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
2023-05-04 10:20:01	ga_s2bm_ard_3-2-1_54LXP_2023-05-04_final
2023-05-04 10:20:23	ga_s2bm_ard_3-2-1_54LZM_2023-05-04_final
2023-05-04 10:20:38	ga_s2bm_ard_3-2-1_54LZL_2023-05-04_final
2023-05-04 10:20:42	ga_s2bm_ard_3-2-1_54LYL_2023-05-04_final
2023-05-04 10:21:32	ga_s2bm_ard_3-2-1_54LWH_2023-05-04_final
2023-05-04 10:21:54	ga_s2bm_ard_3-2-1_54KYF_2023-05-04_final
2023-05-04 10:22:04	ga_s2bm_ard_3-2-1_54KVF_2023-05-04_final
2023-05-04 10:22:26	ga_s2bm_ard_3-2-1_54KUE_2023-05-04_final
2023-05-04 10:22:41	ga_s2bm_ard_3-2-1_54KXC_2023-05-04_final
2023-05-04 10:22:55	ga_s2bm_ard_3-2-1_54KXB_2023-05-04_final
2023-05-04 10:23:35	ga_s2bm_ard_3-2-1_54KUV_2023-05-04_final
2023-05-04 10:23:42	ga_s2bm_ard_3-2-1_53KRQ_2023-05-04_final
2023-05-04 10:24:01	ga_s2bm_ard_3-2-1_54JVT_2023-05-04_final
2023-05-04 10:24:04	ga_s2bm_ard_3-2-1_54JUT_2023-05-04_final
2023-05-04 10:24:07	ga_s2bm_ard_3-2-1_54JTT_2023-05-04_final
2023-05-04 10:24:23	ga_s2bm_ard_3-2-1_54JUR_2023-05-04_final
2023-05-04 10:24:33	ga_s2bm_ard_3-2-1_54JUR_2023-05-04_final
2023-05-04 10:24:42	ga_s2bm_ard_3-2-1_53JQL_2023-05-04_final
2023-05-04 10:25:37	ga_s2bm_ard_3-2-1_53JQG_2023-05-04_final
2023-05-04 10:25:45	ga_s2bm_ard_3-2-1_54JUL_2023-05-04_final
2023-05-04 10:25:49	ga_s2bm_ard_3-2-1_54JTL_2023-05-04_final
2023-05-04 10:25:51	ga_s2bm_ard_3-2-1_53JQF_2023-05-04_final
2023-05-04 10:26:15	ga_s2bm_ard_3-2-1_54HUJ_2023-05-04_final
2023-05-04 10:26:29	ga_s2bm_ard_3-2-1_54HUH_2023-05-04_final
2023-05-04 10:26:38	ga_s2bm_ard_3-2-1_53HPC_2023-05-04_final
2023-05-04 10:26:49	ga_s2bm_ard_3-2-1_53HQB_2023-05-04_final
2023-05-04 10:26:53	ga_s2bm_ard_3-2-1_53HPB_2023-05-04_final
2023-05-04 12:03:47	ga_s2bm_ard_3-2-1_50KKB_2023-05-04_final
2023-05-04 12:04:09	ga_s2bm_ard_3-2-1_50KMV_2023-05-04_final
2023-05-04 12:04:29	ga_s2bm_ard_3-2-1_49KHP_2023-05-04_final
2023-05-04 12:04:33	ga_s2bm_ard_3-2-1_50JMT_2023-05-04_final
2023-05-04 12:04:35	ga_s2bm_ard_3-2-1_50KLU_2023-05-04_final
2023-05-04 12:04:36	ga_s2bm_ard_3-2-1_49KHP_2023-05-04_final
2023-05-04 12:04:39	ga_s2bm_ard_3-2-1_50JMT_2023-05-04_final
2023-05-04 12:04:42	ga_s2bm_ard_3-2-1_50JLT_2023-05-04_final
2023-05-04 12:04:45	ga_s2bm_ard_3-2-1_49JHN_2023-05-04_final
2023-05-04 12:04:56	ga_s2bm_ard_3-2-1_50JLS_2023-05-04_final
2023-05-04 12:05:00	ga_s2bm_ard_3-2-1_50JKS_2023-05-04_final
2023-05-04 12:05:03	ga_s2bm_ard_3-2-1_49JGM_2023-05-04_final
2023-05-04 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2023-05-04_final
2023-05-04 12:05:11	ga_s2bm_ard_3-2-1_49JFM_2023-05-04_final
2023-05-04 12:05:14	ga_s2bm_ard_3-2-1_50JKR_2023-05-04_final
2023-05-04 12:05:32	ga_s2bm_ard_3-2-1_49JGK_2023-05-04_final
2023-05-05 09:52:48	ga_s2bm_ard_3-2-1_55KFS_2023-05-05_final
2023-05-05 09:52:52	ga_s2bm_ard_3-2-1_55KES_2023-05-05_final
2023-05-05 09:53:06	ga_s2bm_ard_3-2-1_55KER_2023-05-05_final
2023-05-05 09:53:10	ga_s2bm_ard_3-2-1_55KDR_2023-05-05_final
2023-05-05 09:54:05	ga_s2bm_ard_3-2-1_55JEM_2023-05-05_final
2023-05-05 09:54:08	ga_s2bm_ard_3-2-1_55JDM_2023-05-05_final
2023-05-05 09:54:19	ga_s2bm_ard_3-2-1_55JEL_2023-05-05_final
2023-05-05 09:54:22	ga_s2bm_ard_3-2-1_55JDL_2023-05-05_final
2023-05-05 09:55:24	ga_s2bm_ard_3-2-1_55JCG_2023-05-05_final
2023-05-05 09:55:38	ga_s2bm_ard_3-2-1_55JCF_2023-05-05_final
2023-05-05 09:55:59	ga_s2bm_ard_3-2-1_54HYK_2023-05-05_final
2023-05-05 09:56:18	ga_s2bm_ard_3-2-1_55HDC_2023-05-05_final
2023-05-05 09:56:51	ga_s2bm_ard_3-2-1_55HCA_2023-05-05_final
2023-05-05 09:57:09	ga_s2bm_ard_3-2-1_55HBV_2023-05-05_final
2023-05-05 09:57:10	ga_s2bm_ard_3-2-1_54HYE_2023-05-05_final
2023-05-05 09:57:35	ga_s2bm_ard_3-2-1_55HCT_2023-05-05_final
2023-05-05 09:57:50	ga_s2bm_ard_3-2-1_55HCS_2023-05-05_final
2023-05-05 09:58:07	ga_s2bm_ard_3-2-1_55GBR_2023-05-05_final
2023-05-05 09:58:08	ga_s2bm_ard_3-2-1_54GYA_2023-05-05_final
2023-05-05 11:31:33	ga_s2bm_ard_3-2-1_51LWE_2023-05-05_final
2023-05-05 11:32:14	ga_s2bm_ard_3-2-1_51KXB_2023-05-05_final
2023-05-05 11:32:17	ga_s2bm_ard_3-2-1_51KWB_2023-05-05_final
2023-05-05 11:32:28	ga_s2bm_ard_3-2-1_51KXA_2023-05-05_final
2023-05-05 11:32:46	ga_s2bm_ard_3-2-1_51KWV_2023-05-05_final
2023-05-05 11:33:11	ga_s2bm_ard_3-2-1_51KXT_2023-05-05_final
2023-05-05 11:33:37	ga_s2bm_ard_3-2-1_51KUS_2023-05-05_final
2023-05-05 11:33:48	ga_s2bm_ard_3-2-1_51KVR_2023-05-05_final
2023-05-05 11:34:02	ga_s2bm_ard_3-2-1_51KVQ_2023-05-05_final
2023-05-05 11:34:28	ga_s2bm_ard_3-2-1_51JWN_2023-05-05_final
2023-05-05 11:34:34	ga_s2bm_ard_3-2-1_51JUN_2023-05-05_final
2023-05-05 11:35:21	ga_s2bm_ard_3-2-1_51JTK_2023-05-05_final
2023-05-05 11:35:36	ga_s2bm_ard_3-2-1_51JTJ_2023-05-05_final
2023-05-05 11:35:47	ga_s2bm_ard_3-2-1_51JUH_2023-05-05_final
2023-05-05 11:36:02	ga_s2bm_ard_3-2-1_51JUG_2023-05-05_final
2023-05-05 11:36:29	ga_s2bm_ard_3-2-1_50JPL_2023-05-05_final
2023-05-05 11:36:36	ga_s2bm_ard_3-2-1_50HQK_2023-05-05_final
2023-05-05 11:36:45	ga_s2bm_ard_3-2-1_51HUD_2023-05-05_final
2023-05-05 11:36:51	ga_s2bm_ard_3-2-1_50HQJ_2023-05-05_final
2023-05-05 11:36:54	ga_s2bm_ard_3-2-1_50HPJ_2023-05-05_final
2023-05-05 11:37:09	ga_s2bm_ard_3-2-1_50HPH_2023-05-05_final
2023-05-05 11:37:32	ga_s2bm_ard_3-2-1_50HPG_2023-05-05_final
2023-05-05 11:37:33	ga_s2bm_ard_3-2-1_50HNG_2023-05-05_final
2023-05-06 09:27:17	ga_s2bm_ard_3-2-1_55HGU_2023-05-05_final
2023-05-06 09:27:52	ga_s2bm_ard_3-2-1_55HFS_2023-05-05_final
2023-05-06 09:28:31	ga_s2bm_ard_3-2-1_55GFP_2023-05-05_final
2023-05-06 09:28:47	ga_s2bm_ard_3-2-1_55GFN_2023-05-05_final
2023-05-16 11:06:34	ga_s2bm_ard_3-2-1_52HDJ_2023-05-16_nrt
2023-05-17 10:30:05	ga_s2bm_ard_3-2-1_54LVP_2023-05-17_nrt
2023-05-17 10:30:42	ga_s2bm_ard_3-2-1_54LTM_2023-05-17_nrt
2023-05-17 10:30:55	ga_s2bm_ard_3-2-1_54LTL_2023-05-17_nrt
2023-05-17 10:31:08	ga_s2bm_ard_3-2-1_54LTK_2023-05-17_nrt
2023-05-17 10:31:15	ga_s2bm_ard_3-2-1_54LTK_2023-05-17_nrt
2023-05-17 10:31:16	ga_s2bm_ard_3-2-1_54LTJ_2023-05-17_nrt
2023-05-17 10:31:24	ga_s2bm_ard_3-2-1_54LTJ_2023-05-17_nrt
2023-05-17 10:31:39	ga_s2bm_ard_3-2-1_54LTH_2023-05-17_nrt
2023-05-17 10:36:47	ga_s2bm_ard_3-2-1_53HLC_2023-05-17_nrt
2023-05-17 10:37:02	ga_s2bm_ard_3-2-1_53HLB_2023-05-17_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