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
2023-08-15 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2023-08-15_final
2023-08-15 12:14:32	ga_s2bm_ard_3-2-1_49KGP_2023-08-15_final
2023-08-15 12:14:36	ga_s2bm_ard_3-2-1_49KFP_2023-08-15_nrt
2023-08-15 12:14:36	ga_s2bm_ard_3-2-1_49JHN_2023-08-15_final
2023-08-15 12:14:47	ga_s2bm_ard_3-2-1_49JGN_2023-08-15_final
2023-08-15 12:14:51	ga_s2bm_ard_3-2-1_49JFN_2023-08-15_final
2023-08-15 12:15:02	ga_s2bm_ard_3-2-1_49JGM_2023-08-15_final
2023-08-15 12:15:05	ga_s2bm_ard_3-2-1_49JFM_2023-08-15_final
2023-08-15 12:15:16	ga_s2bm_ard_3-2-1_49JGL_2023-08-15_final
2023-08-15 12:15:19	ga_s2bm_ard_3-2-1_49JFL_2023-08-15_nrt
2023-08-15 12:15:24	ga_s2bm_ard_3-2-1_49JGK_2023-08-15_final
2023-08-15 12:15:26	ga_s2bm_ard_3-2-1_49JFK_2023-08-15_nrt
2023-08-16 08:24:32	ga_s2bm_ard_3-2-1_59JKH_2023-08-15_final
2023-08-16 08:24:33	ga_s2bm_ard_3-2-1_58JGN_2023-08-15_final
2023-08-16 08:31:47	ga_s2bm_ard_3-2-1_57FVV_2023-08-15_final
2023-08-16 09:59:44	ga_s2bm_ard_3-2-1_55LHJ_2023-08-16_nrt
2023-08-16 09:59:49	ga_s2bm_ard_3-2-1_55LGJ_2023-08-16_nrt
2023-08-16 09:59:53	ga_s2bm_ard_3-2-1_55LFJ_2023-08-16_nrt
2023-08-16 09:59:54	ga_s2bm_ard_3-2-1_55LHH_2023-08-16_nrt
2023-08-16 09:59:56	ga_s2bm_ard_3-2-1_55LEJ_2023-08-16_nrt
2023-08-16 10:00:03	ga_s2bm_ard_3-2-1_55LGH_2023-08-16_nrt
2023-08-16 10:00:07	ga_s2bm_ard_3-2-1_55LFH_2023-08-16_nrt
2023-08-16 10:00:10	ga_s2bm_ard_3-2-1_55LEH_2023-08-16_nrt
2023-08-16 10:00:14	ga_s2bm_ard_3-2-1_55LDH_2023-08-16_nrt
2023-08-16 10:00:18	ga_s2bm_ard_3-2-1_55LGG_2023-08-16_nrt
2023-08-16 10:00:22	ga_s2bm_ard_3-2-1_55LFG_2023-08-16_nrt
2023-08-16 10:00:25	ga_s2bm_ard_3-2-1_55LEG_2023-08-16_nrt
2023-08-16 10:00:28	ga_s2bm_ard_3-2-1_55LDG_2023-08-16_nrt
2023-08-16 10:00:33	ga_s2bm_ard_3-2-1_55LGF_2023-08-16_nrt
2023-08-16 10:00:36	ga_s2bm_ard_3-2-1_55LFF_2023-08-16_nrt
2023-08-16 10:00:40	ga_s2bm_ard_3-2-1_55LEF_2023-08-16_nrt
2023-08-16 10:00:43	ga_s2bm_ard_3-2-1_55LDF_2023-08-16_nrt
2023-08-16 10:00:46	ga_s2bm_ard_3-2-1_55LGE_2023-08-16_nrt
2023-08-16 10:00:51	ga_s2bm_ard_3-2-1_55LFE_2023-08-16_nrt
2023-08-16 10:00:54	ga_s2bm_ard_3-2-1_55LEE_2023-08-16_nrt
2023-08-16 10:00:57	ga_s2bm_ard_3-2-1_55LGD_2023-08-16_nrt
2023-08-16 10:00:57	ga_s2bm_ard_3-2-1_55LDE_2023-08-16_nrt
2023-08-16 10:01:05	ga_s2bm_ard_3-2-1_55LFD_2023-08-16_nrt
2023-08-16 10:01:09	ga_s2bm_ard_3-2-1_55LED_2023-08-16_nrt
2023-08-16 10:01:17	ga_s2bm_ard_3-2-1_55LCD_2023-08-16_final
2023-08-16 10:01:19	ga_s2bm_ard_3-2-1_55LFC_2023-08-16_final
2023-08-16 10:01:23	ga_s2bm_ard_3-2-1_55LEC_2023-08-16_final
2023-08-16 10:01:26	ga_s2bm_ard_3-2-1_55LDC_2023-08-16_nrt
2023-08-16 10:01:30	ga_s2bm_ard_3-2-1_55LCC_2023-08-16_final
2023-08-16 10:01:34	ga_s2bm_ard_3-2-1_55KFB_2023-08-16_final
2023-08-16 10:01:38	ga_s2bm_ard_3-2-1_55KEB_2023-08-16_final
2023-08-16 10:01:41	ga_s2bm_ard_3-2-1_55KDB_2023-08-16_final
2023-08-16 10:01:44	ga_s2bm_ard_3-2-1_55KCB_2023-08-16_final
2023-08-16 10:01:48	ga_s2bm_ard_3-2-1_55KFA_2023-08-16_final
2023-08-16 10:01:52	ga_s2bm_ard_3-2-1_55KEA_2023-08-16_nrt
2023-08-16 10:01:55	ga_s2bm_ard_3-2-1_55KDA_2023-08-16_final
2023-08-16 10:01:59	ga_s2bm_ard_3-2-1_55KCA_2023-08-16_final
2023-08-16 10:02:00	ga_s2bm_ard_3-2-1_55KFV_2023-08-16_nrt
2023-08-16 10:02:06	ga_s2bm_ard_3-2-1_55KEV_2023-08-16_final
2023-08-16 10:02:10	ga_s2bm_ard_3-2-1_55KDV_2023-08-16_final
2023-08-16 10:02:13	ga_s2bm_ard_3-2-1_55KCV_2023-08-16_final
2023-08-16 10:02:20	ga_s2bm_ard_3-2-1_55KBV_2023-08-16_final
2023-08-16 10:02:21	ga_s2bm_ard_3-2-1_55KEU_2023-08-16_final
2023-08-16 10:02:25	ga_s2bm_ard_3-2-1_55KDU_2023-08-16_final
2023-08-16 10:02:28	ga_s2bm_ard_3-2-1_55KCU_2023-08-16_final
2023-08-16 10:02:31	ga_s2bm_ard_3-2-1_55KBU_2023-08-16_final
2023-08-16 10:02:36	ga_s2bm_ard_3-2-1_55KET_2023-08-16_final
2023-08-16 10:02:39	ga_s2bm_ard_3-2-1_55KDT_2023-08-16_final
2023-08-16 10:02:42	ga_s2bm_ard_3-2-1_55KCT_2023-08-16_final
2023-08-16 10:02:45	ga_s2bm_ard_3-2-1_55KBT_2023-08-16_final
2023-08-16 11:41:56	ga_s2bm_ard_3-2-1_51LTD_2023-08-16_nrt
2023-08-16 11:42:01	ga_s2bm_ard_3-2-1_51LWC_2023-08-16_final
2023-08-16 11:42:04	ga_s2bm_ard_3-2-1_51LVC_2023-08-16_final
2023-08-16 11:42:10	ga_s2bm_ard_3-2-1_51LTC_2023-08-16_nrt
2023-08-16 11:42:13	ga_s2bm_ard_3-2-1_50LRH_2023-08-16_nrt
2023-08-16 11:42:25	ga_s2bm_ard_3-2-1_51KTB_2023-08-16_nrt
2023-08-16 11:42:26	ga_s2bm_ard_3-2-1_50KRG_2023-08-16_nrt
2023-08-16 11:42:40	ga_s2bm_ard_3-2-1_50KRF_2023-08-16_nrt
2023-08-16 11:42:54	ga_s2bm_ard_3-2-1_51KTV_2023-08-16_nrt
2023-08-16 11:42:55	ga_s2bm_ard_3-2-1_50KRE_2023-08-16_nrt
2023-08-16 11:43:06	ga_s2bm_ard_3-2-1_51KUU_2023-08-16_final
2023-08-16 11:43:15	ga_s2bm_ard_3-2-1_51KUT_2023-08-16_final
2023-08-16 11:43:22	ga_s2bm_ard_3-2-1_51KUT_2023-08-16_final
2023-08-16 11:43:35	ga_s2bm_ard_3-2-1_51KUS_2023-08-16_final
2023-08-16 11:46:28	ga_s2bm_ard_3-2-1_50JNL_2023-08-16_final
2023-08-16 11:46:31	ga_s2bm_ard_3-2-1_50JML_2023-08-16_final
2023-08-16 11:46:35	ga_s2bm_ard_3-2-1_50HQK_2023-08-16_final
2023-08-16 11:46:39	ga_s2bm_ard_3-2-1_50HPK_2023-08-16_final
2023-08-16 11:46:43	ga_s2bm_ard_3-2-1_50HNK_2023-08-16_final
2023-08-16 11:46:46	ga_s2bm_ard_3-2-1_50HMK_2023-08-16_final
2023-08-16 11:46:48	ga_s2bm_ard_3-2-1_50HQJ_2023-08-16_final
2023-08-16 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2023-08-16_final
2023-08-16 11:46:57	ga_s2bm_ard_3-2-1_50HNJ_2023-08-16_final
2023-08-16 11:46:59	ga_s2bm_ard_3-2-1_50HQH_2023-08-16_final
2023-08-16 11:47:01	ga_s2bm_ard_3-2-1_50HMJ_2023-08-16_final
2023-08-16 11:47:08	ga_s2bm_ard_3-2-1_50HPH_2023-08-16_final
2023-08-16 11:47:12	ga_s2bm_ard_3-2-1_50HNH_2023-08-16_final
2023-08-16 11:47:15	ga_s2bm_ard_3-2-1_50HMH_2023-08-16_final
2023-08-16 11:47:20	ga_s2bm_ard_3-2-1_50HLH_2023-08-16_final
2023-08-16 11:47:22	ga_s2bm_ard_3-2-1_50HPG_2023-08-16_final
2023-08-16 11:47:26	ga_s2bm_ard_3-2-1_50HNG_2023-08-16_final
2023-08-16 11:47:30	ga_s2bm_ard_3-2-1_50HMG_2023-08-16_final
2023-08-16 11:47:32	ga_s2bm_ard_3-2-1_50HLG_2023-08-16_final
2023-08-16 11:47:34	ga_s2bm_ard_3-2-1_50HPF_2023-08-16_nrt
2023-08-16 11:47:35	ga_s2bm_ard_3-2-1_50HNF_2023-08-16_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