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
2023-11-18 11:27:11	ga_s2bm_ard_3-2-1_51HTB_2023-11-18_final
2023-11-20 10:20:15	ga_s2bm_ard_3-2-1_54LWN_2023-11-20_final
2023-11-20 10:20:33	ga_s2bm_ard_3-2-1_54LZL_2023-11-20_final
2023-11-20 10:21:05	ga_s2bm_ard_3-2-1_54LYJ_2023-11-20_final
2023-11-20 10:21:56	ga_s2bm_ard_3-2-1_54KWF_2023-11-20_final
2023-11-20 10:22:25	ga_s2bm_ard_3-2-1_54KWD_2023-11-20_final
2023-11-20 10:22:35	ga_s2bm_ard_3-2-1_54KXC_2023-11-20_final
2023-11-20 10:23:47	ga_s2bm_ard_3-2-1_54KTU_2023-11-20_final
2023-11-20 10:23:55	ga_s2bm_ard_3-2-1_54JVT_2023-11-20_final
2023-11-20 10:24:10	ga_s2bm_ard_3-2-1_54JVS_2023-11-20_final
2023-11-20 10:24:45	ga_s2bm_ard_3-2-1_54JTQ_2023-11-20_final
2023-11-20 10:25:21	ga_s2bm_ard_3-2-1_54JVM_2023-11-20_final
2023-11-20 10:25:26	ga_s2bm_ard_3-2-1_53JQG_2023-11-20_final
2023-11-20 10:25:30	ga_s2bm_ard_3-2-1_54JUM_2023-11-20_final
2023-11-20 10:25:33	ga_s2bm_ard_3-2-1_54JVL_2023-11-20_final
2023-11-20 10:25:55	ga_s2bm_ard_3-2-1_54HUK_2023-11-20_final
2023-11-20 10:26:04	ga_s2bm_ard_3-2-1_53HPE_2023-11-20_final
2023-11-20 10:26:19	ga_s2bm_ard_3-2-1_53HPD_2023-11-20_final
2023-11-20 12:03:17	ga_s2bm_ard_3-2-1_50KNC_2023-11-20_final
2023-11-20 12:04:10	ga_s2bm_ard_3-2-1_50KKV_2023-11-20_final
2023-11-20 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2023-11-20_final
2023-11-20 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2023-11-20_final
2023-11-20 12:04:58	ga_s2bm_ard_3-2-1_49JGM_2023-11-20_final
2023-11-20 12:06:01	ga_s2bm_ard_3-2-1_50JLM_2023-11-20_final
2023-11-21 09:56:02	ga_s2bm_ard_3-2-1_55HCD_2023-11-21_final
2023-11-21 09:56:06	ga_s2bm_ard_3-2-1_54HYJ_2023-11-21_final
2023-11-21 09:56:21	ga_s2bm_ard_3-2-1_54HYH_2023-11-21_final
2023-11-21 09:56:48	ga_s2bm_ard_3-2-1_55HBA_2023-11-21_final
2023-11-21 09:56:54	ga_s2bm_ard_3-2-1_54HXF_2023-11-21_final
2023-11-21 09:57:08	ga_s2bm_ard_3-2-1_54HXE_2023-11-21_final
2023-11-21 09:57:18	ga_s2bm_ard_3-2-1_55HBU_2023-11-21_final
2023-11-21 09:57:19	ga_s2bm_ard_3-2-1_54HYD_2023-11-21_final
2023-11-21 09:57:32	ga_s2bm_ard_3-2-1_55HBT_2023-11-21_final
2023-11-21 09:57:33	ga_s2bm_ard_3-2-1_54HYC_2023-11-21_final
2023-11-21 09:58:01	ga_s2bm_ard_3-2-1_55GBR_2023-11-21_final
2023-11-21 09:58:16	ga_s2bm_ard_3-2-1_54GYV_2023-11-21_final
2023-11-21 11:31:15	ga_s2bm_ard_3-2-1_52LBK_2023-11-21_final
2023-11-21 11:31:31	ga_s2bm_ard_3-2-1_51LXD_2023-11-21_final
2023-11-21 11:31:39	ga_s2bm_ard_3-2-1_51LXD_2023-11-21_final
2023-11-21 11:31:53	ga_s2bm_ard_3-2-1_51LXC_2023-11-21_final
2023-11-21 11:31:56	ga_s2bm_ard_3-2-1_51KZB_2023-11-21_final
2023-11-21 11:32:04	ga_s2bm_ard_3-2-1_51KYB_2023-11-21_final
2023-11-21 11:32:08	ga_s2bm_ard_3-2-1_51KXB_2023-11-21_final
2023-11-21 11:32:22	ga_s2bm_ard_3-2-1_51KXA_2023-11-21_final
2023-11-21 11:32:40	ga_s2bm_ard_3-2-1_51KWV_2023-11-21_final
2023-11-21 11:32:43	ga_s2bm_ard_3-2-1_51KVV_2023-11-21_final
2023-11-21 11:32:58	ga_s2bm_ard_3-2-1_51KVU_2023-11-21_final
2023-11-21 11:33:19	ga_s2bm_ard_3-2-1_51KUT_2023-11-21_final
2023-11-21 11:33:31	ga_s2bm_ard_3-2-1_51KUS_2023-11-21_final
2023-11-21 11:33:41	ga_s2bm_ard_3-2-1_51KVR_2023-11-21_final
2023-11-21 11:33:49	ga_s2bm_ard_3-2-1_51KXQ_2023-11-21_final
2023-11-21 11:33:56	ga_s2bm_ard_3-2-1_51KVQ_2023-11-21_final
2023-11-21 11:34:02	ga_s2bm_ard_3-2-1_51KXP_2023-11-21_final
2023-11-21 11:34:46	ga_s2bm_ard_3-2-1_50JRS_2023-11-21_final
2023-11-21 11:35:04	ga_s2bm_ard_3-2-1_51JWK_2023-11-21_final
2023-11-21 11:35:16	ga_s2bm_ard_3-2-1_51JWJ_2023-11-21_final
2023-11-21 11:35:30	ga_s2bm_ard_3-2-1_51JTJ_2023-11-21_final
2023-11-21 11:35:41	ga_s2bm_ard_3-2-1_51JUH_2023-11-21_final
2023-11-21 11:35:52	ga_s2bm_ard_3-2-1_51JVG_2023-11-21_final
2023-11-21 11:35:56	ga_s2bm_ard_3-2-1_51JUG_2023-11-21_final
2023-11-21 11:36:02	ga_s2bm_ard_3-2-1_50JQM_2023-11-21_final
2023-11-21 11:36:07	ga_s2bm_ard_3-2-1_51JVF_2023-11-21_final
2023-11-21 11:36:14	ga_s2bm_ard_3-2-1_51JTF_2023-11-21_final
2023-11-21 11:36:16	ga_s2bm_ard_3-2-1_50JQL_2023-11-21_final
2023-11-21 11:36:30	ga_s2bm_ard_3-2-1_51HVD_2023-11-21_final
2023-11-21 11:36:34	ga_s2bm_ard_3-2-1_50HPK_2023-11-21_final
2023-11-21 11:36:45	ga_s2bm_ard_3-2-1_50HQJ_2023-11-21_final
2023-11-21 11:36:48	ga_s2bm_ard_3-2-1_50HPJ_2023-11-21_final
2023-11-21 11:36:57	ga_s2bm_ard_3-2-1_51HTC_2023-11-21_final
2023-11-21 11:37:12	ga_s2bm_ard_3-2-1_51HTB_2023-11-21_final
2023-11-21 11:37:23	ga_s2bm_ard_3-2-1_50HNG_2023-11-21_final
2023-11-22 09:28:38	ga_s2bm_ard_3-2-1_55GEN_2023-11-21_final
2023-11-22 09:28:45	ga_s2bm_ard_3-2-1_55GEN_2023-11-21_final
2023-11-22 09:28:56	ga_s2bm_ard_3-2-1_55GEM_2023-11-21_final
2023-12-01 09:57:52	ga_s2bm_ard_3-2-1_54HXB_2023-12-01_nrt
2023-12-01 09:58:26	ga_s2bm_ard_3-2-1_54GYU_2023-12-01_nrt
2023-12-01 11:30:18	ga_s2bm_ard_3-2-1_52LBP_2023-12-01_nrt
2023-12-01 11:30:20	ga_s2bm_ard_3-2-1_51LZJ_2023-12-01_nrt
2023-12-01 11:30:26	ga_s2bm_ard_3-2-1_51LXJ_2023-12-01_nrt
2023-12-01 11:30:30	ga_s2bm_ard_3-2-1_52LBN_2023-12-01_nrt
2023-12-01 11:30:31	ga_s2bm_ard_3-2-1_51LZH_2023-12-01_nrt
2023-12-01 11:30:33	ga_s2bm_ard_3-2-1_51LXJ_2023-12-01_nrt
2023-12-01 11:30:34	ga_s2bm_ard_3-2-1_51LXH_2023-12-01_nrt
2023-12-01 11:30:36	ga_s2bm_ard_3-2-1_52LBN_2023-12-01_nrt
2023-12-01 11:30:37	ga_s2bm_ard_3-2-1_51LZH_2023-12-01_nrt
2023-12-01 11:30:41	ga_s2bm_ard_3-2-1_51LXH_2023-12-01_nrt
2023-12-01 11:30:47	ga_s2bm_ard_3-2-1_52LBM_2023-12-01_nrt
2023-12-01 11:30:49	ga_s2bm_ard_3-2-1_51LZG_2023-12-01_nrt
2023-12-01 11:30:56	ga_s2bm_ard_3-2-1_51LXG_2023-12-01_nrt
2023-12-01 11:31:02	ga_s2bm_ard_3-2-1_52LBL_2023-12-01_nrt
2023-12-01 11:31:03	ga_s2bm_ard_3-2-1_51LZF_2023-12-01_nrt
2023-12-01 11:31:10	ga_s2bm_ard_3-2-1_51LXF_2023-12-01_nrt
2023-12-01 11:31:25	ga_s2bm_ard_3-2-1_51LXE_2023-12-01_nrt
2023-12-01 11:37:29	ga_s2bm_ard_3-2-1_50HNF_2023-12-01_nrt
2023-12-02 09:27:55	ga_s2bm_ard_3-2-1_55GGR_2023-12-01_nrt
2023-12-02 09:28:09	ga_s2bm_ard_3-2-1_55GGQ_2023-12-01_nrt
2023-12-02 09:28:23	ga_s2bm_ard_3-2-1_55GGP_2023-12-01_nrt
2023-12-02 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2023-12-01_nrt
2023-12-02 09:28:46	ga_s2bm_ard_3-2-1_55GGM_2023-12-01_nrt
2023-12-02 09:28:46	ga_s2bm_ard_3-2-1_55GGN_2023-12-01_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