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
2022-10-08 09:24:39	ga_s2bm_ard_3-2-1_56JMP_2022-10-07_final.stac-item
2022-10-08 09:24:50	ga_s2bm_ard_3-2-1_56JNN_2022-10-07_final.stac-item
2022-10-08 09:24:53	ga_s2bm_ard_3-2-1_56JMN_2022-10-07_final.stac-item
2022-10-08 09:25:05	ga_s2bm_ard_3-2-1_56JNM_2022-10-07_final.stac-item
2022-10-08 09:25:08	ga_s2bm_ard_3-2-1_56JMM_2022-10-07_final.stac-item
2022-10-08 09:25:19	ga_s2bm_ard_3-2-1_56JNL_2022-10-07_final.stac-item
2022-10-08 09:25:23	ga_s2bm_ard_3-2-1_56JML_2022-10-07_final.stac-item
2022-10-08 09:25:27	ga_s2bm_ard_3-2-1_56JLL_2022-10-07_final.stac-item
2022-10-08 09:25:37	ga_s2bm_ard_3-2-1_56HMK_2022-10-07_final.stac-item
2022-10-08 09:25:40	ga_s2bm_ard_3-2-1_56HLK_2022-10-07_final.stac-item
2022-10-08 09:25:52	ga_s2bm_ard_3-2-1_56HMJ_2022-10-07_final.stac-item
2022-10-08 09:25:55	ga_s2bm_ard_3-2-1_56HLJ_2022-10-07_final.stac-item
2022-10-08 09:26:29	ga_s2bm_ard_3-2-1_56HKG_2022-10-07_final.stac-item
2022-10-08 09:26:42	ga_s2bm_ard_3-2-1_56HKF_2022-10-07_final.stac-item
2022-10-08 09:26:58	ga_s2bm_ard_3-2-1_55HGV_2022-10-07_final.stac-item
2022-10-08 09:27:59	ga_s2bm_ard_3-2-1_55GFR_2022-10-07_final.stac-item
2022-10-08 09:28:13	ga_s2bm_ard_3-2-1_55GFQ_2022-10-07_final.stac-item
2022-10-08 09:28:26	ga_s2bm_ard_3-2-1_55GFP_2022-10-07_final.stac-item
2022-10-08 09:28:33	ga_s2bm_ard_3-2-1_55GFP_2022-10-07_final.stac-item
2022-10-08 09:28:35	ga_s2bm_ard_3-2-1_55GEP_2022-10-07_final.stac-item
2022-10-08 09:28:42	ga_s2bm_ard_3-2-1_55GFN_2022-10-07_final.stac-item
2022-10-08 09:28:46	ga_s2bm_ard_3-2-1_55GEN_2022-10-07_final.stac-item
2022-10-08 11:01:49	ga_s2bm_ard_3-2-1_53KLB_2022-10-08_final.stac-item
2022-10-08 11:01:53	ga_s2bm_ard_3-2-1_53KKB_2022-10-08_final.stac-item
2022-10-08 11:01:58	ga_s2bm_ard_3-2-1_52KGG_2022-10-08_final.stac-item
2022-10-08 11:02:01	ga_s2bm_ard_3-2-1_53KLA_2022-10-08_final.stac-item
2022-10-08 11:02:01	ga_s2bm_ard_3-2-1_52KFG_2022-10-08_final.stac-item
2022-10-08 11:02:08	ga_s2bm_ard_3-2-1_53KKA_2022-10-08_final.stac-item
2022-10-08 11:02:13	ga_s2bm_ard_3-2-1_52KGF_2022-10-08_final.stac-item
2022-10-08 11:02:16	ga_s2bm_ard_3-2-1_52KFF_2022-10-08_final.stac-item
2022-10-08 11:02:22	ga_s2bm_ard_3-2-1_53KKV_2022-10-08_final.stac-item
2022-10-08 11:02:27	ga_s2bm_ard_3-2-1_52KGE_2022-10-08_final.stac-item
2022-10-08 11:02:30	ga_s2bm_ard_3-2-1_52KFE_2022-10-08_final.stac-item
2022-10-08 11:02:33	ga_s2bm_ard_3-2-1_53KKU_2022-10-08_final.stac-item
2022-10-08 11:02:35	ga_s2bm_ard_3-2-1_52KGD_2022-10-08_final.stac-item
2022-10-08 11:02:35	ga_s2bm_ard_3-2-1_52KGE_2022-10-08_final.stac-item
2022-10-08 11:02:37	ga_s2bm_ard_3-2-1_52KFD_2022-10-08_final.stac-item
2022-10-08 11:02:37	ga_s2bm_ard_3-2-1_52KFE_2022-10-08_final.stac-item
2022-10-08 11:02:40	ga_s2bm_ard_3-2-1_53KKU_2022-10-08_final.stac-item
2022-10-08 11:02:42	ga_s2bm_ard_3-2-1_52KGD_2022-10-08_final.stac-item
2022-10-08 11:02:45	ga_s2bm_ard_3-2-1_52KFD_2022-10-08_final.stac-item
2022-10-08 11:02:49	ga_s2bm_ard_3-2-1_52KED_2022-10-08_final.stac-item
2022-10-08 11:02:52	ga_s2bm_ard_3-2-1_53KKT_2022-10-08_final.stac-item
2022-10-08 11:02:56	ga_s2bm_ard_3-2-1_52KGC_2022-10-08_final.stac-item
2022-10-08 11:02:59	ga_s2bm_ard_3-2-1_52KFC_2022-10-08_final.stac-item
2022-10-08 11:03:03	ga_s2bm_ard_3-2-1_52KEC_2022-10-08_final.stac-item
2022-10-08 11:03:05	ga_s2bm_ard_3-2-1_53KKS_2022-10-08_final.stac-item
2022-10-08 11:03:11	ga_s2bm_ard_3-2-1_52KGB_2022-10-08_final.stac-item
2022-10-08 11:03:14	ga_s2bm_ard_3-2-1_52KFB_2022-10-08_final.stac-item
2022-10-08 11:03:17	ga_s2bm_ard_3-2-1_53KKR_2022-10-08_final.stac-item
2022-10-08 11:03:17	ga_s2bm_ard_3-2-1_52KEB_2022-10-08_final.stac-item
2022-10-08 11:03:20	ga_s2bm_ard_3-2-1_52KHA_2022-10-08_final.stac-item
2022-10-08 11:03:25	ga_s2bm_ard_3-2-1_52KGA_2022-10-08_final.stac-item
2022-10-08 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2022-10-08_final.stac-item
2022-10-08 11:03:32	ga_s2bm_ard_3-2-1_52KEA_2022-10-08_final.stac-item
2022-10-08 11:03:39	ga_s2bm_ard_3-2-1_52KGV_2022-10-08_final.stac-item
2022-10-08 11:03:43	ga_s2bm_ard_3-2-1_52KFV_2022-10-08_final.stac-item
2022-10-08 11:03:46	ga_s2bm_ard_3-2-1_52KEV_2022-10-08_final.stac-item
2022-10-08 11:03:51	ga_s2bm_ard_3-2-1_52KDV_2022-10-08_final.stac-item
2022-10-08 11:03:54	ga_s2bm_ard_3-2-1_52KGU_2022-10-08_final.stac-item
2022-10-08 11:03:57	ga_s2bm_ard_3-2-1_52KFU_2022-10-08_final.stac-item
2022-10-08 11:04:01	ga_s2bm_ard_3-2-1_52KEU_2022-10-08_final.stac-item
2022-10-08 11:04:04	ga_s2bm_ard_3-2-1_52KDU_2022-10-08_final.stac-item
2022-10-08 11:04:08	ga_s2bm_ard_3-2-1_52JGT_2022-10-08_final.stac-item
2022-10-08 11:04:12	ga_s2bm_ard_3-2-1_52JFT_2022-10-08_final.stac-item
2022-10-08 11:04:16	ga_s2bm_ard_3-2-1_52JET_2022-10-08_final.stac-item
2022-10-08 11:04:19	ga_s2bm_ard_3-2-1_52JDT_2022-10-08_final.stac-item
2022-10-08 11:04:22	ga_s2bm_ard_3-2-1_52JGS_2022-10-08_final.stac-item
2022-10-08 11:04:26	ga_s2bm_ard_3-2-1_52JFS_2022-10-08_final.stac-item
2022-10-08 11:04:30	ga_s2bm_ard_3-2-1_52JES_2022-10-08_final.stac-item
2022-10-08 11:04:33	ga_s2bm_ard_3-2-1_52JGR_2022-10-08_final.stac-item
2022-10-08 11:04:33	ga_s2bm_ard_3-2-1_52JDS_2022-10-08_final.stac-item
2022-10-08 11:04:41	ga_s2bm_ard_3-2-1_52JFR_2022-10-08_final.stac-item
2022-10-08 11:04:45	ga_s2bm_ard_3-2-1_52JER_2022-10-08_final.stac-item
2022-10-08 11:04:48	ga_s2bm_ard_3-2-1_52JDR_2022-10-08_final.stac-item
2022-10-08 11:04:53	ga_s2bm_ard_3-2-1_52JCR_2022-10-08_final.stac-item
2022-10-08 11:04:55	ga_s2bm_ard_3-2-1_52JFQ_2022-10-08_final.stac-item
2022-10-08 11:04:59	ga_s2bm_ard_3-2-1_52JEQ_2022-10-08_final.stac-item
2022-10-08 11:05:02	ga_s2bm_ard_3-2-1_52JDQ_2022-10-08_final.stac-item
2022-10-08 11:05:06	ga_s2bm_ard_3-2-1_52JCQ_2022-10-08_final.stac-item
2022-10-08 11:05:10	ga_s2bm_ard_3-2-1_52JFP_2022-10-08_final.stac-item
2022-10-08 11:05:14	ga_s2bm_ard_3-2-1_52JEP_2022-10-08_final.stac-item
2022-10-08 11:05:17	ga_s2bm_ard_3-2-1_52JDP_2022-10-08_final.stac-item
2022-10-08 11:05:20	ga_s2bm_ard_3-2-1_52JCP_2022-10-08_final.stac-item
2022-10-08 11:05:24	ga_s2bm_ard_3-2-1_52JFN_2022-10-08_final.stac-item
2022-10-08 11:05:28	ga_s2bm_ard_3-2-1_52JEN_2022-10-08_final.stac-item
2022-10-08 11:05:32	ga_s2bm_ard_3-2-1_52JDN_2022-10-08_final.stac-item
2022-10-08 11:05:35	ga_s2bm_ard_3-2-1_52JCN_2022-10-08_final.stac-item
2022-10-08 11:05:36	ga_s2bm_ard_3-2-1_52JFM_2022-10-08_final.stac-item
2022-10-08 11:05:42	ga_s2bm_ard_3-2-1_52JEM_2022-10-08_final.stac-item
2022-10-08 11:05:46	ga_s2bm_ard_3-2-1_52JDM_2022-10-08_final.stac-item
2022-10-08 11:05:49	ga_s2bm_ard_3-2-1_52JCM_2022-10-08_final.stac-item
2022-10-08 11:05:56	ga_s2bm_ard_3-2-1_52JBM_2022-10-08_final.stac-item
2022-10-08 11:05:57	ga_s2bm_ard_3-2-1_52JEL_2022-10-08_final.stac-item
2022-10-08 11:06:01	ga_s2bm_ard_3-2-1_52JDL_2022-10-08_final.stac-item
2022-10-08 11:06:04	ga_s2bm_ard_3-2-1_52JCL_2022-10-08_final.stac-item
2022-10-08 11:06:08	ga_s2bm_ard_3-2-1_52JBL_2022-10-08_final.stac-item
2022-10-08 11:06:21	ga_s2bm_ard_3-2-1_52HBK_2022-10-08_final.stac-item
2022-10-08 11:06:34	ga_s2bm_ard_3-2-1_51HYD_2022-10-08_final.stac-item
2022-10-09 08:55:18	ga_s2bm_ard_3-2-1_57JWF_2022-10-08_interim

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