bm_ard_3-2-1_51JTL_2019-11-15_final.stac-item
2019-11-16 11:16:18	ga_s2bm_ard_3-2-1_52HBK_2019-11-16_final.stac-item
2019-11-19 11:24:53	ga_s2bm_ard_3-2-1_51JXL_2019-11-19_final.stac-item
2019-11-19 11:25:26	ga_s2bm_ard_3-2-1_51JWJ_2019-11-19_final.stac-item
2019-11-21 12:04:22	ga_s2bm_ard_3-2-1_50KLU_2019-11-21_final.stac-item
2019-11-23 11:05:49	ga_s2bm_ard_3-2-1_52JCM_2019-11-23_final.stac-item
2019-11-23 11:06:21	ga_s2bm_ard_3-2-1_52HBK_2019-11-23_final.stac-item
2019-11-29 11:22:48	ga_s2bm_ard_3-2-1_51KZU_2019-11-29_final.stac-item
2019-11-29 11:25:09	ga_s2bm_ard_3-2-1_51JWK_2019-11-29_final.stac-item
2019-11-29 11:25:41	ga_s2bm_ard_3-2-1_51JVH_2019-11-29_final.stac-item
2019-12-01 12:04:26	ga_s2bm_ard_3-2-1_49KGP_2019-12-01_final.stac-item
2019-12-01 12:05:36	ga_s2bm_ard_3-2-1_50JKP_2019-12-01_final.stac-item
2019-12-02 11:34:56	ga_s2bm_ard_3-2-1_51JTL_2019-12-02_final.stac-item
2019-12-02 11:35:25	ga_s2bm_ard_3-2-1_51JUJ_2019-12-02_final.stac-item
2019-12-02 11:36:23	ga_s2bm_ard_3-2-1_51HUE_2019-12-02_final.stac-item
2019-12-04 12:13:48	ga_s2bm_ard_3-2-1_50KKA_2019-12-04_final.stac-item
2019-12-04 12:14:39	ga_s2bm_ard_3-2-1_49JFN_2019-12-04_final.stac-item
2019-12-06 11:14:29	ga_s2bm_ard_3-2-1_52JCS_2019-12-06_final.stac-item
2019-12-06 11:14:49	ga_s2bm_ard_3-2-1_51JYL_2019-12-06_final.stac-item
2019-12-06 11:15:16	ga_s2bm_ard_3-2-1_52JBP_2019-12-06_final.stac-item
2019-12-06 11:15:30	ga_s2bm_ard_3-2-1_52JBN_2019-12-06_final.stac-item
2019-12-09 11:24:35	ga_s2bm_ard_3-2-1_51JXM_2019-12-09_final.stac-item
2019-12-09 11:25:00	ga_s2bm_ard_3-2-1_51JYK_2019-12-09_final.stac-item
2019-12-09 11:25:07	ga_s2bm_ard_3-2-1_51JWK_2019-12-09_final.stac-item
2019-12-09 11:25:40	ga_s2bm_ard_3-2-1_51JVH_2019-12-09_final.stac-item
2019-12-12 11:35:25	ga_s2bm_ard_3-2-1_51JUJ_2019-12-12_final.stac-item
2019-12-12 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2019-12-12_final.stac-item
2019-12-16 11:15:05	ga_s2bm_ard_3-2-1_51JYK_2019-12-16_final.stac-item
2019-12-18 11:56:31	ga_s2bm_ard_3-2-1_50HMK_2019-12-18_final.stac-item
2019-12-19 11:24:35	ga_s2bm_ard_3-2-1_51JXM_2019-12-19_final.stac-item
2019-12-19 11:25:01	ga_s2bm_ard_3-2-1_51JYK_2019-12-19_final.stac-item
2019-12-21 12:04:23	ga_s2bm_ard_3-2-1_49KHP_2019-12-21_final.stac-item
2019-12-21 12:04:52	ga_s2bm_ard_3-2-1_50JKS_2019-12-21_final.stac-item
2019-12-22 11:33:08	ga_s2bm_ard_3-2-1_51KWT_2019-12-22_final.stac-item
2019-12-22 11:34:56	ga_s2bm_ard_3-2-1_51JUL_2019-12-22_final.stac-item
2019-12-22 11:35:10	ga_s2bm_ard_3-2-1_51JUK_2019-12-22_final.stac-item
2019-12-22 11:35:21	ga_s2bm_ard_3-2-1_51JVJ_2019-12-22_final.stac-item
2019-12-25 11:46:50	ga_s2bm_ard_3-2-1_50HMJ_2019-12-25_final.stac-item
2019-12-26 11:15:05	ga_s2bm_ard_3-2-1_51JYK_2019-12-26_final.stac-item
2019-12-26 11:15:17	ga_s2bm_ard_3-2-1_52JBP_2019-12-26_final.stac-item
2019-12-28 11:56:50	ga_s2bm_ard_3-2-1_50HLJ_2019-12-28_final.stac-item
2019-12-29 11:25:01	ga_s2bm_ard_3-2-1_51JYK_2019-12-29_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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