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
2018-12-01 09:33:08	ga_s2bm_ard_3-2-1_56KLV_2018-12-01_final.stac-item
2018-12-01 09:33:20	ga_s2bm_ard_3-2-1_56KMU_2018-12-01_final.stac-item
2018-12-01 09:33:23	ga_s2bm_ard_3-2-1_56KLU_2018-12-01_final.stac-item
2018-12-01 09:33:31	ga_s2bm_ard_3-2-1_56JNT_2018-12-01_final.stac-item
2018-12-01 09:33:35	ga_s2bm_ard_3-2-1_56JMT_2018-12-01_final.stac-item
2018-12-01 09:33:38	ga_s2bm_ard_3-2-1_56JLT_2018-12-01_final.stac-item
2018-12-01 09:33:45	ga_s2bm_ard_3-2-1_56JKT_2018-12-01_final.stac-item
2018-12-01 09:33:45	ga_s2bm_ard_3-2-1_56JNS_2018-12-01_final.stac-item
2018-12-01 09:33:49	ga_s2bm_ard_3-2-1_56JMS_2018-12-01_final.stac-item
2018-12-01 09:33:52	ga_s2bm_ard_3-2-1_56JLS_2018-12-01_final.stac-item
2018-12-01 09:33:56	ga_s2bm_ard_3-2-1_55JHM_2018-12-01_final.stac-item
2018-12-01 09:33:56	ga_s2bm_ard_3-2-1_56JKS_2018-12-01_final.stac-item
2018-12-01 09:34:04	ga_s2bm_ard_3-2-1_56JMR_2018-12-01_final.stac-item
2018-12-01 09:34:07	ga_s2bm_ard_3-2-1_56JLR_2018-12-01_final.stac-item
2018-12-01 09:34:10	ga_s2bm_ard_3-2-1_56JKR_2018-12-01_final.stac-item
2018-12-01 09:34:18	ga_s2bm_ard_3-2-1_56JMQ_2018-12-01_final.stac-item
2018-12-01 09:34:22	ga_s2bm_ard_3-2-1_56JLQ_2018-12-01_final.stac-item
2018-12-01 09:34:25	ga_s2bm_ard_3-2-1_56JKQ_2018-12-01_final.stac-item
2018-12-01 09:34:33	ga_s2bm_ard_3-2-1_56JMP_2018-12-01_final.stac-item
2018-12-01 09:34:36	ga_s2bm_ard_3-2-1_56JLP_2018-12-01_final.stac-item
2018-12-01 09:34:39	ga_s2bm_ard_3-2-1_56JNN_2018-12-01_final.stac-item
2018-12-01 09:34:39	ga_s2bm_ard_3-2-1_56JKP_2018-12-01_final.stac-item
2018-12-01 09:34:46	ga_s2bm_ard_3-2-1_55JGJ_2018-12-01_final.stac-item
2018-12-01 09:34:47	ga_s2bm_ard_3-2-1_56JMN_2018-12-01_final.stac-item
2018-12-01 09:34:51	ga_s2bm_ard_3-2-1_56JLN_2018-12-01_final.stac-item
2018-12-01 09:34:54	ga_s2bm_ard_3-2-1_56JKN_2018-12-01_final.stac-item
2018-12-01 09:34:57	ga_s2bm_ard_3-2-1_55JGH_2018-12-01_final.stac-item
2018-12-01 09:35:02	ga_s2bm_ard_3-2-1_56JMM_2018-12-01_final.stac-item
2018-12-01 09:35:05	ga_s2bm_ard_3-2-1_56JLM_2018-12-01_final.stac-item
2018-12-01 09:35:08	ga_s2bm_ard_3-2-1_56JKM_2018-12-01_final.stac-item
2018-12-01 09:35:11	ga_s2bm_ard_3-2-1_55JGG_2018-12-01_final.stac-item
2018-12-01 09:35:16	ga_s2bm_ard_3-2-1_56JML_2018-12-01_final.stac-item
2018-12-01 09:35:20	ga_s2bm_ard_3-2-1_56JLL_2018-12-01_final.stac-item
2018-12-01 09:35:23	ga_s2bm_ard_3-2-1_56JKL_2018-12-01_final.stac-item
2018-12-01 09:35:25	ga_s2bm_ard_3-2-1_55JGF_2018-12-01_final.stac-item
2018-12-01 09:35:31	ga_s2bm_ard_3-2-1_56HMK_2018-12-01_final.stac-item
2018-12-01 09:35:34	ga_s2bm_ard_3-2-1_56HLK_2018-12-01_final.stac-item
2018-12-01 09:35:38	ga_s2bm_ard_3-2-1_56HKK_2018-12-01_final.stac-item
2018-12-01 09:35:40	ga_s2bm_ard_3-2-1_55HGE_2018-12-01_final.stac-item
2018-12-01 09:35:44	ga_s2bm_ard_3-2-1_56HMJ_2018-12-01_final.stac-item
2018-12-01 09:35:46	ga_s2bm_ard_3-2-1_55HFE_2018-12-01_final.stac-item
2018-12-01 09:35:49	ga_s2bm_ard_3-2-1_56HLJ_2018-12-01_final.stac-item
2018-12-01 09:35:52	ga_s2bm_ard_3-2-1_56HKJ_2018-12-01_final.stac-item
2018-12-01 09:35:54	ga_s2bm_ard_3-2-1_55HGD_2018-12-01_final.stac-item
2018-12-01 09:35:58	ga_s2bm_ard_3-2-1_55HFD_2018-12-01_final.stac-item
2018-12-01 09:36:07	ga_s2bm_ard_3-2-1_56HKH_2018-12-01_final.stac-item
2018-12-01 09:36:09	ga_s2bm_ard_3-2-1_55HGC_2018-12-01_final.stac-item
2018-12-01 09:36:12	ga_s2bm_ard_3-2-1_55HFC_2018-12-01_final.stac-item
2018-12-01 09:36:21	ga_s2bm_ard_3-2-1_56HKG_2018-12-01_final.stac-item
2018-12-01 09:36:23	ga_s2bm_ard_3-2-1_55HGB_2018-12-01_final.stac-item
2018-12-01 09:36:27	ga_s2bm_ard_3-2-1_55HFB_2018-12-01_final
2018-12-01 09:36:36	ga_s2bm_ard_3-2-1_56HKF_2018-12-01_final.stac-item
2018-12-01 09:36:38	ga_s2bm_ard_3-2-1_55HGA_2018-12-01_final.stac-item
2018-12-01 09:36:41	ga_s2bm_ard_3-2-1_55HFA_2018-12-01_final.stac-item
2018-12-01 09:36:46	ga_s2bm_ard_3-2-1_55HEA_2018-12-01_final.stac-item
2018-12-01 09:36:52	ga_s2bm_ard_3-2-1_55HGV_2018-12-01_final.stac-item
2018-12-01 09:36:56	ga_s2bm_ard_3-2-1_55HFV_2018-12-01_final.stac-item
2018-12-01 09:36:59	ga_s2bm_ard_3-2-1_55HEV_2018-12-01_final.stac-item
2018-12-01 09:37:14	ga_s2bm_ard_3-2-1_55HEU_2018-12-01_final.stac-item
2018-12-01 09:37:29	ga_s2bm_ard_3-2-1_55HET_2018-12-01_final.stac-item
2018-12-01 09:37:35	ga_s2bm_ard_3-2-1_55HDT_2018-12-01_final.stac-item
2018-12-01 09:37:43	ga_s2bm_ard_3-2-1_55HES_2018-12-01_final.stac-item
2018-12-01 09:37:47	ga_s2bm_ard_3-2-1_55HDS_2018-12-01_final.stac-item
2018-12-01 09:37:53	ga_s2bm_ard_3-2-1_55GFR_2018-12-01_final.stac-item
2018-12-01 09:37:57	ga_s2bm_ard_3-2-1_55GER_2018-12-01_final.stac-item
2018-12-01 09:38:01	ga_s2bm_ard_3-2-1_55GDR_2018-12-01_final.stac-item
2018-12-01 09:38:08	ga_s2bm_ard_3-2-1_55GFQ_2018-12-01_final.stac-item
2018-12-01 09:38:12	ga_s2bm_ard_3-2-1_55GEQ_2018-12-01_final.stac-item
2018-12-01 09:38:16	ga_s2bm_ard_3-2-1_55GDQ_2018-12-01_final.stac-item
2018-12-01 09:38:22	ga_s2bm_ard_3-2-1_55GFP_2018-12-01_final.stac-item
2018-12-01 09:38:26	ga_s2bm_ard_3-2-1_55GEP_2018-12-01_final.stac-item
2018-12-01 09:38:30	ga_s2bm_ard_3-2-1_55GDP_2018-12-01_final.stac-item
2018-12-01 09:38:36	ga_s2bm_ard_3-2-1_55GCP_2018-12-01_final.stac-item
2018-12-01 09:38:36	ga_s2bm_ard_3-2-1_55GFN_2018-12-01_final.stac-item
2018-12-01 09:38:41	ga_s2bm_ard_3-2-1_55GEN_2018-12-01_final.stac-item
2018-12-01 09:38:44	ga_s2bm_ard_3-2-1_55GDN_2018-12-01_final.stac-item
2018-12-01 09:38:48	ga_s2bm_ard_3-2-1_55GCN_2018-12-01_final.stac-item
2018-12-01 11:12:06	ga_s2bm_ard_3-2-1_52KCG_2018-12-01_final.stac-item
2018-12-01 11:12:19	ga_s2bm_ard_3-2-1_52KCF_2018-12-01_final.stac-item
2018-12-01 11:12:34	ga_s2bm_ard_3-2-1_52KCE_2018-12-01_final.stac-item
2018-12-01 11:12:48	ga_s2bm_ard_3-2-1_52KCD_2018-12-01_final.stac-item
2018-12-01 11:13:03	ga_s2bm_ard_3-2-1_52KCC_2018-12-01_final.stac-item
2018-12-01 11:13:09	ga_s2bm_ard_3-2-1_52KBC_2018-12-01_final.stac-item
2018-12-01 11:13:17	ga_s2bm_ard_3-2-1_52KCB_2018-12-01_final.stac-item
2018-12-01 11:13:21	ga_s2bm_ard_3-2-1_52KBB_2018-12-01_final.stac-item
2018-12-01 11:13:32	ga_s2bm_ard_3-2-1_52KCA_2018-12-01_final.stac-item
2018-12-01 11:13:35	ga_s2bm_ard_3-2-1_52KBA_2018-12-01_final.stac-item
2018-12-01 11:13:50	ga_s2bm_ard_3-2-1_52KBV_2018-12-01_final.stac-item
2018-12-01 11:14:03	ga_s2bm_ard_3-2-1_52JET_2018-12-01_final.stac-item
2018-12-01 11:14:04	ga_s2bm_ard_3-2-1_52KBU_2018-12-01_final.stac-item
2018-12-01 11:14:12	ga_s2bm_ard_3-2-1_52JDT_2018-12-01_final.stac-item
2018-12-01 11:14:16	ga_s2bm_ard_3-2-1_52JCT_2018-12-01_final.stac-item
2018-12-01 11:14:19	ga_s2bm_ard_3-2-1_51JZN_2018-12-01_final.stac-item
2018-12-01 11:14:19	ga_s2bm_ard_3-2-1_52JBT_2018-12-01_final.stac-item
2018-12-01 11:14:24	ga_s2bm_ard_3-2-1_51JYN_2018-12-01_final.stac-item
2018-12-01 11:14:27	ga_s2bm_ard_3-2-1_52JDS_2018-12-01_final.stac-item
2018-12-01 11:14:30	ga_s2bm_ard_3-2-1_52JCS_2018-12-01_final.stac-item
2018-12-01 11:14:33	ga_s2bm_ard_3-2-1_51JZM_2018-12-01_final.stac-item
2018-12-01 11:14:33	ga_s2bm_ard_3-2-1_52JBS_2018-12-01_final.stac-item
2018-12-01 11:14:37	ga_s2bm_ard_3-2-1_51JYM_2018-12-01_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