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
2023-06-01 11:21:25	ga_s2bm_ard_3-2-1_52LCK_2023-06-01_final
2023-06-01 11:21:58	ga_s2bm_ard_3-2-1_51LZC_2023-06-01_final
2023-06-01 11:22:11	ga_s2bm_ard_3-2-1_52KBG_2023-06-01_final
2023-06-01 11:22:12	ga_s2bm_ard_3-2-1_51KZB_2023-06-01_final
2023-06-01 11:22:16	ga_s2bm_ard_3-2-1_51KYB_2023-06-01_final
2023-06-01 11:22:37	ga_s2bm_ard_3-2-1_52KCE_2023-06-01_final
2023-06-01 11:22:52	ga_s2bm_ard_3-2-1_52KCD_2023-06-01_final
2023-06-01 11:22:56	ga_s2bm_ard_3-2-1_51KZU_2023-06-01_final
2023-06-01 11:23:39	ga_s2bm_ard_3-2-1_52KBA_2023-06-01_final
2023-06-01 11:23:46	ga_s2bm_ard_3-2-1_51KXR_2023-06-01_final
2023-06-01 11:24:26	ga_s2bm_ard_3-2-1_51JYN_2023-06-01_final
2023-06-01 11:24:41	ga_s2bm_ard_3-2-1_51JYM_2023-06-01_final
2023-06-01 11:25:35	ga_s2bm_ard_3-2-1_51JVJ_2023-06-01_final
2023-06-01 11:25:49	ga_s2bm_ard_3-2-1_51JYG_2023-06-01_final
2023-06-01 11:26:26	ga_s2bm_ard_3-2-1_51HXE_2023-06-01_final
2023-06-01 11:26:33	ga_s2bm_ard_3-2-1_51HVE_2023-06-01_final
2023-06-01 11:27:11	ga_s2bm_ard_3-2-1_51HWB_2023-06-01_final
2023-06-01 11:27:13	ga_s2bm_ard_3-2-1_51HVB_2023-06-01_final
2023-06-02 10:52:19	ga_s2bm_ard_3-2-1_53KKA_2023-06-02_final
2023-06-02 10:52:23	ga_s2bm_ard_3-2-1_52KHF_2023-06-02_final
2023-06-02 10:52:45	ga_s2bm_ard_3-2-1_53KLU_2023-06-02_final
2023-06-02 10:52:48	ga_s2bm_ard_3-2-1_53KKU_2023-06-02_final
2023-06-02 10:52:49	ga_s2bm_ard_3-2-1_53KNT_2023-06-02_final
2023-06-02 10:52:59	ga_s2bm_ard_3-2-1_53KLT_2023-06-02_final
2023-06-02 10:53:03	ga_s2bm_ard_3-2-1_53KKT_2023-06-02_final
2023-06-02 10:53:10	ga_s2bm_ard_3-2-1_53KMS_2023-06-02_final
2023-06-02 10:53:14	ga_s2bm_ard_3-2-1_53KLS_2023-06-02_final
2023-06-02 10:53:18	ga_s2bm_ard_3-2-1_52KHB_2023-06-02_final
2023-06-02 10:54:55	ga_s2bm_ard_3-2-1_53JLK_2023-06-02_final
2023-06-02 10:54:59	ga_s2bm_ard_3-2-1_53JKK_2023-06-02_final
2023-06-02 10:55:35	ga_s2bm_ard_3-2-1_52JFN_2023-06-02_final
2023-06-02 10:55:46	ga_s2bm_ard_3-2-1_52JGM_2023-06-02_final
2023-06-02 10:56:00	ga_s2bm_ard_3-2-1_52JGL_2023-06-02_final
2023-06-02 10:56:24	ga_s2bm_ard_3-2-1_52HDK_2023-06-02_final
2023-06-03 10:25:38	ga_s2bm_ard_3-2-1_53JQG_2023-06-03_final
2023-06-03 10:25:53	ga_s2bm_ard_3-2-1_53JQF_2023-06-03_final
2023-06-03 10:26:07	ga_s2bm_ard_3-2-1_53HQE_2023-06-03_final
2023-06-03 10:26:26	ga_s2bm_ard_3-2-1_53HPD_2023-06-03_final
2023-06-03 10:26:58	ga_s2bm_ard_3-2-1_53HNB_2023-06-03_final
2023-06-03 12:04:17	ga_s2bm_ard_3-2-1_49KHQ_2023-06-03_final
2023-06-03 12:04:28	ga_s2bm_ard_3-2-1_50KLU_2023-06-03_final
2023-06-03 12:04:33	ga_s2bm_ard_3-2-1_50KMU_2023-06-03_final
2023-06-03 12:04:36	ga_s2bm_ard_3-2-1_50KKU_2023-06-03_final
2023-06-03 12:04:46	ga_s2bm_ard_3-2-1_49JHN_2023-06-03_final
2023-06-03 12:04:58	ga_s2bm_ard_3-2-1_50JLS_2023-06-03_final
2023-06-03 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2023-06-03_final
2023-06-03 12:05:19	ga_s2bm_ard_3-2-1_49JGL_2023-06-03_final
2023-06-03 12:05:27	ga_s2bm_ard_3-2-1_50JLQ_2023-06-03_final
2023-06-03 12:06:14	ga_s2bm_ard_3-2-1_50JKM_2023-06-03_final
2023-06-03 12:06:18	ga_s2bm_ard_3-2-1_50JLL_2023-06-03_final
2023-06-04 11:32:12	ga_s2bm_ard_3-2-1_51KYB_2023-06-04_final
2023-06-04 11:32:30	ga_s2bm_ard_3-2-1_51KXA_2023-06-04_final
2023-06-04 11:35:20	ga_s2bm_ard_3-2-1_51JUK_2023-06-04_final
2023-06-04 11:35:31	ga_s2bm_ard_3-2-1_51JVJ_2023-06-04_final
2023-06-04 11:35:34	ga_s2bm_ard_3-2-1_51JUJ_2023-06-04_final
2023-06-04 11:35:45	ga_s2bm_ard_3-2-1_51JVH_2023-06-04_final
2023-06-04 11:36:09	ga_s2bm_ard_3-2-1_50JQM_2023-06-04_final
2023-06-04 11:36:30	ga_s2bm_ard_3-2-1_50JPL_2023-06-04_final
2023-06-04 11:37:30	ga_s2bm_ard_3-2-1_50HNG_2023-06-04_final
2023-06-05 11:00:35	ga_s2bm_ard_3-2-1_52LHN_2023-06-05_final
2023-06-05 11:00:41	ga_s2bm_ard_3-2-1_52LGN_2023-06-05_final
2023-06-05 11:00:53	ga_s2bm_ard_3-2-1_52LGM_2023-06-05_final
2023-06-05 11:01:46	ga_s2bm_ard_3-2-1_53LKC_2023-06-05_final
2023-06-05 11:02:01	ga_s2bm_ard_3-2-1_52KHG_2023-06-05_final
2023-06-05 11:02:15	ga_s2bm_ard_3-2-1_53KKA_2023-06-05_final
2023-06-05 11:02:16	ga_s2bm_ard_3-2-1_52KHF_2023-06-05_final
2023-06-05 11:02:39	ga_s2bm_ard_3-2-1_53KKU_2023-06-05_final
2023-06-05 11:02:46	ga_s2bm_ard_3-2-1_53KKU_2023-06-05_final
2023-06-05 11:02:58	ga_s2bm_ard_3-2-1_53KKT_2023-06-05_final
2023-06-05 11:02:59	ga_s2bm_ard_3-2-1_52KHC_2023-06-05_final
2023-06-05 11:03:06	ga_s2bm_ard_3-2-1_52KFC_2023-06-05_final
2023-06-05 11:03:14	ga_s2bm_ard_3-2-1_52KHB_2023-06-05_final
2023-06-05 11:03:21	ga_s2bm_ard_3-2-1_52KFB_2023-06-05_final
2023-06-05 11:03:32	ga_s2bm_ard_3-2-1_52KGA_2023-06-05_final
2023-06-05 11:03:35	ga_s2bm_ard_3-2-1_52KFA_2023-06-05_final
2023-06-05 11:03:39	ga_s2bm_ard_3-2-1_52KEA_2023-06-05_final
2023-06-05 11:03:50	ga_s2bm_ard_3-2-1_52KFV_2023-06-05_final
2023-06-05 11:03:58	ga_s2bm_ard_3-2-1_52KDV_2023-06-05_final
2023-06-05 11:04:04	ga_s2bm_ard_3-2-1_52KFU_2023-06-05_final
2023-06-05 11:04:22	ga_s2bm_ard_3-2-1_52JET_2023-06-05_final
2023-06-05 11:04:25	ga_s2bm_ard_3-2-1_52JDT_2023-06-05_final
2023-06-05 11:04:37	ga_s2bm_ard_3-2-1_52JES_2023-06-05_final
2023-06-05 11:04:40	ga_s2bm_ard_3-2-1_52JDS_2023-06-05_final
2023-06-05 11:05:17	ga_s2bm_ard_3-2-1_52JFP_2023-06-05_final
2023-06-05 11:05:31	ga_s2bm_ard_3-2-1_52JFN_2023-06-05_final
2023-06-05 11:05:56	ga_s2bm_ard_3-2-1_52JCM_2023-06-05_final
2023-06-05 11:06:02	ga_s2bm_ard_3-2-1_52JBM_2023-06-05_final
2023-06-05 11:06:07	ga_s2bm_ard_3-2-1_52JDL_2023-06-05_final
2023-06-05 11:06:11	ga_s2bm_ard_3-2-1_52JCL_2023-06-05_final
2023-06-05 11:06:14	ga_s2bm_ard_3-2-1_52JBL_2023-06-05_final
2023-06-05 11:06:22	ga_s2bm_ard_3-2-1_52HDK_2023-06-05_final
2023-06-05 11:06:25	ga_s2bm_ard_3-2-1_52HCK_2023-06-05_final
2023-06-05 11:06:40	ga_s2bm_ard_3-2-1_51HYD_2023-06-05_final
2023-06-14 11:30:31	ga_s2bm_ard_3-2-1_51LYJ_2023-06-14_nrt
2023-06-14 11:30:46	ga_s2bm_ard_3-2-1_51LYH_2023-06-14_nrt
2023-06-14 11:31:00	ga_s2bm_ard_3-2-1_51LYG_2023-06-14_nrt
2023-06-14 11:31:22	ga_s2bm_ard_3-2-1_51LWF_2023-06-14_nrt
2023-06-14 11:37:33	ga_s2bm_ard_3-2-1_51HTA_2023-06-14_nrt
2023-06-14 11:37:37	ga_s2bm_ard_3-2-1_50HNF_2023-06-14_nrt
2023-06-15 11:00:21	ga_s2bm_ard_3-2-1_52LHP_2023-06-15_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