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
2023-07-12 10:51:42	ga_s2bm_ard_3-2-1_53LLC_2023-07-12_final
2023-07-12 10:53:41	ga_s2bm_ard_3-2-1_53KMQ_2023-07-12_final
2023-07-12 10:54:02	ga_s2bm_ard_3-2-1_52KHU_2023-07-12_final
2023-07-12 10:54:22	ga_s2bm_ard_3-2-1_53JKN_2023-07-12_final
2023-07-12 10:55:29	ga_s2bm_ard_3-2-1_53JKH_2023-07-12_final
2023-07-12 10:55:47	ga_s2bm_ard_3-2-1_52JGM_2023-07-12_final
2023-07-13 10:19:42	ga_s2bm_ard_3-2-1_54LZQ_2023-07-13_final
2023-07-13 10:19:46	ga_s2bm_ard_3-2-1_54LYQ_2023-07-13_final
2023-07-13 10:19:57	ga_s2bm_ard_3-2-1_54LZP_2023-07-13_final
2023-07-13 10:20:11	ga_s2bm_ard_3-2-1_54LZN_2023-07-13_final
2023-07-13 10:21:37	ga_s2bm_ard_3-2-1_54LVH_2023-07-13_final
2023-07-13 10:22:06	ga_s2bm_ard_3-2-1_54KVF_2023-07-13_final
2023-07-13 10:22:28	ga_s2bm_ard_3-2-1_54KUE_2023-07-13_final
2023-07-13 10:23:42	ga_s2bm_ard_3-2-1_54KTV_2023-07-13_final
2023-07-13 10:24:25	ga_s2bm_ard_3-2-1_54JUS_2023-07-13_final
2023-07-13 10:24:35	ga_s2bm_ard_3-2-1_54JUR_2023-07-13_final
2023-07-13 10:25:15	ga_s2bm_ard_3-2-1_54JVN_2023-07-13_final
2023-07-13 10:25:33	ga_s2bm_ard_3-2-1_54JUM_2023-07-13_final
2023-07-13 10:27:17	ga_s2bm_ard_3-2-1_53HQV_2023-07-13_final
2023-07-13 12:04:26	ga_s2bm_ard_3-2-1_50KMU_2023-07-13_final
2023-07-13 12:04:33	ga_s2bm_ard_3-2-1_50KKU_2023-07-13_final
2023-07-13 12:05:01	ga_s2bm_ard_3-2-1_49JHM_2023-07-13_final
2023-07-13 12:05:48	ga_s2bm_ard_3-2-1_49JGJ_2023-07-13_final
2023-07-13 12:06:00	ga_s2bm_ard_3-2-1_50JKN_2023-07-13_final
2023-07-14 09:51:31	ga_s2bm_ard_3-2-1_55KHB_2023-07-14_final
2023-07-14 09:51:35	ga_s2bm_ard_3-2-1_55KGB_2023-07-14_final
2023-07-14 09:51:38	ga_s2bm_ard_3-2-1_55KFB_2023-07-14_final
2023-07-14 09:51:53	ga_s2bm_ard_3-2-1_55KFA_2023-07-14_final
2023-07-14 09:53:01	ga_s2bm_ard_3-2-1_55KGR_2023-07-14_final
2023-07-14 09:53:34	ga_s2bm_ard_3-2-1_55KFP_2023-07-14_final
2023-07-14 09:54:57	ga_s2bm_ard_3-2-1_55JCJ_2023-07-14_final
2023-07-14 09:55:19	ga_s2bm_ard_3-2-1_55JEG_2023-07-14_final
2023-07-14 09:56:21	ga_s2bm_ard_3-2-1_55HDC_2023-07-14_final
2023-07-14 09:56:27	ga_s2bm_ard_3-2-1_55HBC_2023-07-14_final
2023-07-14 09:57:08	ga_s2bm_ard_3-2-1_55HCV_2023-07-14_final
2023-07-14 09:57:13	ga_s2bm_ard_3-2-1_55HDU_2023-07-14_final
2023-07-14 09:57:31	ga_s2bm_ard_3-2-1_54HXD_2023-07-14_final
2023-07-14 09:57:56	ga_s2bm_ard_3-2-1_54HYB_2023-07-14_final
2023-07-14 09:58:24	ga_s2bm_ard_3-2-1_54GYV_2023-07-14_final
2023-07-14 11:31:29	ga_s2bm_ard_3-2-1_51LYE_2023-07-14_final
2023-07-14 11:31:58	ga_s2bm_ard_3-2-1_51LYC_2023-07-14_final
2023-07-14 11:32:46	ga_s2bm_ard_3-2-1_51KVV_2023-07-14_final
2023-07-14 11:35:20	ga_s2bm_ard_3-2-1_51JUK_2023-07-14_final
2023-07-14 11:35:38	ga_s2bm_ard_3-2-1_51JTJ_2023-07-14_final
2023-07-14 11:36:57	ga_s2bm_ard_3-2-1_50HPJ_2023-07-14_final
2023-07-14 11:37:02	ga_s2bm_ard_3-2-1_51HUC_2023-07-14_final
2023-07-14 11:37:20	ga_s2bm_ard_3-2-1_51HTB_2023-07-14_final
2023-07-15 09:27:06	ga_s2bm_ard_3-2-1_55HGV_2023-07-14_final
2023-08-03 11:30:46	ga_s2bm_ard_3-2-1_51LYH_2023-08-03_nrt
2023-08-03 11:30:56	ga_s2bm_ard_3-2-1_51LZG_2023-08-03_nrt
2023-08-03 11:31:00	ga_s2bm_ard_3-2-1_51LYG_2023-08-03_nrt
2023-08-03 11:31:11	ga_s2bm_ard_3-2-1_51LZF_2023-08-03_nrt
2023-08-03 11:31:15	ga_s2bm_ard_3-2-1_51LYF_2023-08-03_nrt
2023-08-03 11:31:22	ga_s2bm_ard_3-2-1_51LWF_2023-08-03_nrt
2023-08-03 11:31:50	ga_s2bm_ard_3-2-1_51LWD_2023-08-03_nrt
2023-08-03 11:37:32	ga_s2bm_ard_3-2-1_51HTA_2023-08-03_nrt
2023-08-03 11:37:37	ga_s2bm_ard_3-2-1_50HNF_2023-08-03_nrt
2023-08-04 09:22:58	ga_s2bm_ard_3-2-1_56KPA_2023-08-03_nrt
2023-08-04 09:23:12	ga_s2bm_ard_3-2-1_56KPV_2023-08-03_nrt
2023-08-04 09:23:27	ga_s2bm_ard_3-2-1_56KPU_2023-08-03_nrt
2023-08-04 09:23:31	ga_s2bm_ard_3-2-1_56KNU_2023-08-03_nrt
2023-08-04 09:23:41	ga_s2bm_ard_3-2-1_56JPT_2023-08-03_nrt
2023-08-04 09:24:10	ga_s2bm_ard_3-2-1_56JPR_2023-08-03_nrt
2023-08-04 09:24:25	ga_s2bm_ard_3-2-1_56JPQ_2023-08-03_nrt
2023-08-04 09:24:39	ga_s2bm_ard_3-2-1_56JPP_2023-08-03_nrt
2023-08-04 09:24:54	ga_s2bm_ard_3-2-1_56JPN_2023-08-03_nrt
2023-08-04 09:25:08	ga_s2bm_ard_3-2-1_56JPM_2023-08-03_nrt
2023-08-04 09:25:22	ga_s2bm_ard_3-2-1_56JPL_2023-08-03_nrt
2023-08-04 09:26:10	ga_s2bm_ard_3-2-1_56HNH_2023-08-03_nrt
2023-08-04 09:26:13	ga_s2bm_ard_3-2-1_56HMH_2023-08-03_nrt
2023-08-04 09:26:24	ga_s2bm_ard_3-2-1_56HNG_2023-08-03_nrt
2023-08-04 09:26:28	ga_s2bm_ard_3-2-1_56HMG_2023-08-03_nrt
2023-08-04 09:26:38	ga_s2bm_ard_3-2-1_56HNF_2023-08-03_nrt
2023-08-04 09:26:42	ga_s2bm_ard_3-2-1_56HMF_2023-08-03_nrt
2023-08-04 09:26:46	ga_s2bm_ard_3-2-1_56HLF_2023-08-03_nrt
2023-08-04 09:26:57	ga_s2bm_ard_3-2-1_56HME_2023-08-03_nrt
2023-08-04 09:27:00	ga_s2bm_ard_3-2-1_56HLE_2023-08-03_nrt
2023-08-04 09:27:11	ga_s2bm_ard_3-2-1_56HMD_2023-08-03_nrt
2023-08-04 09:27:15	ga_s2bm_ard_3-2-1_56HLD_2023-08-03_nrt
2023-08-04 09:27:26	ga_s2bm_ard_3-2-1_56HMC_2023-08-03_nrt
2023-08-04 09:27:29	ga_s2bm_ard_3-2-1_56HLC_2023-08-03_nrt
2023-08-04 09:27:33	ga_s2bm_ard_3-2-1_55HGT_2023-08-03_nrt
2023-08-04 09:27:40	ga_s2bm_ard_3-2-1_56HMB_2023-08-03_nrt
2023-08-04 09:27:44	ga_s2bm_ard_3-2-1_56HLB_2023-08-03_nrt
2023-08-04 09:27:48	ga_s2bm_ard_3-2-1_55HGS_2023-08-03_nrt
2023-08-04 09:27:58	ga_s2bm_ard_3-2-1_56GLA_2023-08-03_nrt
2023-08-04 09:28:02	ga_s2bm_ard_3-2-1_56GKA_2023-08-03_nrt
2023-08-04 09:28:02	ga_s2bm_ard_3-2-1_55GGR_2023-08-03_nrt
2023-08-04 09:28:16	ga_s2bm_ard_3-2-1_56GKV_2023-08-03_nrt
2023-08-04 09:28:16	ga_s2bm_ard_3-2-1_55GGQ_2023-08-03_nrt
2023-08-04 09:28:31	ga_s2bm_ard_3-2-1_55GGP_2023-08-03_nrt
2023-08-04 09:28:31	ga_s2bm_ard_3-2-1_56GKU_2023-08-03_nrt
2023-08-04 09:28:42	ga_s2bm_ard_3-2-1_56GLT_2023-08-03_nrt
2023-08-04 09:28:45	ga_s2bm_ard_3-2-1_55GGN_2023-08-03_nrt
2023-08-04 09:28:56	ga_s2bm_ard_3-2-1_56GLS_2023-08-03_nrt
2023-08-04 09:28:59	ga_s2bm_ard_3-2-1_55GGM_2023-08-03_nrt
2023-08-04 09:29:01	ga_s2bm_ard_3-2-1_55GFM_2023-08-03_nrt
2023-08-04 11:00:15	ga_s2bm_ard_3-2-1_53LLJ_2023-08-04_nrt
2023-08-04 11:06:35	ga_s2bm_ard_3-2-1_52HDJ_2023-08-04_nrt
2023-08-04 11:06:36	ga_s2bm_ard_3-2-1_52HCJ_2023-08-04_nrt

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