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
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_51HTC_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_51HTD_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_51HUD_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_50HPH_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_50HPJ_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_50HQH_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_50HQJ_2018-05-11_final.stac-item
2018-05-24 10:05:08	ga_s2bm_ard_3-2-1_54HWJ_2018-05-24_final.stac-item
2018-05-24 10:05:08	ga_s2bm_ard_3-2-1_55HBC_2018-05-24_final.stac-item
2018-05-24 10:05:08	ga_s2bm_ard_3-2-1_55HBD_2018-05-24_final.stac-item
2018-05-24 10:05:08	ga_s2bm_ard_3-2-1_54HXH_2018-05-24_final.stac-item
2018-05-24 10:05:08	ga_s2bm_ard_3-2-1_54HXJ_2018-05-24_final.stac-item
2018-05-24 10:05:08	ga_s2bm_ard_3-2-1_54HYH_2018-05-24_final.stac-item
2018-05-24 10:05:08	ga_s2bm_ard_3-2-1_54HYJ_2018-05-24_final.stac-item
2019-06-30 10:46:29	ga_s2bm_ard_3-2-1_53HMD_2019-06-30_final.stac-item
2019-06-30 10:46:32	ga_s2bm_ard_3-2-1_53HLD_2019-06-30_final.stac-item
2019-07-01 10:16:18	ga_s2bm_ard_3-2-1_54HWJ_2019-07-01_final.stac-item
2019-07-01 10:16:22	ga_s2bm_ard_3-2-1_54HVJ_2019-07-01_final.stac-item
2019-07-01 10:16:25	ga_s2bm_ard_3-2-1_54HUJ_2019-07-01_final.stac-item
2019-07-01 10:16:29	ga_s2bm_ard_3-2-1_54HTJ_2019-07-01_final.stac-item
2019-07-12 11:26:45	ga_s2bm_ard_3-2-1_51HXD_2019-07-12_final.stac-item
2019-07-12 11:26:49	ga_s2bm_ard_3-2-1_51HWD_2019-07-12_final.stac-item
2019-07-12 11:26:52	ga_s2bm_ard_3-2-1_51HVD_2019-07-12_final.stac-item
2019-07-12 11:26:56	ga_s2bm_ard_3-2-1_51HUD_2019-07-12_final.stac-item
2019-07-18 10:06:13	ga_s2bm_ard_3-2-1_55HBD_2019-07-18_final.stac-item
2019-07-18 10:06:15	ga_s2bm_ard_3-2-1_54HYJ_2019-07-18_final.stac-item
2019-07-18 10:06:19	ga_s2bm_ard_3-2-1_54HXJ_2019-07-18_final.stac-item
2019-07-18 10:06:22	ga_s2bm_ard_3-2-1_54HWJ_2019-07-18_final.stac-item
2019-07-18 10:06:27	ga_s2bm_ard_3-2-1_55HBC_2019-07-18_final.stac-item
2019-07-18 10:06:29	ga_s2bm_ard_3-2-1_54HYH_2019-07-18_final.stac-item
2019-07-18 10:06:33	ga_s2bm_ard_3-2-1_54HXH_2019-07-18_final.stac-item
2019-09-20 09:45:54	ga_s2bm_ard_3-2-1_55HGD_2019-09-20_final.stac-item
2019-09-20 09:45:58	ga_s2bm_ard_3-2-1_55HFD_2019-09-20_final.stac-item
2019-09-20 09:46:01	ga_s2bm_ard_3-2-1_55HED_2019-09-20_final.stac-item
2019-09-20 09:46:05	ga_s2bm_ard_3-2-1_55HDD_2019-09-20_final.stac-item
2019-09-20 09:46:06	ga_s2bm_ard_3-2-1_55HGC_2019-09-20_final.stac-item
2019-09-20 09:46:12	ga_s2bm_ard_3-2-1_55HFC_2019-09-20_final.stac-item
2019-09-23 11:36:42	ga_s2bm_ard_3-2-1_51HUD_2019-09-23_final.stac-item
2019-09-23 11:36:46	ga_s2bm_ard_3-2-1_51HTD_2019-09-23_final.stac-item
2019-09-23 11:36:48	ga_s2bm_ard_3-2-1_50HQJ_2019-09-23_final.stac-item
2019-09-23 11:36:51	ga_s2bm_ard_3-2-1_50HPJ_2019-09-23_final.stac-item
2019-09-23 11:37:00	ga_s2bm_ard_3-2-1_51HTC_2019-09-23_final.stac-item
2019-09-23 11:37:02	ga_s2bm_ard_3-2-1_50HQH_2019-09-23_final.stac-item
2019-09-23 11:37:06	ga_s2bm_ard_3-2-1_50HPH_2019-09-23_final.stac-item
2019-09-24 09:25:54	ga_s2bm_ard_3-2-1_56HMJ_2019-09-23_final.stac-item
2019-09-24 09:25:57	ga_s2bm_ard_3-2-1_56HLJ_2019-09-23_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 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_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 11:46:53	ga_s2bm_ard_3-2-1_50HQH_2019-09-26_final.stac-item
2019-09-26 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2019-09-26_final.stac-item
2019-09-26 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2019-09-26_final.stac-item
2019-10-02 10:26:13	ga_s2bm_ard_3-2-1_54HUJ_2019-10-02_final.stac-item
2019-10-02 10:26:16	ga_s2bm_ard_3-2-1_54HTJ_2019-10-02_final.stac-item
2019-10-02 10:26:18	ga_s2bm_ard_3-2-1_53HQD_2019-10-02_final.stac-item
2019-10-02 10:26:22	ga_s2bm_ard_3-2-1_53HPD_2019-10-02_final.stac-item
2019-10-02 10:26:31	ga_s2bm_ard_3-2-1_54HTH_2019-10-02_final.stac-item
2019-10-02 10:26:33	ga_s2bm_ard_3-2-1_53HQC_2019-10-02_final.stac-item
2019-10-02 10:26:36	ga_s2bm_ard_3-2-1_53HPC_2019-10-02_final.stac-item
2019-12-04 10:36:11	ga_s2bm_ard_3-2-1_53HPD_2019-12-04_final.stac-item
2019-12-04 10:36:15	ga_s2bm_ard_3-2-1_53HND_2019-12-04_final.stac-item
2019-12-04 10:36:19	ga_s2bm_ard_3-2-1_53HMD_2019-12-04_final.stac-item
2019-12-04 10:36:22	ga_s2bm_ard_3-2-1_53HLD_2019-12-04_final.stac-item
2019-12-09 11:26:30	ga_s2bm_ard_3-2-1_51HXD_2019-12-09_final.stac-item
2019-12-09 11:26:34	ga_s2bm_ard_3-2-1_51HWD_2019-12-09_final.stac-item
2019-12-09 11:26:38	ga_s2bm_ard_3-2-1_51HVD_2019-12-09_final.stac-item
2019-12-09 11:26:41	ga_s2bm_ard_3-2-1_51HUD_2019-12-09_final.stac-item
2019-12-11 10:26:07	ga_s2bm_ard_3-2-1_54HUJ_2019-12-11_final.stac-item
2019-12-11 10:26:10	ga_s2bm_ard_3-2-1_54HTJ_2019-12-11_final.stac-item
2019-12-11 10:26:12	ga_s2bm_ard_3-2-1_53HQD_2019-12-11_final.stac-item
2019-12-11 10:26:16	ga_s2bm_ard_3-2-1_53HPD_2019-12-11_final.stac-item
2019-12-11 10:26:25	ga_s2bm_ard_3-2-1_54HTH_2019-12-11_final.stac-item
2019-12-11 10:26:26	ga_s2bm_ard_3-2-1_53HQC_2019-12-11_final.stac-item
2019-12-11 10:26:30	ga_s2bm_ard_3-2-1_53HPC_2019-12-11_final.stac-item
2019-12-15 10:05:58	ga_s2bm_ard_3-2-1_55HBD_2019-12-15_final.stac-item
2019-12-15 10:06:00	ga_s2bm_ard_3-2-1_54HYJ_2019-12-15_final.stac-item
2019-12-15 10:06:05	ga_s2bm_ard_3-2-1_55HBC_2019-12-15_final.stac-item
2019-12-15 10:06:05	ga_s2bm_ard_3-2-1_55HBD_2019-12-15_final.stac-item
2019-12-15 10:06:05	ga_s2bm_ard_3-2-1_54HYH_2019-12-15_final.stac-item
2019-12-15 10:06:06	ga_s2bm_ard_3-2-1_54HYJ_2019-12-15_final.stac-item
2019-12-15 10:06:08	ga_s2bm_ard_3-2-1_54HXJ_2019-12-15_final.stac-item
2019-12-15 10:06:10	ga_s2bm_ard_3-2-1_54HWJ_2019-12-15_final.stac-item
2019-12-15 10:06:13	ga_s2bm_ard_3-2-1_55HBC_2019-12-15_final.stac-item
2019-12-15 10:06:15	ga_s2bm_ard_3-2-1_54HYH_2019-12-15_final.stac-item
2019-12-15 10:06:19	ga_s2bm_ard_3-2-1_54HXH_2019-12-15_final.stac-item
2019-12-16 11:16:31	ga_s2bm_ard_3-2-1_51HYD_2019-12-16_final.stac-item
2019-12-16 11:16:35	ga_s2bm_ard_3-2-1_51HXD_2019-12-16_final.stac-item
2019-12-16 11:16:39	ga_s2bm_ard_3-2-1_51HWD_2019-12-16_final.stac-item
2019-12-22 09:55:56	ga_s2bm_ard_3-2-1_55HDD_2019-12-22_final.stac-item
2019-12-22 09:56:00	ga_s2bm_ard_3-2-1_55HCD_2019-12-22_final.stac-item
2019-12-22 09:56:03	ga_s2bm_ard_3-2-1_55HBD_2019-12-22_final.stac-item
2019-12-22 09:56:05	ga_s2bm_ard_3-2-1_54HYJ_2019-12-22_final.stac-item
2019-12-22 09:56:18	ga_s2bm_ard_3-2-1_55HBC_2019-12-22_final.stac-item
2019-12-22 09:56:20	ga_s2bm_ard_3-2-1_54HYH_2019-12-22_final.stac-item
2019-12-25 10:05:59	ga_s2bm_ard_3-2-1_55HBD_2019-12-25_final.stac-item
2019-12-25 10:06:08	ga_s2bm_ard_3-2-1_55HBD_2019-12-25_final.stac-item
2019-12-25 10:06:08	ga_s2bm_ard_3-2-1_55HBC_2019-12-25_final.stac-item
2019-12-25 10:06:09	ga_s2bm_ard_3-2-1_54HXH_2019-12-25_final.stac-item
2019-12-25 10:06:12	ga_s2bm_ard_3-2-1_54HWJ_2019-12-25_final.stac-item
2019-12-25 10:06:14	ga_s2bm_ard_3-2-1_55HBC_2019-12-25_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