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
2023-02-17 10:02:46	ga_s2bm_ard_3-2-1_55KDS_2023-02-17_final
2023-02-17 10:02:49	ga_s2bm_ard_3-2-1_55KCS_2023-02-17_final
2023-02-17 10:02:52	ga_s2bm_ard_3-2-1_55KBS_2023-02-17_final
2023-02-17 10:02:53	ga_s2bm_ard_3-2-1_54KZB_2023-02-17_final
2023-02-17 10:02:56	ga_s2bm_ard_3-2-1_55KER_2023-02-17_final
2023-02-17 10:03:00	ga_s2bm_ard_3-2-1_55KDR_2023-02-17_final
2023-02-17 10:03:04	ga_s2bm_ard_3-2-1_55KCR_2023-02-17_final
2023-02-17 10:03:07	ga_s2bm_ard_3-2-1_55KEQ_2023-02-17_nrt.stac-item
2023-02-17 10:03:07	ga_s2bm_ard_3-2-1_55KEQ_2023-02-17_final
2023-02-17 10:03:07	ga_s2bm_ard_3-2-1_55KBR_2023-02-17_final
2023-02-17 10:03:07	ga_s2bm_ard_3-2-1_54KZA_2023-02-17_final
2023-02-17 10:03:15	ga_s2bm_ard_3-2-1_55KDQ_2023-02-17_final
2023-02-17 10:03:18	ga_s2bm_ard_3-2-1_55KCQ_2023-02-17_nrt.stac-item
2023-02-17 10:03:18	ga_s2bm_ard_3-2-1_55KCQ_2023-02-17_final
2023-02-17 10:03:22	ga_s2bm_ard_3-2-1_55KBQ_2023-02-17_final
2023-02-17 10:03:22	ga_s2bm_ard_3-2-1_54KZV_2023-02-17_nrt.stac-item
2023-02-17 10:03:22	ga_s2bm_ard_3-2-1_54KZV_2023-02-17_final
2023-02-17 10:03:29	ga_s2bm_ard_3-2-1_55KDP_2023-02-17_final
2023-02-17 10:03:33	ga_s2bm_ard_3-2-1_55KCP_2023-02-17_final
2023-02-17 10:03:36	ga_s2bm_ard_3-2-1_55KBP_2023-02-17_final
2023-02-17 10:03:36	ga_s2bm_ard_3-2-1_54KZU_2023-02-17_final
2023-02-17 10:03:40	ga_s2bm_ard_3-2-1_54KYU_2023-02-17_final
2023-02-17 10:03:44	ga_s2bm_ard_3-2-1_55JDN_2023-02-17_final
2023-02-17 10:03:48	ga_s2bm_ard_3-2-1_55JCN_2023-02-17_final
2023-02-17 10:03:51	ga_s2bm_ard_3-2-1_54JZT_2023-02-17_final
2023-02-17 10:03:51	ga_s2bm_ard_3-2-1_55JBN_2023-02-17_final
2023-02-17 10:03:54	ga_s2bm_ard_3-2-1_54JYT_2023-02-17_final
2023-02-17 10:03:58	ga_s2bm_ard_3-2-1_55JDM_2023-02-17_final
2023-02-17 10:04:02	ga_s2bm_ard_3-2-1_55JCM_2023-02-17_nrt.stac-item
2023-02-17 10:04:02	ga_s2bm_ard_3-2-1_55JCM_2023-02-17_final
2023-02-17 10:04:05	ga_s2bm_ard_3-2-1_54JZS_2023-02-17_final
2023-02-17 10:04:05	ga_s2bm_ard_3-2-1_55JBM_2023-02-17_final
2023-02-17 10:04:09	ga_s2bm_ard_3-2-1_54JYS_2023-02-17_final
2023-02-17 10:04:11	ga_s2bm_ard_3-2-1_55JDL_2023-02-17_final
2023-02-17 10:04:15	ga_s2bm_ard_3-2-1_55JCL_2023-02-17_final
2023-02-17 10:04:16	ga_s2bm_ard_3-2-1_55JBL_2023-02-17_nrt.stac-item
2023-02-17 10:04:16	ga_s2bm_ard_3-2-1_55JBL_2023-02-17_final
2023-02-17 10:04:18	ga_s2bm_ard_3-2-1_54JYR_2023-02-17_final
2023-02-17 10:04:19	ga_s2bm_ard_3-2-1_55JDL_2023-02-17_final
2023-02-17 10:04:21	ga_s2bm_ard_3-2-1_55JDK_2023-02-17_final
2023-02-17 10:04:22	ga_s2bm_ard_3-2-1_55JCL_2023-02-17_final
2023-02-17 10:04:23	ga_s2bm_ard_3-2-1_55JBL_2023-02-17_final
2023-02-17 10:04:25	ga_s2bm_ard_3-2-1_54JYR_2023-02-17_final
2023-02-17 10:04:30	ga_s2bm_ard_3-2-1_54JXR_2023-02-17_final
2023-02-17 10:04:31	ga_s2bm_ard_3-2-1_55JCK_2023-02-17_final
2023-02-17 10:04:35	ga_s2bm_ard_3-2-1_55JBK_2023-02-17_final
2023-02-17 10:04:38	ga_s2bm_ard_3-2-1_54JYQ_2023-02-17_nrt.stac-item
2023-02-17 10:04:38	ga_s2bm_ard_3-2-1_54JYQ_2023-02-17_final
2023-02-17 10:04:42	ga_s2bm_ard_3-2-1_54JXQ_2023-02-17_final
2023-02-17 10:04:46	ga_s2bm_ard_3-2-1_55JCJ_2023-02-17_final
2023-02-17 10:04:49	ga_s2bm_ard_3-2-1_55JBJ_2023-02-17_final
2023-02-17 10:04:52	ga_s2bm_ard_3-2-1_54JYP_2023-02-17_final
2023-02-17 10:04:55	ga_s2bm_ard_3-2-1_54JXP_2023-02-17_final
2023-02-17 10:05:00	ga_s2bm_ard_3-2-1_55JCH_2023-02-17_final
2023-02-17 10:05:04	ga_s2bm_ard_3-2-1_55JBH_2023-02-17_nrt.stac-item
2023-02-17 10:05:04	ga_s2bm_ard_3-2-1_55JBH_2023-02-17_final
2023-02-17 10:05:06	ga_s2bm_ard_3-2-1_54JYN_2023-02-17_final
2023-02-17 10:05:10	ga_s2bm_ard_3-2-1_54JXN_2023-02-17_final
2023-02-17 10:05:14	ga_s2bm_ard_3-2-1_55JCG_2023-02-17_final
2023-02-17 10:05:18	ga_s2bm_ard_3-2-1_55JBG_2023-02-17_final
2023-02-17 10:05:21	ga_s2bm_ard_3-2-1_54JYM_2023-02-17_final
2023-02-17 10:05:25	ga_s2bm_ard_3-2-1_54JXM_2023-02-17_final
2023-02-17 10:05:27	ga_s2bm_ard_3-2-1_55JCF_2023-02-17_final
2023-02-17 10:05:31	ga_s2bm_ard_3-2-1_54JWM_2023-02-17_final
2023-02-17 10:05:33	ga_s2bm_ard_3-2-1_55JBF_2023-02-17_final
2023-02-17 10:05:35	ga_s2bm_ard_3-2-1_54JYL_2023-02-17_final
2023-02-17 10:05:37	ga_s2bm_ard_3-2-1_55HCE_2023-02-17_final
2023-02-17 10:05:39	ga_s2bm_ard_3-2-1_54JXL_2023-02-17_final
2023-02-17 10:05:43	ga_s2bm_ard_3-2-1_54JWL_2023-02-17_final
2023-02-17 10:05:47	ga_s2bm_ard_3-2-1_55HBE_2023-02-17_final
2023-02-17 10:05:50	ga_s2bm_ard_3-2-1_54HYK_2023-02-17_final
2023-02-17 10:05:53	ga_s2bm_ard_3-2-1_54HXK_2023-02-17_final
2023-02-17 10:05:57	ga_s2bm_ard_3-2-1_54HWK_2023-02-17_final
2023-02-17 10:06:02	ga_s2bm_ard_3-2-1_55HBD_2023-02-17_nrt.stac-item
2023-02-17 10:06:02	ga_s2bm_ard_3-2-1_55HBD_2023-02-17_final
2023-02-17 10:06:04	ga_s2bm_ard_3-2-1_54HYJ_2023-02-17_final
2023-02-17 11:45:01	ga_s2bm_ard_3-2-1_50JQR_2023-02-17_final
2023-02-17 11:45:12	ga_s2bm_ard_3-2-1_51JTK_2023-02-17_final
2023-02-17 11:45:16	ga_s2bm_ard_3-2-1_50JQQ_2023-02-17_final
2023-02-17 11:45:37	ga_s2bm_ard_3-2-1_50JNP_2023-02-17_final
2023-02-17 11:45:41	ga_s2bm_ard_3-2-1_51JTH_2023-02-17_final
2023-02-17 11:45:44	ga_s2bm_ard_3-2-1_50JQN_2023-02-17_final
2023-02-17 11:45:52	ga_s2bm_ard_3-2-1_50JNN_2023-02-17_final
2023-02-17 11:45:59	ga_s2bm_ard_3-2-1_50JQM_2023-02-17_final
2023-02-17 11:46:05	ga_s2bm_ard_3-2-1_51JTF_2023-02-17_final
2023-02-17 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2023-02-17_final
2023-02-17 11:46:50	ga_s2bm_ard_3-2-1_50HNJ_2023-02-17_final
2023-02-17 11:46:51	ga_s2bm_ard_3-2-1_50HQH_2023-02-17_final
2023-02-17 11:46:53	ga_s2bm_ard_3-2-1_50HMJ_2023-02-17_final
2023-02-17 11:47:00	ga_s2bm_ard_3-2-1_50HPH_2023-02-17_final
2023-02-17 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2023-02-17_final
2023-02-17 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2023-02-17_final
2023-02-17 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2023-02-17_final
2023-02-17 11:47:15	ga_s2bm_ard_3-2-1_50HPG_2023-02-17_final
2023-02-17 11:47:19	ga_s2bm_ard_3-2-1_50HNG_2023-02-17_final
2023-02-17 11:47:22	ga_s2bm_ard_3-2-1_50HMG_2023-02-17_final
2023-02-17 11:47:25	ga_s2bm_ard_3-2-1_50HLG_2023-02-17_final
2023-02-17 11:47:28	ga_s2bm_ard_3-2-1_50HPF_2023-02-17_nrt.stac-item
2023-02-17 11:47:30	ga_s2bm_ard_3-2-1_50HNF_2023-02-17_nrt.stac-item
2023-02-17 11:47:32	ga_s2bm_ard_3-2-1_50HMF_2023-02-17_nrt.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