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
2023-05-18 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2023-05-18_final
2023-05-18 11:47:22	ga_s2bm_ard_3-2-1_50HPG_2023-05-18_final
2023-05-18 11:47:25	ga_s2bm_ard_3-2-1_50HNG_2023-05-18_final
2023-05-18 11:47:29	ga_s2bm_ard_3-2-1_50HMG_2023-05-18_final
2023-05-18 11:47:31	ga_s2bm_ard_3-2-1_50HLG_2023-05-18_final
2023-05-18 11:47:33	ga_s2bm_ard_3-2-1_50HPF_2023-05-18_nrt
2023-05-18 11:47:34	ga_s2bm_ard_3-2-1_50HNF_2023-05-18_nrt
2023-05-18 11:47:36	ga_s2bm_ard_3-2-1_50HMF_2023-05-18_nrt
2023-05-19 09:29:43	ga_s2bm_ard_3-2-1_56LPP_2023-05-18_nrt
2023-05-19 09:29:49	ga_s2bm_ard_3-2-1_56LPP_2023-05-18_nrt
2023-05-19 09:29:59	ga_s2bm_ard_3-2-1_56LPN_2023-05-18_nrt
2023-05-19 09:30:09	ga_s2bm_ard_3-2-1_56LPM_2023-05-19_nrt
2023-05-19 09:31:31	ga_s2bm_ard_3-2-1_56KPG_2023-05-19_nrt
2023-05-19 09:31:32	ga_s2bm_ard_3-2-1_56KNG_2023-05-19_nrt
2023-05-19 09:31:35	ga_s2bm_ard_3-2-1_56KPF_2023-05-19_nrt
2023-05-19 09:31:36	ga_s2bm_ard_3-2-1_56KNF_2023-05-19_nrt
2023-05-19 09:32:31	ga_s2bm_ard_3-2-1_56KPC_2023-05-19_final
2023-05-19 09:32:33	ga_s2bm_ard_3-2-1_56KNC_2023-05-19_nrt
2023-05-19 09:32:35	ga_s2bm_ard_3-2-1_56KMC_2023-05-19_nrt
2023-05-19 09:32:39	ga_s2bm_ard_3-2-1_56KPB_2023-05-19_final
2023-05-19 09:32:42	ga_s2bm_ard_3-2-1_56KNB_2023-05-19_final
2023-05-19 09:32:46	ga_s2bm_ard_3-2-1_56KMB_2023-05-19_final
2023-05-19 09:32:51	ga_s2bm_ard_3-2-1_56KLB_2023-05-19_final
2023-05-19 09:32:53	ga_s2bm_ard_3-2-1_56KPA_2023-05-19_nrt
2023-05-19 09:32:57	ga_s2bm_ard_3-2-1_56KNA_2023-05-19_final
2023-05-19 09:33:00	ga_s2bm_ard_3-2-1_56KMA_2023-05-19_final
2023-05-19 09:33:04	ga_s2bm_ard_3-2-1_56KLA_2023-05-19_final
2023-05-19 09:33:08	ga_s2bm_ard_3-2-1_56KPV_2023-05-19_nrt
2023-05-19 09:33:11	ga_s2bm_ard_3-2-1_56KNV_2023-05-19_nrt
2023-05-19 09:33:15	ga_s2bm_ard_3-2-1_56KMV_2023-05-19_nrt
2023-05-19 09:33:18	ga_s2bm_ard_3-2-1_56KLV_2023-05-19_final
2023-05-19 09:33:22	ga_s2bm_ard_3-2-1_56KPU_2023-05-19_nrt
2023-05-19 09:33:26	ga_s2bm_ard_3-2-1_56KNU_2023-05-19_nrt
2023-05-19 09:33:29	ga_s2bm_ard_3-2-1_56KMU_2023-05-19_final
2023-05-19 09:33:32	ga_s2bm_ard_3-2-1_56KLU_2023-05-19_final
2023-05-19 09:33:35	ga_s2bm_ard_3-2-1_56JPT_2023-05-19_nrt
2023-05-19 09:34:56	ga_s2bm_ard_3-2-1_56JMN_2023-05-19_final
2023-05-19 09:35:00	ga_s2bm_ard_3-2-1_56JLN_2023-05-19_final
2023-05-19 09:35:03	ga_s2bm_ard_3-2-1_56JKN_2023-05-19_final
2023-05-19 09:35:06	ga_s2bm_ard_3-2-1_55JGH_2023-05-19_final
2023-05-19 09:35:11	ga_s2bm_ard_3-2-1_56JMM_2023-05-19_final
2023-05-19 09:35:14	ga_s2bm_ard_3-2-1_56JLM_2023-05-19_final
2023-05-19 09:35:18	ga_s2bm_ard_3-2-1_56JKM_2023-05-19_final
2023-05-19 09:35:20	ga_s2bm_ard_3-2-1_55JGG_2023-05-19_final
2023-05-19 09:35:26	ga_s2bm_ard_3-2-1_56JML_2023-05-19_final
2023-05-19 09:35:29	ga_s2bm_ard_3-2-1_56JLL_2023-05-19_final
2023-05-19 09:35:32	ga_s2bm_ard_3-2-1_56JKL_2023-05-19_final
2023-05-19 09:35:35	ga_s2bm_ard_3-2-1_55JGF_2023-05-19_final
2023-05-19 09:35:40	ga_s2bm_ard_3-2-1_56HMK_2023-05-19_final
2023-05-19 09:35:44	ga_s2bm_ard_3-2-1_56HLK_2023-05-19_final
2023-05-19 09:35:47	ga_s2bm_ard_3-2-1_56HKK_2023-05-19_final
2023-05-19 09:35:49	ga_s2bm_ard_3-2-1_55HGE_2023-05-19_final
2023-05-19 09:35:53	ga_s2bm_ard_3-2-1_56HMJ_2023-05-19_final
2023-05-19 09:35:55	ga_s2bm_ard_3-2-1_55HFE_2023-05-19_final
2023-05-19 09:35:58	ga_s2bm_ard_3-2-1_56HLJ_2023-05-19_final
2023-05-19 09:36:01	ga_s2bm_ard_3-2-1_56HKJ_2023-05-19_final
2023-05-19 09:36:03	ga_s2bm_ard_3-2-1_56HMH_2023-05-19_nrt
2023-05-19 09:36:03	ga_s2bm_ard_3-2-1_55HGD_2023-05-19_final
2023-05-19 09:36:07	ga_s2bm_ard_3-2-1_55HFD_2023-05-19_final
2023-05-19 09:36:12	ga_s2bm_ard_3-2-1_56HLH_2023-05-19_final
2023-05-19 09:36:16	ga_s2bm_ard_3-2-1_56HKH_2023-05-19_final
2023-05-19 09:36:18	ga_s2bm_ard_3-2-1_55HGC_2023-05-19_final
2023-05-19 09:36:22	ga_s2bm_ard_3-2-1_55HFC_2023-05-19_final
2023-05-19 11:11:31	ga_s2bm_ard_3-2-1_52LGJ_2023-05-19_final
2023-05-19 11:11:35	ga_s2bm_ard_3-2-1_52LFJ_2023-05-19_final
2023-05-19 11:11:39	ga_s2bm_ard_3-2-1_52LEJ_2023-05-19_final
2023-05-19 11:11:42	ga_s2bm_ard_3-2-1_52LDJ_2023-05-19_final
2023-05-19 11:11:44	ga_s2bm_ard_3-2-1_52LGH_2023-05-19_final
2023-05-19 11:11:49	ga_s2bm_ard_3-2-1_52LFH_2023-05-19_final
2023-05-19 11:11:53	ga_s2bm_ard_3-2-1_52LEH_2023-05-19_final
2023-05-19 11:11:55	ga_s2bm_ard_3-2-1_52KGG_2023-05-19_final
2023-05-19 11:11:56	ga_s2bm_ard_3-2-1_52LDH_2023-05-19_final
2023-05-19 11:12:04	ga_s2bm_ard_3-2-1_52KFG_2023-05-19_final
2023-05-19 11:12:08	ga_s2bm_ard_3-2-1_52KEG_2023-05-19_final
2023-05-19 11:12:11	ga_s2bm_ard_3-2-1_52KDG_2023-05-19_final
2023-05-19 11:12:15	ga_s2bm_ard_3-2-1_52KCG_2023-05-19_final
2023-05-19 11:12:18	ga_s2bm_ard_3-2-1_52KFF_2023-05-19_final
2023-05-19 11:12:22	ga_s2bm_ard_3-2-1_52KEF_2023-05-19_final
2023-05-19 11:12:25	ga_s2bm_ard_3-2-1_52KDF_2023-05-19_final
2023-05-19 11:12:28	ga_s2bm_ard_3-2-1_52KCF_2023-05-19_final
2023-05-19 11:12:33	ga_s2bm_ard_3-2-1_52KFE_2023-05-19_final
2023-05-19 11:12:37	ga_s2bm_ard_3-2-1_52KEE_2023-05-19_final
2023-05-19 11:12:40	ga_s2bm_ard_3-2-1_52KDE_2023-05-19_final
2023-05-19 11:12:42	ga_s2bm_ard_3-2-1_52KCE_2023-05-19_final
2023-05-19 11:12:44	ga_s2bm_ard_3-2-1_52KFD_2023-05-19_final
2023-05-19 11:12:46	ga_s2bm_ard_3-2-1_52KED_2023-05-19_final
2023-05-19 11:12:47	ga_s2bm_ard_3-2-1_52KDE_2023-05-19_final
2023-05-19 11:12:48	ga_s2bm_ard_3-2-1_52KCE_2023-05-19_final
2023-05-19 11:12:49	ga_s2bm_ard_3-2-1_52KCD_2023-05-19_final
2023-05-19 11:12:50	ga_s2bm_ard_3-2-1_52KFD_2023-05-19_final
2023-05-19 11:12:52	ga_s2bm_ard_3-2-1_52KED_2023-05-19_final
2023-05-19 11:12:54	ga_s2bm_ard_3-2-1_52KDD_2023-05-19_final
2023-05-19 11:12:58	ga_s2bm_ard_3-2-1_52KCD_2023-05-19_final
2023-05-19 11:12:58	ga_s2bm_ard_3-2-1_52KFC_2023-05-19_final
2023-05-19 11:13:05	ga_s2bm_ard_3-2-1_52KEC_2023-05-19_final
2023-05-19 11:13:09	ga_s2bm_ard_3-2-1_52KDC_2023-05-19_final
2023-05-19 11:13:12	ga_s2bm_ard_3-2-1_52KCC_2023-05-19_final
2023-05-19 11:13:18	ga_s2bm_ard_3-2-1_52KBC_2023-05-19_final
2023-05-19 11:13:20	ga_s2bm_ard_3-2-1_52KEB_2023-05-19_final
2023-05-19 11:13:24	ga_s2bm_ard_3-2-1_52KDB_2023-05-19_final

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