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
2019-02-12 11:26:22	ga_s2bm_ard_3-2-1_51HXE_2019-02-12_final.stac-item
2019-02-12 11:26:26	ga_s2bm_ard_3-2-1_51HWE_2019-02-12_final.stac-item
2019-02-12 11:26:29	ga_s2bm_ard_3-2-1_51HVE_2019-02-12_final.stac-item
2019-02-12 11:26:32	ga_s2bm_ard_3-2-1_51HUE_2019-02-12_final.stac-item
2019-02-18 11:46:29	ga_s2bm_ard_3-2-1_50HQK_2019-02-18_final.stac-item
2019-02-18 11:46:33	ga_s2bm_ard_3-2-1_50HPK_2019-02-18_final.stac-item
2019-02-18 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2019-02-18_final.stac-item
2019-02-18 11:46:40	ga_s2bm_ard_3-2-1_50HPK_2019-02-18_final.stac-item
2019-02-18 11:46:42	ga_s2bm_ard_3-2-1_50HNK_2019-02-18_final.stac-item
2019-02-18 11:46:44	ga_s2bm_ard_3-2-1_50HMK_2019-02-18_final.stac-item
2019-02-21 10:15:58	ga_s2bm_ard_3-2-1_54HVK_2019-02-21_final.stac-item
2019-02-21 10:16:01	ga_s2bm_ard_3-2-1_54HUK_2019-02-21_final.stac-item
2019-04-27 11:06:31	ga_s2bm_ard_3-2-1_52HBK_2019-04-27_final.stac-item
2019-04-27 11:06:44	ga_s2bm_ard_3-2-1_51HYD_2019-04-27_final.stac-item
2019-04-28 10:36:10	ga_s2bm_ard_3-2-1_53HPE_2019-04-28_final.stac-item
2019-04-28 10:36:14	ga_s2bm_ard_3-2-1_53HNE_2019-04-28_final.stac-item
2019-04-28 10:36:17	ga_s2bm_ard_3-2-1_53HME_2019-04-28_final.stac-item
2019-04-28 10:36:24	ga_s2bm_ard_3-2-1_53HLE_2019-04-28_final.stac-item
2019-05-02 10:15:57	ga_s2bm_ard_3-2-1_54HXK_2019-05-02_final.stac-item
2019-05-02 10:16:03	ga_s2bm_ard_3-2-1_54HWK_2019-05-02_final.stac-item
2019-05-02 10:16:06	ga_s2bm_ard_3-2-1_54HVK_2019-05-02_final.stac-item
2019-05-02 10:16:10	ga_s2bm_ard_3-2-1_54HUK_2019-05-02_final.stac-item
2019-05-03 09:45:48	ga_s2bm_ard_3-2-1_55HGE_2019-05-03_final.stac-item
2019-05-03 09:45:52	ga_s2bm_ard_3-2-1_55HFE_2019-05-03_final.stac-item
2019-05-03 09:45:55	ga_s2bm_ard_3-2-1_55HEE_2019-05-03_final.stac-item
2019-05-03 09:45:59	ga_s2bm_ard_3-2-1_55HDE_2019-05-03_final.stac-item
2019-05-03 09:46:02	ga_s2bm_ard_3-2-1_55HGD_2019-05-03_final.stac-item
2019-05-03 11:26:33	ga_s2bm_ard_3-2-1_51HWE_2019-05-03_final.stac-item
2019-05-03 11:26:37	ga_s2bm_ard_3-2-1_51HVE_2019-05-03_final.stac-item
2019-05-03 11:26:40	ga_s2bm_ard_3-2-1_51HUE_2019-05-03_final.stac-item
2019-05-11 10:46:14	ga_s2bm_ard_3-2-1_53HME_2019-05-11_final.stac-item
2019-05-11 10:46:18	ga_s2bm_ard_3-2-1_53HLE_2019-05-11_final.stac-item
2019-05-12 10:15:58	ga_s2bm_ard_3-2-1_54HXK_2019-05-12_final.stac-item
2019-05-12 10:16:03	ga_s2bm_ard_3-2-1_54HWK_2019-05-12_final.stac-item
2019-05-12 10:16:07	ga_s2bm_ard_3-2-1_54HVK_2019-05-12_final.stac-item
2019-05-12 10:16:10	ga_s2bm_ard_3-2-1_54HUK_2019-05-12_final.stac-item
2019-05-15 10:26:06	ga_s2bm_ard_3-2-1_54HUK_2019-05-15_final.stac-item
2019-05-15 10:26:10	ga_s2bm_ard_3-2-1_54HTK_2019-05-15_final.stac-item
2019-05-15 10:26:12	ga_s2bm_ard_3-2-1_53HQE_2019-05-15_final.stac-item
2019-05-15 10:26:15	ga_s2bm_ard_3-2-1_53HPE_2019-05-15_final.stac-item
2019-05-17 09:25:48	ga_s2bm_ard_3-2-1_56HMK_2019-05-16_final.stac-item
2019-05-17 09:25:51	ga_s2bm_ard_3-2-1_56HLK_2019-05-16_final.stac-item
2019-05-19 10:05:58	ga_s2bm_ard_3-2-1_55HBE_2019-05-19_final.stac-item
2019-05-19 10:06:00	ga_s2bm_ard_3-2-1_54HYK_2019-05-19_final.stac-item
2019-05-19 10:06:04	ga_s2bm_ard_3-2-1_54HXK_2019-05-19_final.stac-item
2019-05-19 10:06:08	ga_s2bm_ard_3-2-1_54HWK_2019-05-19_final.stac-item
2019-05-19 10:06:13	ga_s2bm_ard_3-2-1_55HBD_2019-05-19_final.stac-item
2019-05-19 10:06:15	ga_s2bm_ard_3-2-1_54HYJ_2019-05-19_final.stac-item
2019-05-20 09:35:44	ga_s2bm_ard_3-2-1_56HMK_2019-05-20_final.stac-item
2019-05-20 09:35:47	ga_s2bm_ard_3-2-1_56HLK_2019-05-20_final.stac-item
2019-05-20 09:35:51	ga_s2bm_ard_3-2-1_56HKK_2019-05-20_final.stac-item
2019-05-20 09:35:53	ga_s2bm_ard_3-2-1_55HGE_2019-05-20_final.stac-item
2019-05-20 09:35:59	ga_s2bm_ard_3-2-1_55HFE_2019-05-20_final.stac-item
2019-05-20 09:36:05	ga_s2bm_ard_3-2-1_56HKJ_2019-05-20_final.stac-item
2019-05-20 09:36:07	ga_s2bm_ard_3-2-1_55HGD_2019-05-20_final.stac-item
2019-05-25 10:26:06	ga_s2bm_ard_3-2-1_54HUK_2019-05-25_final.stac-item
2019-05-25 10:26:10	ga_s2bm_ard_3-2-1_54HTK_2019-05-25_final.stac-item
2019-05-25 10:26:12	ga_s2bm_ard_3-2-1_53HQE_2019-05-25_final.stac-item
2019-05-25 10:26:15	ga_s2bm_ard_3-2-1_53HPE_2019-05-25_final.stac-item
2019-05-25 10:26:24	ga_s2bm_ard_3-2-1_54HTJ_2019-05-25_final.stac-item
2019-05-25 10:26:26	ga_s2bm_ard_3-2-1_53HQD_2019-05-25_final.stac-item
2023-12-11 11:36:20	ga_s2bm_ard_3-2-1_51HVE_2023-12-11_final
2023-12-11 11:36:25	ga_s2bm_ard_3-2-1_51HUE_2023-12-11_final
2023-12-11 11:36:28	ga_s2bm_ard_3-2-1_51HTE_2023-12-11_final
2023-12-11 11:36:31	ga_s2bm_ard_3-2-1_50HQK_2023-12-11_final
2023-12-12 11:06:11	ga_s2bm_ard_3-2-1_52HEK_2023-12-12_nrt
2023-12-12 11:06:13	ga_s2bm_ard_3-2-1_52HDK_2023-12-12_final
2023-12-12 11:06:18	ga_s2bm_ard_3-2-1_52HEK_2023-12-12_nrt
2023-12-12 11:06:20	ga_s2bm_ard_3-2-1_52HDK_2023-12-12_final
2023-12-12 11:06:21	ga_s2bm_ard_3-2-1_52HCK_2023-12-12_final
2023-12-12 11:06:23	ga_s2bm_ard_3-2-1_52HBK_2023-12-12_final
2023-12-12 11:06:30	ga_s2bm_ard_3-2-1_52HBJ_2023-12-12_nrt
2023-12-14 10:05:47	ga_s2bm_ard_3-2-1_55HBE_2023-12-14_final
2023-12-14 10:05:50	ga_s2bm_ard_3-2-1_54HYK_2023-12-14_final
2023-12-14 10:05:54	ga_s2bm_ard_3-2-1_54HXK_2023-12-14_final
2023-12-14 10:05:57	ga_s2bm_ard_3-2-1_54HWK_2023-12-14_final
2023-12-14 10:06:02	ga_s2bm_ard_3-2-1_55HBD_2023-12-14_final
2023-12-14 10:06:04	ga_s2bm_ard_3-2-1_54HYJ_2023-12-14_final
2023-12-15 11:16:15	ga_s2bm_ard_3-2-1_52HCK_2023-12-15_final
2023-12-15 11:16:19	ga_s2bm_ard_3-2-1_52HBK_2023-12-15_final
2023-12-15 11:16:21	ga_s2bm_ard_3-2-1_51HYE_2023-12-15_final
2023-12-15 11:16:25	ga_s2bm_ard_3-2-1_51HXE_2023-12-15_final
2023-12-15 11:16:29	ga_s2bm_ard_3-2-1_51HWE_2023-12-15_final
2023-12-15 11:16:33	ga_s2bm_ard_3-2-1_52HBJ_2023-12-15_nrt
2023-12-15 11:16:35	ga_s2bm_ard_3-2-1_51HYD_2023-12-15_final
2023-12-16 10:46:05	ga_s2bm_ard_3-2-1_53HME_2023-12-16_final
2023-12-16 10:46:08	ga_s2bm_ard_3-2-1_53HLE_2023-12-16_final
2023-12-16 10:46:12	ga_s2bm_ard_3-2-1_53HKE_2023-12-16_final
2023-12-16 10:46:14	ga_s2bm_ard_3-2-1_52HGK_2023-12-16_final
2023-12-16 10:46:25	ga_s2bm_ard_3-2-1_53HKD_2023-12-16_nrt
2023-12-16 10:46:26	ga_s2bm_ard_3-2-1_52HGJ_2023-12-16_nrt
2023-12-17 11:56:36	ga_s2bm_ard_3-2-1_50HMK_2023-12-17_final
2023-12-17 11:56:40	ga_s2bm_ard_3-2-1_50HLK_2023-12-17_final
2023-12-17 11:56:43	ga_s2bm_ard_3-2-1_50HKK_2023-12-17_nrt
2023-12-17 11:56:45	ga_s2bm_ard_3-2-1_49HGE_2023-12-17_nrt
2023-12-17 11:56:57	ga_s2bm_ard_3-2-1_50HKJ_2023-12-17_nrt
2023-12-17 11:56:59	ga_s2bm_ard_3-2-1_49HGD_2023-12-17_nrt
2023-12-19 10:56:15	ga_s2bm_ard_3-2-1_52HFK_2023-12-19_nrt
2023-12-19 10:56:18	ga_s2bm_ard_3-2-1_52HEK_2023-12-19_nrt
2023-12-19 10:56:20	ga_s2bm_ard_3-2-1_53HKD_2023-12-19_nrt

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