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
2019-07-28 11:45:08	ga_s2bm_ard_3-2-1_51JTL_2019-07-28_final.stac-item
2019-07-28 11:45:11	ga_s2bm_ard_3-2-1_50JQR_2019-07-28_final.stac-item
2019-07-28 11:45:15	ga_s2bm_ard_3-2-1_50JPR_2019-07-28_final.stac-item
2019-07-28 11:45:19	ga_s2bm_ard_3-2-1_50JNR_2019-07-28_final.stac-item
2019-07-28 11:45:22	ga_s2bm_ard_3-2-1_51JTK_2019-07-28_final.stac-item
2019-07-28 11:45:26	ga_s2bm_ard_3-2-1_50JQQ_2019-07-28_final.stac-item
2019-07-28 11:45:29	ga_s2bm_ard_3-2-1_50JPQ_2019-07-28_final.stac-item
2019-07-29 11:14:54	ga_s2bm_ard_3-2-1_52JDR_2019-07-29_final.stac-item
2019-07-29 11:14:58	ga_s2bm_ard_3-2-1_52JCR_2019-07-29_final.stac-item
2019-07-29 11:15:01	ga_s2bm_ard_3-2-1_52JBR_2019-07-29_final.stac-item
2019-07-29 11:15:04	ga_s2bm_ard_3-2-1_51JYL_2019-07-29_final.stac-item
2019-07-29 11:15:12	ga_s2bm_ard_3-2-1_52JCQ_2019-07-29_final.stac-item
2019-07-29 11:15:15	ga_s2bm_ard_3-2-1_52JBQ_2019-07-29_final.stac-item
2019-07-29 11:15:18	ga_s2bm_ard_3-2-1_51JYK_2019-07-29_final.stac-item
2019-08-03 12:05:16	ga_s2bm_ard_3-2-1_50JLR_2019-08-03_final.stac-item
2019-08-03 12:05:19	ga_s2bm_ard_3-2-1_50JKR_2019-08-03_final.stac-item
2019-08-03 12:05:23	ga_s2bm_ard_3-2-1_49JGL_2019-08-03_final.stac-item
2019-08-03 12:05:30	ga_s2bm_ard_3-2-1_50JLQ_2019-08-03_final.stac-item
2019-08-03 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-08-03_final.stac-item
2019-08-03 12:05:37	ga_s2bm_ard_3-2-1_49JGK_2019-08-03_final.stac-item
2019-08-08 11:14:53	ga_s2bm_ard_3-2-1_52JDR_2019-08-08_final.stac-item
2019-08-08 11:14:57	ga_s2bm_ard_3-2-1_52JCR_2019-08-08_final.stac-item
2019-08-08 11:15:00	ga_s2bm_ard_3-2-1_52JBR_2019-08-08_final.stac-item
2019-08-08 11:15:03	ga_s2bm_ard_3-2-1_51JYL_2019-08-08_final.stac-item
2019-08-08 11:15:11	ga_s2bm_ard_3-2-1_52JCQ_2019-08-08_final.stac-item
2019-08-08 11:15:14	ga_s2bm_ard_3-2-1_52JBQ_2019-08-08_final.stac-item
2019-08-08 11:15:17	ga_s2bm_ard_3-2-1_51JYK_2019-08-08_final.stac-item
2019-08-10 10:14:28	ga_s2bm_ard_3-2-1_54JYR_2019-08-10_final.stac-item
2019-08-10 10:14:31	ga_s2bm_ard_3-2-1_54JXR_2019-08-10_final.stac-item
2019-08-10 10:14:35	ga_s2bm_ard_3-2-1_54JWR_2019-08-10_final.stac-item
2019-08-10 10:14:38	ga_s2bm_ard_3-2-1_54JVR_2019-08-10_final.stac-item
2019-08-10 10:14:42	ga_s2bm_ard_3-2-1_54JYQ_2019-08-10_final.stac-item
2019-08-10 10:14:46	ga_s2bm_ard_3-2-1_54JXQ_2019-08-10_final.stac-item
2019-08-11 09:44:12	ga_s2bm_ard_3-2-1_56JLR_2019-08-11_final.stac-item
2019-08-11 09:44:17	ga_s2bm_ard_3-2-1_56JKR_2019-08-11_final.stac-item
2019-08-11 09:44:20	ga_s2bm_ard_3-2-1_55JGL_2019-08-11_final.stac-item
2019-08-11 09:44:23	ga_s2bm_ard_3-2-1_56JLQ_2019-08-11_final.stac-item
2019-08-11 09:44:24	ga_s2bm_ard_3-2-1_55JFL_2019-08-11_final.stac-item
2019-08-11 09:44:30	ga_s2bm_ard_3-2-1_56JKQ_2019-08-11_final.stac-item
2019-08-11 09:44:32	ga_s2bm_ard_3-2-1_55JEL_2019-08-11_final.stac-item
2019-08-11 09:44:32	ga_s2bm_ard_3-2-1_55JGK_2019-08-11_final.stac-item
2019-08-11 09:44:34	ga_s2bm_ard_3-2-1_55JFK_2019-08-11_final.stac-item
2019-08-13 12:05:15	ga_s2bm_ard_3-2-1_50JLR_2019-08-13_final.stac-item
2019-08-13 12:05:18	ga_s2bm_ard_3-2-1_50JKR_2019-08-13_final.stac-item
2019-08-13 12:05:21	ga_s2bm_ard_3-2-1_49JGL_2019-08-13_final.stac-item
2019-08-13 12:05:29	ga_s2bm_ard_3-2-1_50JLQ_2019-08-13_final.stac-item
2019-08-13 12:05:33	ga_s2bm_ard_3-2-1_50JKQ_2019-08-13_final.stac-item
2019-08-13 12:05:36	ga_s2bm_ard_3-2-1_49JGK_2019-08-13_final.stac-item
2019-08-19 10:44:41	ga_s2bm_ard_3-2-1_53JNL_2019-08-19_final.stac-item
2019-08-19 10:44:45	ga_s2bm_ard_3-2-1_53JML_2019-08-19_final.stac-item
2019-08-19 10:44:48	ga_s2bm_ard_3-2-1_53JLL_2019-08-19_final.stac-item
2019-08-19 10:44:54	ga_s2bm_ard_3-2-1_53JKL_2019-08-19_final.stac-item
2019-08-19 10:45:02	ga_s2bm_ard_3-2-1_53JLK_2019-08-19_final.stac-item
2019-08-19 10:45:06	ga_s2bm_ard_3-2-1_53JKK_2019-08-19_final.stac-item
2019-08-24 09:54:18	ga_s2bm_ard_3-2-1_55JFL_2019-08-24_final.stac-item
2019-08-24 09:54:21	ga_s2bm_ard_3-2-1_55JEL_2019-08-24_final.stac-item
2019-08-24 09:54:25	ga_s2bm_ard_3-2-1_55JDL_2019-08-24_final.stac-item
2019-08-24 09:54:28	ga_s2bm_ard_3-2-1_55JCL_2019-08-24_final.stac-item
2019-08-27 10:04:18	ga_s2bm_ard_3-2-1_55JDL_2019-08-27_final.stac-item
2019-08-27 10:04:23	ga_s2bm_ard_3-2-1_55JCL_2019-08-27_final.stac-item
2019-08-27 10:04:26	ga_s2bm_ard_3-2-1_55JBL_2019-08-27_final.stac-item
2019-08-27 10:04:30	ga_s2bm_ard_3-2-1_54JYR_2019-08-27_final.stac-item
2019-08-27 10:04:37	ga_s2bm_ard_3-2-1_54JXR_2019-08-27_final.stac-item
2019-08-27 10:04:37	ga_s2bm_ard_3-2-1_55JCK_2019-08-27_final.stac-item
2019-08-27 10:04:41	ga_s2bm_ard_3-2-1_55JBK_2019-08-27_final.stac-item
2019-08-27 10:04:44	ga_s2bm_ard_3-2-1_54JYQ_2019-08-27_final.stac-item
2019-08-27 10:04:48	ga_s2bm_ard_3-2-1_54JXQ_2019-08-27_final.stac-item
2019-08-30 10:14:25	ga_s2bm_ard_3-2-1_54JYR_2019-08-30_final.stac-item
2019-08-30 10:14:28	ga_s2bm_ard_3-2-1_54JXR_2019-08-30_final.stac-item
2019-08-30 10:14:32	ga_s2bm_ard_3-2-1_54JWR_2019-08-30_final.stac-item
2019-08-30 10:14:35	ga_s2bm_ard_3-2-1_54JVR_2019-08-30_final.stac-item
2019-08-30 10:14:39	ga_s2bm_ard_3-2-1_54JYQ_2019-08-30_final.stac-item
2019-08-30 10:14:43	ga_s2bm_ard_3-2-1_54JXQ_2019-08-30_final.stac-item
2019-09-05 10:34:32	ga_s2bm_ard_3-2-1_54JTR_2019-09-05_final.stac-item
2019-09-05 10:34:35	ga_s2bm_ard_3-2-1_53JQL_2019-09-05_final.stac-item
2019-09-05 10:34:39	ga_s2bm_ard_3-2-1_53JPL_2019-09-05_final.stac-item
2019-09-05 10:34:42	ga_s2bm_ard_3-2-1_53JNL_2019-09-05_final.stac-item
2019-09-05 10:34:46	ga_s2bm_ard_3-2-1_54JTQ_2019-09-05_final.stac-item
2019-09-05 10:34:49	ga_s2bm_ard_3-2-1_53JQK_2019-09-05_final.stac-item
2019-09-05 10:34:53	ga_s2bm_ard_3-2-1_53JPK_2019-09-05_final.stac-item
2019-09-07 09:34:16	ga_s2bm_ard_3-2-1_56JKR_2019-09-07_final.stac-item
2019-09-07 09:34:31	ga_s2bm_ard_3-2-1_56JKQ_2019-09-07_final.stac-item
2019-09-11 10:54:39	ga_s2bm_ard_3-2-1_53JLL_2019-09-11_final.stac-item
2019-09-11 10:54:42	ga_s2bm_ard_3-2-1_53JKL_2019-09-11_final.stac-item
2019-09-11 10:54:45	ga_s2bm_ard_3-2-1_52JGR_2019-09-11_final.stac-item
2019-09-11 10:54:48	ga_s2bm_ard_3-2-1_52JFR_2019-09-11_final.stac-item
2019-09-11 10:54:53	ga_s2bm_ard_3-2-1_53JLK_2019-09-11_final.stac-item
2019-09-11 10:54:57	ga_s2bm_ard_3-2-1_53JKK_2019-09-11_final.stac-item
2019-09-11 10:55:00	ga_s2bm_ard_3-2-1_52JGQ_2019-09-11_final.stac-item
2019-09-11 10:55:03	ga_s2bm_ard_3-2-1_52JFQ_2019-09-11_final.stac-item
2019-09-15 12:15:10	ga_s2bm_ard_3-2-1_49JGL_2019-09-15_final.stac-item
2019-09-15 12:15:20	ga_s2bm_ard_3-2-1_49JGK_2019-09-15_final.stac-item
2019-09-16 10:04:19	ga_s2bm_ard_3-2-1_55JDL_2019-09-16_final.stac-item
2019-09-16 10:04:21	ga_s2bm_ard_3-2-1_55JCL_2019-09-16_final.stac-item
2019-09-16 10:04:23	ga_s2bm_ard_3-2-1_55JBL_2019-09-16_final.stac-item
2019-09-16 10:04:25	ga_s2bm_ard_3-2-1_54JYR_2019-09-16_final.stac-item
2019-09-16 10:04:32	ga_s2bm_ard_3-2-1_54JXR_2019-09-16_final.stac-item
2019-09-16 10:04:33	ga_s2bm_ard_3-2-1_55JCK_2019-09-16_final.stac-item
2019-09-16 10:04:36	ga_s2bm_ard_3-2-1_55JBK_2019-09-16_final.stac-item
2019-09-16 10:04:39	ga_s2bm_ard_3-2-1_54JYQ_2019-09-16_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