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
2019-03-11 09:35:50	ga_s2bm_ard_3-2-1_56HLJ_2019-03-11_final.stac-item
2019-03-11 09:35:54	ga_s2bm_ard_3-2-1_56HKJ_2019-03-11_final.stac-item
2019-03-11 09:35:56	ga_s2bm_ard_3-2-1_55HGD_2019-03-11_final.stac-item
2019-03-11 09:36:00	ga_s2bm_ard_3-2-1_55HFD_2019-03-11_final.stac-item
2019-03-11 09:36:09	ga_s2bm_ard_3-2-1_56HKH_2019-03-11_final.stac-item
2019-03-11 09:36:10	ga_s2bm_ard_3-2-1_55HGC_2019-03-11_final.stac-item
2019-03-11 09:36:14	ga_s2bm_ard_3-2-1_55HFC_2019-03-11_final.stac-item
2019-03-11 09:36:23	ga_s2bm_ard_3-2-1_56HKG_2019-03-11_final.stac-item
2019-03-11 09:36:25	ga_s2bm_ard_3-2-1_55HGB_2019-03-11_final.stac-item
2019-03-11 09:36:29	ga_s2bm_ard_3-2-1_55HFB_2019-03-11_final.stac-item
2019-03-11 09:36:38	ga_s2bm_ard_3-2-1_56HKF_2019-03-11_final.stac-item
2019-03-11 09:36:39	ga_s2bm_ard_3-2-1_55HGA_2019-03-11_final.stac-item
2019-03-11 09:36:43	ga_s2bm_ard_3-2-1_55HFA_2019-03-11_final.stac-item
2019-03-11 09:36:48	ga_s2bm_ard_3-2-1_55HEA_2019-03-11_final.stac-item
2019-03-11 09:36:54	ga_s2bm_ard_3-2-1_55HGV_2019-03-11_final.stac-item
2019-03-11 09:36:57	ga_s2bm_ard_3-2-1_55HFV_2019-03-11_final.stac-item
2019-03-11 09:37:01	ga_s2bm_ard_3-2-1_55HEV_2019-03-11_final.stac-item
2019-03-11 09:37:16	ga_s2bm_ard_3-2-1_55HEU_2019-03-11_final.stac-item
2019-03-11 09:37:30	ga_s2bm_ard_3-2-1_55HET_2019-03-11_final.stac-item
2019-03-11 09:37:37	ga_s2bm_ard_3-2-1_55HDT_2019-03-11_final.stac-item
2019-03-11 09:37:45	ga_s2bm_ard_3-2-1_55HES_2019-03-11_final.stac-item
2019-03-11 09:37:49	ga_s2bm_ard_3-2-1_55HDS_2019-03-11_final.stac-item
2019-03-11 09:37:55	ga_s2bm_ard_3-2-1_55GFR_2019-03-11_final.stac-item
2019-03-11 09:37:59	ga_s2bm_ard_3-2-1_55GER_2019-03-11_final.stac-item
2019-03-11 09:38:02	ga_s2bm_ard_3-2-1_55GDR_2019-03-11_final.stac-item
2019-03-11 09:38:10	ga_s2bm_ard_3-2-1_55GFQ_2019-03-11_final.stac-item
2019-03-11 09:38:13	ga_s2bm_ard_3-2-1_55GEQ_2019-03-11_final.stac-item
2019-03-11 09:38:16	ga_s2bm_ard_3-2-1_55GDQ_2019-03-11_final.stac-item
2019-03-11 09:38:19	ga_s2bm_ard_3-2-1_55GFP_2019-03-11_final.stac-item
2019-03-11 09:38:21	ga_s2bm_ard_3-2-1_55GEQ_2019-03-11_final.stac-item
2019-03-11 09:38:21	ga_s2bm_ard_3-2-1_55GEP_2019-03-11_final.stac-item
2019-03-11 09:38:22	ga_s2bm_ard_3-2-1_55GDP_2019-03-11_final.stac-item
2019-03-11 09:38:23	ga_s2bm_ard_3-2-1_55GDQ_2019-03-11_final.stac-item
2019-03-11 09:38:26	ga_s2bm_ard_3-2-1_55GFP_2019-03-11_final.stac-item
2019-03-11 09:38:28	ga_s2bm_ard_3-2-1_55GEP_2019-03-11_final.stac-item
2019-03-11 09:38:32	ga_s2bm_ard_3-2-1_55GDP_2019-03-11_final.stac-item
2019-03-11 09:38:38	ga_s2bm_ard_3-2-1_55GCP_2019-03-11_final.stac-item
2019-03-11 09:38:38	ga_s2bm_ard_3-2-1_55GFN_2019-03-11_final.stac-item
2019-03-11 09:38:42	ga_s2bm_ard_3-2-1_55GEN_2019-03-11_final.stac-item
2019-03-11 09:38:46	ga_s2bm_ard_3-2-1_55GDN_2019-03-11_final.stac-item
2019-03-11 09:38:50	ga_s2bm_ard_3-2-1_55GCN_2019-03-11_final.stac-item
2019-03-11 11:12:08	ga_s2bm_ard_3-2-1_52KCG_2019-03-11_final.stac-item
2019-03-11 11:12:21	ga_s2bm_ard_3-2-1_52KCF_2019-03-11_final.stac-item
2019-03-11 11:12:35	ga_s2bm_ard_3-2-1_52KCE_2019-03-11_final.stac-item
2019-03-11 11:12:50	ga_s2bm_ard_3-2-1_52KCD_2019-03-11_final.stac-item
2019-03-11 11:13:04	ga_s2bm_ard_3-2-1_52KCC_2019-03-11_final.stac-item
2019-03-11 11:13:09	ga_s2bm_ard_3-2-1_52KBC_2019-03-11_final.stac-item
2019-03-11 11:13:10	ga_s2bm_ard_3-2-1_52KCC_2019-03-11_final.stac-item
2019-03-11 11:13:11	ga_s2bm_ard_3-2-1_52KCB_2019-03-11_final.stac-item
2019-03-11 11:13:12	ga_s2bm_ard_3-2-1_52KBC_2019-03-11_final.stac-item
2019-03-11 11:13:19	ga_s2bm_ard_3-2-1_52KCB_2019-03-11_final.stac-item
2019-03-11 11:13:23	ga_s2bm_ard_3-2-1_52KBB_2019-03-11_final.stac-item
2019-03-11 11:13:34	ga_s2bm_ard_3-2-1_52KCA_2019-03-11_final.stac-item
2019-03-11 11:13:37	ga_s2bm_ard_3-2-1_52KBA_2019-03-11_final.stac-item
2019-03-11 11:13:51	ga_s2bm_ard_3-2-1_52KBV_2019-03-11_final.stac-item
2019-03-11 11:14:03	ga_s2bm_ard_3-2-1_52KCU_2019-03-11_final.stac-item
2019-03-11 11:14:05	ga_s2bm_ard_3-2-1_52JET_2019-03-11_final.stac-item
2019-03-11 11:14:06	ga_s2bm_ard_3-2-1_52KBU_2019-03-11_final.stac-item
2019-03-11 11:14:14	ga_s2bm_ard_3-2-1_52JDT_2019-03-11_final.stac-item
2019-03-11 11:14:18	ga_s2bm_ard_3-2-1_52JCT_2019-03-11_final.stac-item
2019-03-11 11:14:21	ga_s2bm_ard_3-2-1_51JZN_2019-03-11_final.stac-item
2019-03-11 11:14:21	ga_s2bm_ard_3-2-1_52JBT_2019-03-11_final.stac-item
2019-03-11 11:14:26	ga_s2bm_ard_3-2-1_51JYN_2019-03-11_final.stac-item
2019-03-11 11:14:28	ga_s2bm_ard_3-2-1_52JDS_2019-03-11_final.stac-item
2019-03-11 11:14:32	ga_s2bm_ard_3-2-1_52JCS_2019-03-11_final.stac-item
2019-03-11 11:14:35	ga_s2bm_ard_3-2-1_51JZM_2019-03-11_final.stac-item
2019-03-11 11:14:35	ga_s2bm_ard_3-2-1_52JBS_2019-03-11_final.stac-item
2019-03-11 11:14:38	ga_s2bm_ard_3-2-1_51JYM_2019-03-11_final.stac-item
2019-03-11 11:14:43	ga_s2bm_ard_3-2-1_52JDR_2019-03-11_final.stac-item
2019-03-11 11:14:47	ga_s2bm_ard_3-2-1_52JCR_2019-03-11_final.stac-item
2019-03-11 11:14:50	ga_s2bm_ard_3-2-1_52JBR_2019-03-11_final.stac-item
2019-03-11 11:14:53	ga_s2bm_ard_3-2-1_51JYL_2019-03-11_final.stac-item
2019-03-11 11:14:57	ga_s2bm_ard_3-2-1_52JDQ_2019-03-11_final.stac-item
2019-03-11 11:15:01	ga_s2bm_ard_3-2-1_52JCQ_2019-03-11_final.stac-item
2019-03-11 11:15:04	ga_s2bm_ard_3-2-1_52JBQ_2019-03-11_final.stac-item
2019-03-11 11:15:08	ga_s2bm_ard_3-2-1_51JYK_2019-03-11_final.stac-item
2019-03-11 11:15:10	ga_s2bm_ard_3-2-1_52JDP_2019-03-11_final.stac-item
2019-03-11 11:15:16	ga_s2bm_ard_3-2-1_52JCP_2019-03-11_final.stac-item
2019-03-11 11:15:19	ga_s2bm_ard_3-2-1_52JBP_2019-03-11_final.stac-item
2019-03-11 11:15:20	ga_s2bm_ard_3-2-1_52JDN_2019-03-11_final.stac-item
2019-03-11 11:15:22	ga_s2bm_ard_3-2-1_51JYJ_2019-03-11_final.stac-item
2019-03-11 11:15:27	ga_s2bm_ard_3-2-1_51JXJ_2019-03-11_final.stac-item
2019-03-11 11:15:30	ga_s2bm_ard_3-2-1_52JCN_2019-03-11_final.stac-item
2019-03-11 11:15:34	ga_s2bm_ard_3-2-1_52JBN_2019-03-11_final.stac-item
2019-03-11 11:15:36	ga_s2bm_ard_3-2-1_51JYH_2019-03-11_final.stac-item
2019-03-11 11:15:40	ga_s2bm_ard_3-2-1_51JXH_2019-03-11_final.stac-item
2019-03-11 11:15:45	ga_s2bm_ard_3-2-1_52JCM_2019-03-11_final.stac-item
2019-03-11 11:15:48	ga_s2bm_ard_3-2-1_52JBM_2019-03-11_final.stac-item
2019-03-11 11:15:51	ga_s2bm_ard_3-2-1_51JYG_2019-03-11_final.stac-item
2019-03-11 11:15:54	ga_s2bm_ard_3-2-1_51JXG_2019-03-11_final.stac-item
2019-03-11 11:15:59	ga_s2bm_ard_3-2-1_52JCL_2019-03-11_final.stac-item
2019-03-11 11:16:03	ga_s2bm_ard_3-2-1_52JBL_2019-03-11_final.stac-item
2019-03-11 11:16:05	ga_s2bm_ard_3-2-1_51JYF_2019-03-11_final.stac-item
2019-03-11 11:16:09	ga_s2bm_ard_3-2-1_51JXF_2019-03-11_final.stac-item
2019-03-11 11:16:17	ga_s2bm_ard_3-2-1_52HBK_2019-03-11_final.stac-item
2019-03-11 11:16:20	ga_s2bm_ard_3-2-1_51HYE_2019-03-11_final.stac-item
2019-03-11 11:16:23	ga_s2bm_ard_3-2-1_51HXE_2019-03-11_final.stac-item
2019-03-11 11:16:28	ga_s2bm_ard_3-2-1_51HWE_2019-03-11_final.stac-item
2019-03-11 11:16:34	ga_s2bm_ard_3-2-1_51HYD_2019-03-11_final.stac-item
2019-03-11 11:16:38	ga_s2bm_ard_3-2-1_51HXD_2019-03-11_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