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
2023-12-02 11:00:55	ga_s2bm_ard_3-2-1_53LME_2023-12-02_final
2023-12-02 11:00:56	ga_s2bm_ard_3-2-1_52LHL_2023-12-02_final
2023-12-02 11:00:59	ga_s2bm_ard_3-2-1_52LGL_2023-12-02_final
2023-12-02 11:01:06	ga_s2bm_ard_3-2-1_53LLE_2023-12-02_final
2023-12-02 11:01:10	ga_s2bm_ard_3-2-1_53LKE_2023-12-02_final
2023-12-02 11:01:11	ga_s2bm_ard_3-2-1_52LHK_2023-12-02_final
2023-12-02 11:01:14	ga_s2bm_ard_3-2-1_52LGK_2023-12-02_final
2023-12-02 11:01:21	ga_s2bm_ard_3-2-1_53LLD_2023-12-02_final
2023-12-02 11:01:24	ga_s2bm_ard_3-2-1_53LKD_2023-12-02_final
2023-12-02 11:01:25	ga_s2bm_ard_3-2-1_52LHJ_2023-12-02_final
2023-12-02 11:01:29	ga_s2bm_ard_3-2-1_52LGJ_2023-12-02_final
2023-12-02 11:01:35	ga_s2bm_ard_3-2-1_53LLC_2023-12-02_final
2023-12-02 11:01:36	ga_s2bm_ard_3-2-1_52LFJ_2023-12-02_final
2023-12-02 11:01:39	ga_s2bm_ard_3-2-1_53LKC_2023-12-02_final
2023-12-02 11:01:40	ga_s2bm_ard_3-2-1_52LHH_2023-12-02_final
2023-12-02 11:01:43	ga_s2bm_ard_3-2-1_52LGH_2023-12-02_final
2023-12-02 11:01:47	ga_s2bm_ard_3-2-1_52LFH_2023-12-02_final
2023-12-02 11:01:49	ga_s2bm_ard_3-2-1_53KLB_2023-12-02_final
2023-12-02 11:01:53	ga_s2bm_ard_3-2-1_53KKB_2023-12-02_final
2023-12-02 11:01:54	ga_s2bm_ard_3-2-1_52KHG_2023-12-02_final
2023-12-02 11:01:58	ga_s2bm_ard_3-2-1_52KGG_2023-12-02_final
2023-12-02 11:02:00	ga_s2bm_ard_3-2-1_53KLA_2023-12-02_final
2023-12-02 11:02:01	ga_s2bm_ard_3-2-1_52KFG_2023-12-02_final
2023-12-02 11:02:07	ga_s2bm_ard_3-2-1_53KKA_2023-12-02_final
2023-12-02 11:02:09	ga_s2bm_ard_3-2-1_52KHF_2023-12-02_final
2023-12-02 11:02:12	ga_s2bm_ard_3-2-1_52KGF_2023-12-02_final
2023-12-02 11:02:15	ga_s2bm_ard_3-2-1_52KFF_2023-12-02_final
2023-12-02 11:02:22	ga_s2bm_ard_3-2-1_53KKV_2023-12-02_final
2023-12-02 11:02:23	ga_s2bm_ard_3-2-1_52KHE_2023-12-02_final
2023-12-02 11:02:27	ga_s2bm_ard_3-2-1_52KGE_2023-12-02_final
2023-12-02 11:02:30	ga_s2bm_ard_3-2-1_52KFE_2023-12-02_final
2023-12-02 11:02:37	ga_s2bm_ard_3-2-1_53KKU_2023-12-02_final
2023-12-02 11:02:37	ga_s2bm_ard_3-2-1_52KHD_2023-12-02_final
2023-12-02 11:02:41	ga_s2bm_ard_3-2-1_52KGD_2023-12-02_final
2023-12-02 11:02:43	ga_s2bm_ard_3-2-1_52KFD_2023-12-02_final
2023-12-02 11:02:46	ga_s2bm_ard_3-2-1_52KED_2023-12-02_final
2023-12-02 11:02:47	ga_s2bm_ard_3-2-1_52KHC_2023-12-02_final
2023-12-02 11:02:47	ga_s2bm_ard_3-2-1_53KKT_2023-12-02_final
2023-12-02 11:02:48	ga_s2bm_ard_3-2-1_52KGD_2023-12-02_final
2023-12-02 11:02:48	ga_s2bm_ard_3-2-1_52KGC_2023-12-02_final
2023-12-02 11:02:50	ga_s2bm_ard_3-2-1_52KFC_2023-12-02_final
2023-12-02 11:02:50	ga_s2bm_ard_3-2-1_52KFD_2023-12-02_final
2023-12-02 11:02:52	ga_s2bm_ard_3-2-1_52KED_2023-12-02_final
2023-12-02 11:02:53	ga_s2bm_ard_3-2-1_53KKT_2023-12-02_final
2023-12-02 11:02:53	ga_s2bm_ard_3-2-1_52KHC_2023-12-02_final
2023-12-02 11:02:56	ga_s2bm_ard_3-2-1_52KGC_2023-12-02_final
2023-12-02 11:02:59	ga_s2bm_ard_3-2-1_52KFC_2023-12-02_final
2023-12-02 11:03:02	ga_s2bm_ard_3-2-1_52KEC_2023-12-02_final
2023-12-02 11:03:05	ga_s2bm_ard_3-2-1_53KKS_2023-12-02_final
2023-12-02 11:03:06	ga_s2bm_ard_3-2-1_52KHB_2023-12-02_final
2023-12-02 11:03:10	ga_s2bm_ard_3-2-1_52KGB_2023-12-02_final
2023-12-02 11:03:14	ga_s2bm_ard_3-2-1_52KFB_2023-12-02_final
2023-12-02 11:03:16	ga_s2bm_ard_3-2-1_53KKR_2023-12-02_final
2023-12-02 11:03:17	ga_s2bm_ard_3-2-1_52KEB_2023-12-02_final
2023-12-02 11:03:20	ga_s2bm_ard_3-2-1_52KHA_2023-12-02_final
2023-12-02 11:03:24	ga_s2bm_ard_3-2-1_52KGA_2023-12-02_final
2023-12-02 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2023-12-02_final
2023-12-02 11:03:30	ga_s2bm_ard_3-2-1_52KHV_2023-12-02_final
2023-12-02 11:03:32	ga_s2bm_ard_3-2-1_52KEA_2023-12-02_final
2023-12-02 11:03:39	ga_s2bm_ard_3-2-1_52KGV_2023-12-02_final
2023-12-02 11:03:43	ga_s2bm_ard_3-2-1_52KFV_2023-12-02_final
2023-12-02 11:03:46	ga_s2bm_ard_3-2-1_52KEV_2023-12-02_final
2023-12-02 11:03:51	ga_s2bm_ard_3-2-1_52KDV_2023-12-02_final
2023-12-02 11:03:53	ga_s2bm_ard_3-2-1_52KGU_2023-12-02_final
2023-12-02 11:03:57	ga_s2bm_ard_3-2-1_52KFU_2023-12-02_final
2023-12-02 11:04:00	ga_s2bm_ard_3-2-1_52KEU_2023-12-02_final
2023-12-02 11:04:04	ga_s2bm_ard_3-2-1_52KDU_2023-12-02_final
2023-12-02 11:04:08	ga_s2bm_ard_3-2-1_52JGT_2023-12-02_final
2023-12-02 11:04:12	ga_s2bm_ard_3-2-1_52JFT_2023-12-02_final
2023-12-02 11:04:15	ga_s2bm_ard_3-2-1_52JET_2023-12-02_final
2023-12-02 11:04:18	ga_s2bm_ard_3-2-1_52JDT_2023-12-02_final
2023-12-02 11:04:21	ga_s2bm_ard_3-2-1_52JGS_2023-12-02_final
2023-12-02 11:04:26	ga_s2bm_ard_3-2-1_52JFS_2023-12-02_final
2023-12-02 11:04:30	ga_s2bm_ard_3-2-1_52JES_2023-12-02_final
2023-12-02 11:04:33	ga_s2bm_ard_3-2-1_52JGR_2023-12-02_final
2023-12-02 11:04:33	ga_s2bm_ard_3-2-1_52JDS_2023-12-02_final
2023-12-02 11:04:40	ga_s2bm_ard_3-2-1_52JFR_2023-12-02_final
2023-12-02 11:04:44	ga_s2bm_ard_3-2-1_52JER_2023-12-02_final
2023-12-02 11:04:47	ga_s2bm_ard_3-2-1_52JDR_2023-12-02_final
2023-12-02 11:04:53	ga_s2bm_ard_3-2-1_52JCR_2023-12-02_final
2023-12-02 11:04:55	ga_s2bm_ard_3-2-1_52JFQ_2023-12-02_final
2023-12-02 11:04:59	ga_s2bm_ard_3-2-1_52JEQ_2023-12-02_final
2023-12-02 11:05:02	ga_s2bm_ard_3-2-1_52JDQ_2023-12-02_final
2023-12-02 11:05:05	ga_s2bm_ard_3-2-1_52JCQ_2023-12-02_final
2023-12-02 11:05:10	ga_s2bm_ard_3-2-1_52JFP_2023-12-02_final
2023-12-02 11:05:13	ga_s2bm_ard_3-2-1_52JEP_2023-12-02_final
2023-12-02 11:05:17	ga_s2bm_ard_3-2-1_52JDP_2023-12-02_final
2023-12-02 11:05:20	ga_s2bm_ard_3-2-1_52JCP_2023-12-02_final
2023-12-02 11:05:23	ga_s2bm_ard_3-2-1_52JFN_2023-12-02_final
2023-12-02 11:05:28	ga_s2bm_ard_3-2-1_52JEN_2023-12-02_final
2023-12-02 11:05:31	ga_s2bm_ard_3-2-1_52JDN_2023-12-02_final
2023-12-02 11:05:34	ga_s2bm_ard_3-2-1_52JCN_2023-12-02_final
2023-12-03 10:33:29	ga_s2bm_ard_3-2-1_54KUV_2023-12-03_final
2023-12-03 10:33:35	ga_s2bm_ard_3-2-1_53KPQ_2023-12-03_final
2023-12-03 10:33:38	ga_s2bm_ard_3-2-1_54KUU_2023-12-03_final
2023-12-03 10:33:50	ga_s2bm_ard_3-2-1_53KPP_2023-12-03_final
2023-12-03 10:33:57	ga_s2bm_ard_3-2-1_53JRN_2023-12-03_final
2023-12-03 10:34:01	ga_s2bm_ard_3-2-1_53JQN_2023-12-03_final
2023-12-03 10:34:15	ga_s2bm_ard_3-2-1_53JQM_2023-12-03_final
2023-12-03 10:34:22	ga_s2bm_ard_3-2-1_53JNM_2023-12-03_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