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
2019-07-04 12:05:05	ga_s2bm_ard_3-2-1_49JHM_2019-07-04_final.stac-item
2019-07-04 12:05:09	ga_s2bm_ard_3-2-1_49JGM_2019-07-04_final.stac-item
2019-07-04 12:05:17	ga_s2bm_ard_3-2-1_49JFM_2019-07-04_final.stac-item
2019-07-07 12:15:05	ga_s2bm_ard_3-2-1_49JGM_2019-07-07_final.stac-item
2019-07-07 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-07-07_final.stac-item
2019-07-14 12:05:05	ga_s2bm_ard_3-2-1_49JHM_2019-07-14_final.stac-item
2019-07-14 12:05:09	ga_s2bm_ard_3-2-1_49JGM_2019-07-14_final.stac-item
2019-07-14 12:05:17	ga_s2bm_ard_3-2-1_49JFM_2019-07-14_final.stac-item
2019-07-17 12:15:05	ga_s2bm_ard_3-2-1_49JGM_2019-07-17_final.stac-item
2019-07-17 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-07-17_final.stac-item
2019-07-24 12:05:05	ga_s2bm_ard_3-2-1_49JHM_2019-07-24_final.stac-item
2019-07-24 12:05:09	ga_s2bm_ard_3-2-1_49JGM_2019-07-24_final.stac-item
2019-07-24 12:05:17	ga_s2bm_ard_3-2-1_49JFM_2019-07-24_final.stac-item
2019-07-27 12:15:04	ga_s2bm_ard_3-2-1_49JGM_2019-07-27_final.stac-item
2019-07-27 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-07-27_final.stac-item
2019-08-03 12:05:04	ga_s2bm_ard_3-2-1_49JHM_2019-08-03_final.stac-item
2019-08-03 12:05:08	ga_s2bm_ard_3-2-1_49JGM_2019-08-03_final.stac-item
2019-08-03 12:05:16	ga_s2bm_ard_3-2-1_49JFM_2019-08-03_final.stac-item
2019-08-04 11:36:56	ga_s2bm_ard_3-2-1_50HQJ_2019-08-04_final.stac-item
2019-08-06 12:15:03	ga_s2bm_ard_3-2-1_49JGM_2019-08-06_final.stac-item
2019-08-06 12:15:07	ga_s2bm_ard_3-2-1_49JFM_2019-08-06_final.stac-item
2019-08-07 11:47:14	ga_s2bm_ard_3-2-1_50HNH_2019-08-07_final.stac-item
2019-08-13 12:05:03	ga_s2bm_ard_3-2-1_49JHM_2019-08-13_final.stac-item
2019-08-13 12:05:07	ga_s2bm_ard_3-2-1_49JGM_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
2019-08-16 12:15:02	ga_s2bm_ard_3-2-1_49JGM_2019-08-16_final.stac-item
2019-08-16 12:15:06	ga_s2bm_ard_3-2-1_49JFM_2019-08-16_final.stac-item
2019-08-17 11:46:43	ga_s2bm_ard_3-2-1_50HNK_2019-08-17_final.stac-item
2019-08-20 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2019-08-20_final.stac-item
2019-08-23 12:05:02	ga_s2bm_ard_3-2-1_49JHM_2019-08-23_final.stac-item
2019-08-23 12:05:06	ga_s2bm_ard_3-2-1_49JGM_2019-08-23_final.stac-item
2019-08-26 12:15:01	ga_s2bm_ard_3-2-1_49JGM_2019-08-26_final.stac-item
2019-08-26 12:15:04	ga_s2bm_ard_3-2-1_49JFM_2019-08-26_final.stac-item
2019-08-27 11:47:14	ga_s2bm_ard_3-2-1_50HMH_2019-08-27_final.stac-item
2019-08-30 11:56:44	ga_s2bm_ard_3-2-1_50HLK_2019-08-30_final.stac-item
2019-09-02 12:03:53	ga_s2bm_ard_3-2-1_49KHR_2019-09-02_final.stac-item
2019-09-02 12:04:02	ga_s2bm_ard_3-2-1_49KHR_2019-09-02_final.stac-item
2019-09-02 12:04:46	ga_s2bm_ard_3-2-1_49JHN_2019-09-02_final.stac-item
2019-09-02 12:04:49	ga_s2bm_ard_3-2-1_49JGN_2019-09-02_final.stac-item
2019-09-03 11:36:51	ga_s2bm_ard_3-2-1_50HQJ_2019-09-03_final.stac-item
2019-09-05 12:14:01	ga_s2bm_ard_3-2-1_49KGR_2019-09-05_final.stac-item
2019-09-05 12:14:09	ga_s2bm_ard_3-2-1_49KGQ_2019-09-05_final.stac-item
2019-09-05 12:14:09	ga_s2bm_ard_3-2-1_49KGR_2019-09-05_final.stac-item
2019-09-05 12:14:16	ga_s2bm_ard_3-2-1_49KGQ_2019-09-05_final.stac-item
2019-09-05 12:14:24	ga_s2bm_ard_3-2-1_49KHP_2019-09-05_final.stac-item
2019-09-05 12:14:34	ga_s2bm_ard_3-2-1_49JHN_2019-09-05_final.stac-item
2019-09-05 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2019-09-05_final.stac-item
2019-09-05 12:14:48	ga_s2bm_ard_3-2-1_49JFN_2019-09-05_final.stac-item
2019-09-06 11:46:40	ga_s2bm_ard_3-2-1_50HNK_2019-09-06_final.stac-item
2019-09-06 11:46:45	ga_s2bm_ard_3-2-1_50HQJ_2019-09-06_final.stac-item
2019-09-06 11:46:54	ga_s2bm_ard_3-2-1_50HNJ_2019-09-06_final.stac-item
2019-09-06 11:47:09	ga_s2bm_ard_3-2-1_50HNH_2019-09-06_final.stac-item
2019-09-06 11:47:17	ga_s2bm_ard_3-2-1_50HLH_2019-09-06_final.stac-item
2019-09-09 11:56:32	ga_s2bm_ard_3-2-1_50HNK_2019-09-09_final.stac-item
2019-09-09 11:56:42	ga_s2bm_ard_3-2-1_50HLK_2019-09-09_final.stac-item
2019-09-09 11:56:56	ga_s2bm_ard_3-2-1_50HLJ_2019-09-09_final.stac-item
2019-09-09 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2019-09-09_final.stac-item
2019-09-09 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2019-09-09_final.stac-item
2019-09-12 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2019-09-12_final.stac-item
2019-09-12 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2019-09-12_final.stac-item
2019-09-12 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2019-09-12_final.stac-item
2019-09-13 11:36:49	ga_s2bm_ard_3-2-1_50HQJ_2019-09-13_final.stac-item
2019-09-15 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2019-09-15_final.stac-item
2019-09-15 12:13:58	ga_s2bm_ard_3-2-1_49KGR_2019-09-15_final.stac-item
2019-09-15 12:14:06	ga_s2bm_ard_3-2-1_49KGQ_2019-09-15_final.stac-item
2019-09-15 12:14:06	ga_s2bm_ard_3-2-1_49KGR_2019-09-15_final.stac-item
2019-09-15 12:14:13	ga_s2bm_ard_3-2-1_49KGQ_2019-09-15_final.stac-item
2019-09-15 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2019-09-15_final.stac-item
2019-09-15 12:14:31	ga_s2bm_ard_3-2-1_49JHN_2019-09-15_final.stac-item
2019-09-15 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2019-09-15_final.stac-item
2019-09-15 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2019-09-15_final.stac-item
2019-09-16 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2019-09-16_final.stac-item
2019-09-16 11:46:43	ga_s2bm_ard_3-2-1_50HQJ_2019-09-16_final.stac-item
2019-09-16 11:46:51	ga_s2bm_ard_3-2-1_50HNJ_2019-09-16_final.stac-item
2019-09-16 11:47:06	ga_s2bm_ard_3-2-1_50HNH_2019-09-16_final.stac-item
2019-09-16 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2019-09-16_final.stac-item
2019-09-16 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2019-09-16_final.stac-item
2019-09-19 11:56:29	ga_s2bm_ard_3-2-1_50HNK_2019-09-19_final.stac-item
2019-09-19 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2019-09-19_final.stac-item
2019-09-19 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2019-09-19_final.stac-item
2019-09-19 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2019-09-19_final.stac-item
2019-09-22 12:03:59	ga_s2bm_ard_3-2-1_49KHR_2019-09-22_final.stac-item
2019-09-22 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2019-09-22_final.stac-item
2019-09-22 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2019-09-22_final.stac-item
2019-09-22 12:04:45	ga_s2bm_ard_3-2-1_49JGN_2019-09-22_final.stac-item
2019-09-23 11:36:48	ga_s2bm_ard_3-2-1_50HQJ_2019-09-23_final.stac-item
2019-09-25 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2019-09-25_final.stac-item
2019-09-25 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2019-09-25_final.stac-item
2019-09-25 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2019-09-25_final.stac-item
2019-09-25 12:14:31	ga_s2bm_ard_3-2-1_49JHN_2019-09-25_final.stac-item
2019-09-26 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2019-09-26_final.stac-item
2019-09-26 11:46:43	ga_s2bm_ard_3-2-1_50HQJ_2019-09-26_final.stac-item
2019-09-26 11:46:52	ga_s2bm_ard_3-2-1_50HNJ_2019-09-26_final.stac-item
2019-09-26 11:47:06	ga_s2bm_ard_3-2-1_50HNH_2019-09-26_final.stac-item
2019-09-26 11:47:10	ga_s2bm_ard_3-2-1_50HMH_2019-09-26_final.stac-item
2019-09-26 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2019-09-26_final.stac-item
2019-09-29 11:56:30	ga_s2bm_ard_3-2-1_50HNK_2019-09-29_final.stac-item
2019-09-29 11:56:40	ga_s2bm_ard_3-2-1_50HLK_2019-09-29_final.stac-item
2019-09-29 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2019-09-29_final.stac-item
2019-09-29 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2019-09-29_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

All years