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
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_54LYJ_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_54LYK_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_55LBD_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_55LBE_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_54LZJ_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_54LZK_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_55LCD_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_55LCE_2017-12-18_final.stac-item
2018-11-27 11:31:14	ga_s2bm_ard_3-2-1_52LBK_2018-11-27_final.stac-item
2018-11-27 11:31:17	ga_s2bm_ard_3-2-1_51LZE_2018-11-27_final.stac-item
2018-11-27 11:31:20	ga_s2bm_ard_3-2-1_51LYE_2018-11-27_final.stac-item
2018-11-27 11:31:25	ga_s2bm_ard_3-2-1_52LBJ_2018-11-27_final.stac-item
2018-11-27 11:31:27	ga_s2bm_ard_3-2-1_51LWE_2018-11-27_final.stac-item
2018-11-27 11:31:31	ga_s2bm_ard_3-2-1_51LZD_2018-11-27_final.stac-item
2018-11-27 11:31:35	ga_s2bm_ard_3-2-1_51LYD_2018-11-27_final.stac-item
2018-11-27 11:31:38	ga_s2bm_ard_3-2-1_51LXD_2018-11-27_final.stac-item
2018-11-30 11:41:22	ga_s2bm_ard_3-2-1_51LWE_2018-11-30_final.stac-item
2018-11-30 11:41:25	ga_s2bm_ard_3-2-1_51LVE_2018-11-30_final.stac-item
2018-11-30 11:41:28	ga_s2bm_ard_3-2-1_51LUE_2018-11-30_final.stac-item
2018-12-06 10:20:44	ga_s2bm_ard_3-2-1_54LZK_2018-12-06_final.stac-item
2018-12-06 10:20:48	ga_s2bm_ard_3-2-1_54LYK_2018-12-06_final.stac-item
2018-12-06 10:20:52	ga_s2bm_ard_3-2-1_54LXK_2018-12-06_final.stac-item
2018-12-06 10:20:55	ga_s2bm_ard_3-2-1_54LWK_2018-12-06_final.stac-item
2018-12-06 10:20:55	ga_s2bm_ard_3-2-1_54LZJ_2018-12-06_final.stac-item
2018-12-06 10:21:02	ga_s2bm_ard_3-2-1_54LYJ_2018-12-06_final.stac-item
2018-12-06 10:21:06	ga_s2bm_ard_3-2-1_54LXJ_2018-12-06_final.stac-item
2018-12-12 10:41:02	ga_s2bm_ard_3-2-1_53LPE_2018-12-12_final.stac-item
2018-12-12 10:41:13	ga_s2bm_ard_3-2-1_53LQD_2018-12-12_final.stac-item
2018-12-12 10:41:17	ga_s2bm_ard_3-2-1_53LPD_2018-12-12_final
2018-12-13 11:51:20	ga_s2bm_ard_3-2-1_51LUE_2018-12-13_final.stac-item
2018-12-16 10:20:43	ga_s2bm_ard_3-2-1_54LZK_2018-12-16_final.stac-item
2018-12-16 10:20:48	ga_s2bm_ard_3-2-1_54LYK_2018-12-16_final.stac-item
2018-12-16 10:20:51	ga_s2bm_ard_3-2-1_54LXK_2018-12-16_final.stac-item
2018-12-16 10:20:54	ga_s2bm_ard_3-2-1_54LWK_2018-12-16_final.stac-item
2018-12-16 10:20:55	ga_s2bm_ard_3-2-1_54LZJ_2018-12-16_final.stac-item
2018-12-16 10:21:02	ga_s2bm_ard_3-2-1_54LYJ_2018-12-16_final.stac-item
2018-12-16 10:21:06	ga_s2bm_ard_3-2-1_54LXJ_2018-12-16_final.stac-item
2019-03-03 10:10:48	ga_s2bm_ard_3-2-1_55LCE_2019-03-03_final.stac-item
2019-03-03 10:10:51	ga_s2bm_ard_3-2-1_55LBE_2019-03-03_final.stac-item
2019-03-03 10:10:53	ga_s2bm_ard_3-2-1_54LZK_2019-03-03_final.stac-item
2019-03-03 10:10:58	ga_s2bm_ard_3-2-1_54LYK_2019-03-03_final.stac-item
2019-03-03 10:11:03	ga_s2bm_ard_3-2-1_55LCD_2019-03-03_final.stac-item
2019-03-03 10:11:06	ga_s2bm_ard_3-2-1_55LBD_2019-03-03_final.stac-item
2019-03-03 10:11:07	ga_s2bm_ard_3-2-1_54LZJ_2019-03-03_final.stac-item
2019-03-03 10:11:11	ga_s2bm_ard_3-2-1_54LYJ_2019-03-03_final.stac-item
2019-03-18 11:01:30	ga_s2bm_ard_3-2-1_52LGJ_2019-03-18_final.stac-item
2019-04-29 11:41:33	ga_s2bm_ard_3-2-1_51LWE_2019-04-29_final.stac-item
2019-04-29 11:41:37	ga_s2bm_ard_3-2-1_51LVE_2019-04-29_final.stac-item
2019-04-29 11:41:40	ga_s2bm_ard_3-2-1_51LUE_2019-04-29_final.stac-item
2019-04-30 11:11:20	ga_s2bm_ard_3-2-1_52LGK_2019-04-30_final.stac-item
2019-04-30 11:11:23	ga_s2bm_ard_3-2-1_52LFK_2019-04-30_final.stac-item
2019-04-30 11:11:34	ga_s2bm_ard_3-2-1_52LGJ_2019-04-30_final.stac-item
2019-04-30 11:11:38	ga_s2bm_ard_3-2-1_52LFJ_2019-04-30_final.stac-item
2019-05-02 11:51:35	ga_s2bm_ard_3-2-1_51LUE_2019-05-02_final.stac-item
2019-05-15 10:20:58	ga_s2bm_ard_3-2-1_54LZK_2019-05-15_final.stac-item
2019-05-15 10:21:02	ga_s2bm_ard_3-2-1_54LYK_2019-05-15_final.stac-item
2019-05-15 10:21:05	ga_s2bm_ard_3-2-1_54LXK_2019-05-15_final.stac-item
2019-05-15 10:21:09	ga_s2bm_ard_3-2-1_54LWK_2019-05-15_final.stac-item
2019-05-15 10:21:09	ga_s2bm_ard_3-2-1_54LZJ_2019-05-15_final.stac-item
2019-05-15 10:21:16	ga_s2bm_ard_3-2-1_54LYJ_2019-05-15_final.stac-item
2019-05-15 10:21:20	ga_s2bm_ard_3-2-1_54LXJ_2019-05-15_final.stac-item
2019-05-20 11:11:21	ga_s2bm_ard_3-2-1_52LGK_2019-05-20_final.stac-item
2019-05-20 11:11:24	ga_s2bm_ard_3-2-1_52LFK_2019-05-20_final.stac-item
2019-05-20 11:11:35	ga_s2bm_ard_3-2-1_52LGJ_2019-05-20_final.stac-item
2019-05-20 11:11:39	ga_s2bm_ard_3-2-1_52LFJ_2019-05-20_final.stac-item
2019-05-22 11:51:36	ga_s2bm_ard_3-2-1_51LUE_2019-05-22_final.stac-item
2019-05-25 10:20:58	ga_s2bm_ard_3-2-1_54LZK_2019-05-25_final.stac-item
2019-05-25 10:21:02	ga_s2bm_ard_3-2-1_54LYK_2019-05-25_final.stac-item
2019-05-25 10:21:05	ga_s2bm_ard_3-2-1_54LXK_2019-05-25_final.stac-item
2019-05-25 10:21:09	ga_s2bm_ard_3-2-1_54LWK_2019-05-25_final.stac-item
2019-05-25 10:21:09	ga_s2bm_ard_3-2-1_54LZJ_2019-05-25_final.stac-item
2019-05-25 10:21:16	ga_s2bm_ard_3-2-1_54LYJ_2019-05-25_final.stac-item
2019-05-25 10:21:20	ga_s2bm_ard_3-2-1_54LXJ_2019-05-25_final.stac-item
2019-05-27 11:01:17	ga_s2bm_ard_3-2-1_53LLE_2019-05-27_final.stac-item
2019-05-27 11:01:21	ga_s2bm_ard_3-2-1_53LKE_2019-05-27_final.stac-item
2019-05-27 11:01:22	ga_s2bm_ard_3-2-1_52LHK_2019-05-27_final.stac-item
2019-05-27 11:01:26	ga_s2bm_ard_3-2-1_52LGK_2019-05-27_final.stac-item
2019-05-27 11:01:32	ga_s2bm_ard_3-2-1_53LLD_2019-05-27_final.stac-item
2019-05-27 11:01:35	ga_s2bm_ard_3-2-1_53LKD_2019-05-27_final.stac-item
2019-05-27 11:01:37	ga_s2bm_ard_3-2-1_52LHJ_2019-05-27_final.stac-item
2019-05-27 11:01:40	ga_s2bm_ard_3-2-1_52LGJ_2019-05-27_final.stac-item
2019-05-28 10:31:04	ga_s2bm_ard_3-2-1_54LWK_2019-05-28_final.stac-item
2019-05-29 11:41:34	ga_s2bm_ard_3-2-1_51LWE_2019-05-29_final.stac-item
2019-05-29 11:41:38	ga_s2bm_ard_3-2-1_51LVE_2019-05-29_final.stac-item
2019-05-29 11:41:41	ga_s2bm_ard_3-2-1_51LUE_2019-05-29_final.stac-item
2019-05-30 11:11:21	ga_s2bm_ard_3-2-1_52LGK_2019-05-30_final.stac-item
2019-05-30 11:11:24	ga_s2bm_ard_3-2-1_52LFK_2019-05-30_final.stac-item
2019-05-30 11:11:35	ga_s2bm_ard_3-2-1_52LGJ_2019-05-30_final.stac-item
2019-05-30 11:11:39	ga_s2bm_ard_3-2-1_52LFJ_2019-05-30_final.stac-item
2019-08-01 11:21:32	ga_s2bm_ard_3-2-1_52LBK_2019-08-01_final.stac-item
2019-08-01 11:21:33	ga_s2bm_ard_3-2-1_51LZE_2019-08-01_final.stac-item
2019-08-01 11:21:43	ga_s2bm_ard_3-2-1_52LCJ_2019-08-01_final.stac-item
2019-08-01 11:21:46	ga_s2bm_ard_3-2-1_52LBJ_2019-08-01_final.stac-item
2019-08-01 11:21:48	ga_s2bm_ard_3-2-1_51LZD_2019-08-01_final.stac-item
2019-08-10 11:51:34	ga_s2bm_ard_3-2-1_51LUE_2019-08-10_final.stac-item
2019-08-18 11:11:18	ga_s2bm_ard_3-2-1_52LGK_2019-08-18_final.stac-item
2019-08-18 11:11:22	ga_s2bm_ard_3-2-1_52LFK_2019-08-18_final.stac-item
2019-08-18 11:11:33	ga_s2bm_ard_3-2-1_52LGJ_2019-08-18_final.stac-item
2019-08-18 11:11:36	ga_s2bm_ard_3-2-1_52LFJ_2019-08-18_final.stac-item
2020-02-26 11:51:24	ga_s2bm_ard_3-2-1_51LUE_2020-02-26_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

All years