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
2022-06-15 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2022-06-15_final.stac-item
2022-06-16 09:41:27	ga_s2bm_ard_3-2-1_56KMG_2022-06-16_final
2022-06-16 09:41:31	ga_s2bm_ard_3-2-1_56KLG_2022-06-16_final
2022-06-16 09:41:33	ga_s2bm_ard_3-2-1_56KKG_2022-06-16_final
2022-06-16 09:41:36	ga_s2bm_ard_3-2-1_55KHB_2022-06-16_final
2022-06-16 09:41:42	ga_s2bm_ard_3-2-1_56KMF_2022-06-16_final
2022-06-16 09:41:45	ga_s2bm_ard_3-2-1_56KLF_2022-06-16_final.stac-item
2022-06-16 09:41:48	ga_s2bm_ard_3-2-1_56KKF_2022-06-16_final.stac-item
2022-06-16 09:41:56	ga_s2bm_ard_3-2-1_56KME_2022-06-16_final
2022-06-16 09:42:00	ga_s2bm_ard_3-2-1_56KLE_2022-06-16_final.stac-item
2022-06-16 09:42:11	ga_s2bm_ard_3-2-1_56KMD_2022-06-16_final
2022-06-16 09:42:14	ga_s2bm_ard_3-2-1_56KLD_2022-06-16_final.stac-item
2022-06-16 09:42:37	ga_s2bm_ard_3-2-1_55KGT_2022-06-16_final.stac-item
2022-06-16 09:42:40	ga_s2bm_ard_3-2-1_56KMB_2022-06-16_final
2022-06-16 09:42:43	ga_s2bm_ard_3-2-1_56KLB_2022-06-16_final.stac-item
2022-06-16 09:42:47	ga_s2bm_ard_3-2-1_56KKB_2022-06-16_final.stac-item
2022-06-16 09:42:47	ga_s2bm_ard_3-2-1_55KHS_2022-06-16_final.stac-item
2022-06-16 09:42:50	ga_s2bm_ard_3-2-1_55KGS_2022-06-16_final.stac-item
2022-06-16 09:42:53	ga_s2bm_ard_3-2-1_56KMA_2022-06-16_final.stac-item
2022-06-16 09:42:58	ga_s2bm_ard_3-2-1_56KLA_2022-06-16_final.stac-item
2022-06-16 09:43:01	ga_s2bm_ard_3-2-1_56KKA_2022-06-16_final.stac-item
2022-06-16 09:43:01	ga_s2bm_ard_3-2-1_55KHR_2022-06-16_final.stac-item
2022-06-16 09:43:05	ga_s2bm_ard_3-2-1_55KGR_2022-06-16_final.stac-item
2022-06-16 09:43:12	ga_s2bm_ard_3-2-1_56KLV_2022-06-16_final.stac-item
2022-06-16 09:43:16	ga_s2bm_ard_3-2-1_56KKV_2022-06-16_final.stac-item
2022-06-16 09:43:16	ga_s2bm_ard_3-2-1_55KHQ_2022-06-16_final.stac-item
2022-06-16 09:43:19	ga_s2bm_ard_3-2-1_55KGQ_2022-06-16_final.stac-item
2022-06-16 09:43:27	ga_s2bm_ard_3-2-1_56KLU_2022-06-16_final.stac-item
2022-06-16 09:43:27	ga_s2bm_ard_3-2-1_55KFQ_2022-06-16_final.stac-item
2022-06-16 09:43:30	ga_s2bm_ard_3-2-1_56KKU_2022-06-16_final.stac-item
2022-06-16 09:43:30	ga_s2bm_ard_3-2-1_55KHP_2022-06-16_final.stac-item
2022-06-16 09:43:34	ga_s2bm_ard_3-2-1_55KGP_2022-06-16_final.stac-item
2022-06-16 09:43:38	ga_s2bm_ard_3-2-1_55KFP_2022-06-16_final.stac-item
2022-06-16 09:43:42	ga_s2bm_ard_3-2-1_56JLT_2022-06-16_final.stac-item
2022-06-16 09:43:45	ga_s2bm_ard_3-2-1_55JHN_2022-06-16_final.stac-item
2022-06-16 09:43:45	ga_s2bm_ard_3-2-1_56JKT_2022-06-16_final.stac-item
2022-06-16 09:43:48	ga_s2bm_ard_3-2-1_55JGN_2022-06-16_final.stac-item
2022-06-16 09:43:52	ga_s2bm_ard_3-2-1_55JFN_2022-06-16_final.stac-item
2022-06-16 09:43:56	ga_s2bm_ard_3-2-1_56JLS_2022-06-16_final.stac-item
2022-06-16 09:43:59	ga_s2bm_ard_3-2-1_55JHM_2022-06-16_final.stac-item
2022-06-16 09:43:59	ga_s2bm_ard_3-2-1_56JKS_2022-06-16_final.stac-item
2022-06-16 09:44:03	ga_s2bm_ard_3-2-1_55JGM_2022-06-16_final.stac-item
2022-06-16 09:44:06	ga_s2bm_ard_3-2-1_55JFM_2022-06-16_final.stac-item
2022-06-16 09:44:09	ga_s2bm_ard_3-2-1_56JLR_2022-06-16_final.stac-item
2022-06-16 09:44:14	ga_s2bm_ard_3-2-1_56JKR_2022-06-16_final.stac-item
2022-06-16 09:44:19	ga_s2bm_ard_3-2-1_56JLQ_2022-06-16_final.stac-item
2022-06-16 09:44:28	ga_s2bm_ard_3-2-1_56JKQ_2022-06-16_final.stac-item
2022-06-16 09:44:43	ga_s2bm_ard_3-2-1_56JKP_2022-06-16_final.stac-item
2022-06-16 09:44:58	ga_s2bm_ard_3-2-1_56JKN_2022-06-16_final.stac-item
2022-06-16 09:45:12	ga_s2bm_ard_3-2-1_56JKM_2022-06-16_final.stac-item
2022-06-16 09:45:25	ga_s2bm_ard_3-2-1_56JKL_2022-06-16_final.stac-item
2022-06-16 09:45:36	ga_s2bm_ard_3-2-1_56HKK_2022-06-16_final.stac-item
2022-06-16 09:45:44	ga_s2bm_ard_3-2-1_55HGE_2022-06-16_final.stac-item
2022-06-16 09:45:48	ga_s2bm_ard_3-2-1_55HFE_2022-06-16_final.stac-item
2022-06-16 09:45:51	ga_s2bm_ard_3-2-1_55HEE_2022-06-16_final.stac-item
2022-06-16 09:45:54	ga_s2bm_ard_3-2-1_55HDE_2022-06-16_final.stac-item
2022-06-16 09:45:58	ga_s2bm_ard_3-2-1_55HGD_2022-06-16_final.stac-item
2022-06-16 09:46:02	ga_s2bm_ard_3-2-1_55HFD_2022-06-16_final.stac-item
2022-06-16 09:46:06	ga_s2bm_ard_3-2-1_55HED_2022-06-16_final.stac-item
2022-06-16 09:46:09	ga_s2bm_ard_3-2-1_55HDD_2022-06-16_final.stac-item
2022-06-16 09:46:11	ga_s2bm_ard_3-2-1_55HGC_2022-06-16_final.stac-item
2022-06-16 09:46:16	ga_s2bm_ard_3-2-1_55HFC_2022-06-16_final.stac-item
2022-06-16 09:46:20	ga_s2bm_ard_3-2-1_55HEC_2022-06-16_final.stac-item
2022-06-16 09:46:20	ga_s2bm_ard_3-2-1_55HGB_2022-06-16_final.stac-item
2022-06-16 09:46:24	ga_s2bm_ard_3-2-1_55HDC_2022-06-16_final.stac-item
2022-06-16 09:46:31	ga_s2bm_ard_3-2-1_55HFB_2022-06-16_final.stac-item
2022-06-16 09:46:31	ga_s2bm_ard_3-2-1_55HCC_2022-06-16_final.stac-item
2022-06-16 09:46:35	ga_s2bm_ard_3-2-1_55HEB_2022-06-16_final.stac-item
2022-06-16 09:46:38	ga_s2bm_ard_3-2-1_55HDB_2022-06-16_final.stac-item
2022-06-16 09:46:42	ga_s2bm_ard_3-2-1_55HCB_2022-06-16_final.stac-item
2022-06-16 09:46:45	ga_s2bm_ard_3-2-1_55HFA_2022-06-16_final.stac-item
2022-06-16 09:46:49	ga_s2bm_ard_3-2-1_55HEA_2022-06-16_final.stac-item
2022-06-16 09:46:53	ga_s2bm_ard_3-2-1_55HDA_2022-06-16_final.stac-item
2022-06-16 09:46:56	ga_s2bm_ard_3-2-1_55HCA_2022-06-16_final.stac-item
2022-06-16 09:47:00	ga_s2bm_ard_3-2-1_55HFV_2022-06-16_final.stac-item
2022-06-16 09:47:04	ga_s2bm_ard_3-2-1_55HEV_2022-06-16_final.stac-item
2022-06-16 09:47:07	ga_s2bm_ard_3-2-1_55HDV_2022-06-16_final.stac-item
2022-06-16 09:47:11	ga_s2bm_ard_3-2-1_55HCV_2022-06-16_final.stac-item
2022-06-16 09:47:18	ga_s2bm_ard_3-2-1_55HEU_2022-06-16_final.stac-item
2022-06-16 09:47:22	ga_s2bm_ard_3-2-1_55HDU_2022-06-16_final.stac-item
2022-06-16 09:47:25	ga_s2bm_ard_3-2-1_55HCU_2022-06-16_final.stac-item
2022-06-16 09:47:32	ga_s2bm_ard_3-2-1_55HET_2022-06-16_final.stac-item
2022-06-16 09:47:33	ga_s2bm_ard_3-2-1_55HBU_2022-06-16_final.stac-item
2022-06-16 09:47:36	ga_s2bm_ard_3-2-1_55HDT_2022-06-16_final.stac-item
2022-06-16 09:47:40	ga_s2bm_ard_3-2-1_55HCT_2022-06-16_final.stac-item
2022-06-16 09:47:44	ga_s2bm_ard_3-2-1_55HBT_2022-06-16_final.stac-item
2022-06-16 09:47:47	ga_s2bm_ard_3-2-1_55HES_2022-06-16_final.stac-item
2022-06-16 09:47:48	ga_s2bm_ard_3-2-1_54HYC_2022-06-16_final.stac-item
2022-06-16 09:47:51	ga_s2bm_ard_3-2-1_55HDS_2022-06-16_final.stac-item
2022-06-16 09:47:54	ga_s2bm_ard_3-2-1_55HCS_2022-06-16_final.stac-item
2022-06-16 09:47:57	ga_s2bm_ard_3-2-1_55HBS_2022-06-16_final.stac-item
2022-06-16 09:47:58	ga_s2bm_ard_3-2-1_54HYB_2022-06-16_final.stac-item
2022-06-16 09:48:02	ga_s2bm_ard_3-2-1_55GER_2022-06-16_final.stac-item
2022-06-16 09:48:05	ga_s2bm_ard_3-2-1_55GDR_2022-06-16_final.stac-item
2022-06-16 09:48:09	ga_s2bm_ard_3-2-1_55GCR_2022-06-16_final.stac-item
2022-06-16 09:48:12	ga_s2bm_ard_3-2-1_55GBR_2022-06-16_final.stac-item
2022-06-16 09:48:12	ga_s2bm_ard_3-2-1_54GYA_2022-06-16_final.stac-item
2022-06-16 09:48:15	ga_s2bm_ard_3-2-1_55GEQ_2022-06-16_final.stac-item
2022-06-16 09:48:20	ga_s2bm_ard_3-2-1_55GDQ_2022-06-16_final.stac-item
2022-06-16 09:48:23	ga_s2bm_ard_3-2-1_55GCQ_2022-06-16_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