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
2019-07-06 11:06:33	ga_s2bm_ard_3-2-1_52HBK_2019-07-06_final.stac-item
2019-07-06 11:06:46	ga_s2bm_ard_3-2-1_51HYD_2019-07-06_final.stac-item
2019-07-08 10:05:58	ga_s2bm_ard_3-2-1_55HBE_2019-07-08_final.stac-item
2019-07-08 10:06:01	ga_s2bm_ard_3-2-1_54HYK_2019-07-08_final.stac-item
2019-07-08 10:06:04	ga_s2bm_ard_3-2-1_54HXK_2019-07-08_final.stac-item
2019-07-08 10:06:08	ga_s2bm_ard_3-2-1_54HWK_2019-07-08_final.stac-item
2019-07-08 10:06:13	ga_s2bm_ard_3-2-1_55HBD_2019-07-08_final.stac-item
2019-07-08 10:06:15	ga_s2bm_ard_3-2-1_54HYJ_2019-07-08_final.stac-item
2019-07-10 10:46:15	ga_s2bm_ard_3-2-1_53HME_2019-07-10_final.stac-item
2019-07-10 10:46:18	ga_s2bm_ard_3-2-1_53HLE_2019-07-10_final.stac-item
2019-07-10 10:46:33	ga_s2bm_ard_3-2-1_53HLD_2019-07-10_final.stac-item
2019-07-11 10:15:59	ga_s2bm_ard_3-2-1_54HXK_2019-07-11_final.stac-item
2019-07-11 10:16:04	ga_s2bm_ard_3-2-1_54HWK_2019-07-11_final.stac-item
2019-07-11 10:16:07	ga_s2bm_ard_3-2-1_54HVK_2019-07-11_final.stac-item
2019-07-11 10:16:11	ga_s2bm_ard_3-2-1_54HUK_2019-07-11_final.stac-item
2019-07-11 10:16:25	ga_s2bm_ard_3-2-1_54HUJ_2019-07-11_final.stac-item
2019-07-11 10:16:29	ga_s2bm_ard_3-2-1_54HTJ_2019-07-11_final.stac-item
2019-07-17 10:36:15	ga_s2bm_ard_3-2-1_53HNE_2019-07-17_final.stac-item
2019-07-17 10:36:19	ga_s2bm_ard_3-2-1_53HME_2019-07-17_final.stac-item
2019-07-17 10:36:25	ga_s2bm_ard_3-2-1_53HLE_2019-07-17_final.stac-item
2019-07-17 10:36:30	ga_s2bm_ard_3-2-1_53HND_2019-07-17_final.stac-item
2019-07-24 10:26:06	ga_s2bm_ard_3-2-1_54HUK_2019-07-24_final.stac-item
2019-07-24 10:26:10	ga_s2bm_ard_3-2-1_54HTK_2019-07-24_final.stac-item
2019-07-24 10:26:12	ga_s2bm_ard_3-2-1_53HQE_2019-07-24_final.stac-item
2019-07-24 10:26:15	ga_s2bm_ard_3-2-1_53HPE_2019-07-24_final.stac-item
2019-07-25 09:55:51	ga_s2bm_ard_3-2-1_55HEE_2019-07-25_final.stac-item
2019-07-25 09:55:55	ga_s2bm_ard_3-2-1_55HDE_2019-07-25_final.stac-item
2019-07-25 09:55:59	ga_s2bm_ard_3-2-1_55HCE_2019-07-25_final.stac-item
2019-07-25 09:56:02	ga_s2bm_ard_3-2-1_55HBE_2019-07-25_final.stac-item
2019-07-25 09:56:05	ga_s2bm_ard_3-2-1_54HYK_2019-07-25_final.stac-item
2019-07-25 09:56:13	ga_s2bm_ard_3-2-1_55HCD_2019-07-25_final.stac-item
2019-07-25 09:56:17	ga_s2bm_ard_3-2-1_55HBD_2019-07-25_final.stac-item
2019-07-25 09:56:18	ga_s2bm_ard_3-2-1_54HYJ_2019-07-25_final.stac-item
2019-07-28 11:46:38	ga_s2bm_ard_3-2-1_50HQK_2019-07-28_final.stac-item
2019-07-28 11:46:42	ga_s2bm_ard_3-2-1_50HPK_2019-07-28_final.stac-item
2019-07-28 11:46:46	ga_s2bm_ard_3-2-1_50HNK_2019-07-28_final.stac-item
2019-07-28 11:46:49	ga_s2bm_ard_3-2-1_50HMK_2019-07-28_final.stac-item
2019-07-28 11:46:50	ga_s2bm_ard_3-2-1_50HQJ_2019-07-28_final.stac-item
2019-07-28 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2019-07-28_final.stac-item
2019-07-28 11:46:55	ga_s2bm_ard_3-2-1_50HNJ_2019-07-28_final.stac-item
2019-07-28 11:46:56	ga_s2bm_ard_3-2-1_50HMK_2019-07-28_final.stac-item
2019-07-31 11:56:44	ga_s2bm_ard_3-2-1_50HMK_2019-07-31_final.stac-item
2019-07-31 11:56:48	ga_s2bm_ard_3-2-1_50HLK_2019-07-31_final.stac-item
2019-07-31 11:57:03	ga_s2bm_ard_3-2-1_50HLJ_2019-07-31_final.stac-item
2019-08-05 11:06:31	ga_s2bm_ard_3-2-1_52HBK_2019-08-05_final.stac-item
2019-08-05 11:06:44	ga_s2bm_ard_3-2-1_51HYD_2019-08-05_final.stac-item
2019-08-06 10:36:10	ga_s2bm_ard_3-2-1_53HPE_2019-08-06_final.stac-item
2019-08-06 10:36:14	ga_s2bm_ard_3-2-1_53HNE_2019-08-06_final.stac-item
2019-08-06 10:36:18	ga_s2bm_ard_3-2-1_53HME_2019-08-06_final.stac-item
2019-08-06 10:36:24	ga_s2bm_ard_3-2-1_53HLE_2019-08-06_final.stac-item
2019-08-06 10:36:25	ga_s2bm_ard_3-2-1_53HPD_2019-08-06_final.stac-item
2019-08-06 10:36:29	ga_s2bm_ard_3-2-1_53HND_2019-08-06_final.stac-item
2019-08-07 10:05:57	ga_s2bm_ard_3-2-1_55HBE_2019-08-07_final.stac-item
2019-08-07 10:05:59	ga_s2bm_ard_3-2-1_54HYK_2019-08-07_final.stac-item
2019-08-07 10:06:03	ga_s2bm_ard_3-2-1_54HXK_2019-08-07_final.stac-item
2019-08-07 10:06:06	ga_s2bm_ard_3-2-1_54HWK_2019-08-07_final.stac-item
2019-08-07 10:06:11	ga_s2bm_ard_3-2-1_55HBD_2019-08-07_final.stac-item
2019-08-07 10:06:13	ga_s2bm_ard_3-2-1_54HYJ_2019-08-07_final.stac-item
2019-08-07 10:06:17	ga_s2bm_ard_3-2-1_54HXJ_2019-08-07_final.stac-item
2019-08-07 10:06:21	ga_s2bm_ard_3-2-1_54HWJ_2019-08-07_final.stac-item
2019-08-10 11:57:02	ga_s2bm_ard_3-2-1_50HLJ_2019-08-10_final.stac-item
2019-08-11 09:45:47	ga_s2bm_ard_3-2-1_55HGE_2019-08-11_final.stac-item
2019-08-11 09:45:51	ga_s2bm_ard_3-2-1_55HFE_2019-08-11_final.stac-item
2019-08-11 09:45:54	ga_s2bm_ard_3-2-1_55HEE_2019-08-11_final.stac-item
2019-08-11 09:45:58	ga_s2bm_ard_3-2-1_55HDE_2019-08-11_final.stac-item
2019-08-11 09:46:01	ga_s2bm_ard_3-2-1_55HGD_2019-08-11_final.stac-item
2019-08-11 09:46:05	ga_s2bm_ard_3-2-1_55HFD_2019-08-11_final.stac-item
2019-08-11 09:46:09	ga_s2bm_ard_3-2-1_55HED_2019-08-11_final.stac-item
2019-08-11 11:26:29	ga_s2bm_ard_3-2-1_51HXE_2019-08-11_final.stac-item
2019-08-11 11:26:33	ga_s2bm_ard_3-2-1_51HWE_2019-08-11_final.stac-item
2019-08-11 11:26:36	ga_s2bm_ard_3-2-1_51HVE_2019-08-11_final.stac-item
2019-08-11 11:26:39	ga_s2bm_ard_3-2-1_51HUE_2019-08-11_final.stac-item
2019-08-11 11:26:43	ga_s2bm_ard_3-2-1_51HXD_2019-08-11_final.stac-item
2019-08-11 11:26:47	ga_s2bm_ard_3-2-1_51HWD_2019-08-11_final.stac-item
2019-08-15 09:25:46	ga_s2bm_ard_3-2-1_56HMK_2019-08-14_final.stac-item
2019-08-15 09:25:49	ga_s2bm_ard_3-2-1_56HLK_2019-08-14_final.stac-item
2019-08-15 09:26:04	ga_s2bm_ard_3-2-1_56HLJ_2019-08-14_final.stac-item
2019-08-15 11:06:30	ga_s2bm_ard_3-2-1_52HBK_2019-08-15_final.stac-item
2019-08-15 11:06:43	ga_s2bm_ard_3-2-1_51HYD_2019-08-15_final.stac-item
2019-08-16 10:36:09	ga_s2bm_ard_3-2-1_53HPE_2019-08-16_final.stac-item
2019-08-16 10:36:13	ga_s2bm_ard_3-2-1_53HNE_2019-08-16_final.stac-item
2019-08-16 10:36:16	ga_s2bm_ard_3-2-1_53HME_2019-08-16_final.stac-item
2019-08-16 10:36:23	ga_s2bm_ard_3-2-1_53HLE_2019-08-16_final.stac-item
2019-08-16 10:36:23	ga_s2bm_ard_3-2-1_53HPD_2019-08-16_final.stac-item
2019-08-16 10:36:27	ga_s2bm_ard_3-2-1_53HND_2019-08-16_final.stac-item
2019-08-17 11:46:47	ga_s2bm_ard_3-2-1_50HMK_2019-08-17_final.stac-item
2019-08-17 11:46:49	ga_s2bm_ard_3-2-1_50HQJ_2019-08-17_final.stac-item
2019-08-17 11:46:54	ga_s2bm_ard_3-2-1_50HPJ_2019-08-17_final.stac-item
2019-08-17 11:46:58	ga_s2bm_ard_3-2-1_50HNJ_2019-08-17_final.stac-item
2019-08-18 09:35:41	ga_s2bm_ard_3-2-1_56HMK_2019-08-18_final.stac-item
2019-08-18 09:35:45	ga_s2bm_ard_3-2-1_56HLK_2019-08-18_final.stac-item
2019-08-18 09:35:48	ga_s2bm_ard_3-2-1_56HKK_2019-08-18_final.stac-item
2019-08-18 09:35:50	ga_s2bm_ard_3-2-1_55HGE_2019-08-18_final.stac-item
2019-08-18 09:35:56	ga_s2bm_ard_3-2-1_55HFE_2019-08-18_final.stac-item
2019-08-18 09:35:59	ga_s2bm_ard_3-2-1_56HLJ_2019-08-18_final.stac-item
2019-08-18 09:36:03	ga_s2bm_ard_3-2-1_56HKJ_2019-08-18_final.stac-item
2019-08-18 09:36:05	ga_s2bm_ard_3-2-1_55HGD_2019-08-18_final.stac-item
2019-08-18 09:36:08	ga_s2bm_ard_3-2-1_55HFD_2019-08-18_final.stac-item
2019-08-20 11:56:42	ga_s2bm_ard_3-2-1_50HMK_2019-08-20_final.stac-item
2019-08-20 11:56:46	ga_s2bm_ard_3-2-1_50HLK_2019-08-20_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