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
2023-03-25 10:26:09	ga_s2bm_ard_3-2-1_53HPE_2023-03-25_final
2023-03-25 10:26:24	ga_s2bm_ard_3-2-1_53HPD_2023-03-25_final
2023-03-25 10:26:43	ga_s2bm_ard_3-2-1_53HNC_2023-03-25_final
2023-03-25 10:26:56	ga_s2bm_ard_3-2-1_53HNB_2023-03-25_final
2023-03-25 12:03:47	ga_s2bm_ard_3-2-1_50KKB_2023-03-25_final
2023-03-25 12:04:09	ga_s2bm_ard_3-2-1_50KMV_2023-03-25_final
2023-03-25 12:04:13	ga_s2bm_ard_3-2-1_50KLV_2023-03-25_final
2023-03-25 12:04:16	ga_s2bm_ard_3-2-1_49KHQ_2023-03-25_final
2023-03-25 12:04:24	ga_s2bm_ard_3-2-1_50KMU_2023-03-25_final
2023-03-25 12:04:27	ga_s2bm_ard_3-2-1_50KLU_2023-03-25_final
2023-03-25 12:04:29	ga_s2bm_ard_3-2-1_49KHP_2023-03-25_final
2023-03-25 12:04:35	ga_s2bm_ard_3-2-1_50KLU_2023-03-25_final
2023-03-25 12:04:35	ga_s2bm_ard_3-2-1_49JHN_2023-03-25_final
2023-03-25 12:04:36	ga_s2bm_ard_3-2-1_49KHP_2023-03-25_final
2023-03-25 12:04:36	ga_s2bm_ard_3-2-1_50JKT_2023-03-25_final
2023-03-25 12:04:45	ga_s2bm_ard_3-2-1_49JHN_2023-03-25_final
2023-03-25 12:04:45	ga_s2bm_ard_3-2-1_50JKT_2023-03-25_final
2023-03-25 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2023-03-25_final
2023-03-25 12:04:51	ga_s2bm_ard_3-2-1_50JMS_2023-03-25_final
2023-03-25 12:04:56	ga_s2bm_ard_3-2-1_50JLS_2023-03-25_final
2023-03-25 12:04:59	ga_s2bm_ard_3-2-1_49JHM_2023-03-25_final
2023-03-25 12:04:59	ga_s2bm_ard_3-2-1_50JKS_2023-03-25_final
2023-03-25 12:05:01	ga_s2bm_ard_3-2-1_50JMR_2023-03-25_final
2023-03-25 12:05:03	ga_s2bm_ard_3-2-1_49JGM_2023-03-25_final
2023-03-25 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2023-03-25_final
2023-03-25 12:05:14	ga_s2bm_ard_3-2-1_50JKR_2023-03-25_final
2023-03-25 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2023-03-25_final
2023-03-25 12:05:29	ga_s2bm_ard_3-2-1_50JKQ_2023-03-25_final
2023-03-25 12:05:40	ga_s2bm_ard_3-2-1_50JLP_2023-03-25_final
2023-03-25 12:05:43	ga_s2bm_ard_3-2-1_50JKP_2023-03-25_final
2023-03-25 12:05:46	ga_s2bm_ard_3-2-1_49JGJ_2023-03-25_final
2023-03-25 12:05:58	ga_s2bm_ard_3-2-1_50JKN_2023-03-25_final
2023-03-25 12:06:01	ga_s2bm_ard_3-2-1_49JGH_2023-03-25_final
2023-03-25 12:06:16	ga_s2bm_ard_3-2-1_50JLL_2023-03-25_final
2023-03-26 11:31:27	ga_s2bm_ard_3-2-1_51LYE_2023-03-26_final
2023-03-26 11:31:33	ga_s2bm_ard_3-2-1_51LWE_2023-03-26_final
2023-03-26 11:32:25	ga_s2bm_ard_3-2-1_51KYA_2023-03-26_final
2023-03-26 11:32:35	ga_s2bm_ard_3-2-1_51KVA_2023-03-26_final
2023-03-26 11:32:43	ga_s2bm_ard_3-2-1_51KXV_2023-03-26_final
2023-03-26 11:32:49	ga_s2bm_ard_3-2-1_51KVV_2023-03-26_final
2023-03-26 11:32:53	ga_s2bm_ard_3-2-1_51KYU_2023-03-26_final
2023-03-26 11:33:01	ga_s2bm_ard_3-2-1_51KWU_2023-03-26_final
2023-03-26 11:33:04	ga_s2bm_ard_3-2-1_51KVU_2023-03-26_final
2023-03-26 11:33:05	ga_s2bm_ard_3-2-1_51KYT_2023-03-26_final
2023-03-26 11:33:15	ga_s2bm_ard_3-2-1_51KWT_2023-03-26_final
2023-03-26 11:33:30	ga_s2bm_ard_3-2-1_51KWS_2023-03-26_final
2023-03-26 11:33:44	ga_s2bm_ard_3-2-1_51KWR_2023-03-26_final
2023-03-26 11:34:20	ga_s2bm_ard_3-2-1_51KUP_2023-03-26_final
2023-03-26 11:34:52	ga_s2bm_ard_3-2-1_51JTM_2023-03-26_final
2023-03-26 11:35:04	ga_s2bm_ard_3-2-1_51JUL_2023-03-26_final
2023-03-26 11:35:07	ga_s2bm_ard_3-2-1_51JTL_2023-03-26_final
2023-03-26 11:35:10	ga_s2bm_ard_3-2-1_51JWK_2023-03-26_final
2023-03-26 11:35:18	ga_s2bm_ard_3-2-1_51JUK_2023-03-26_final
2023-03-26 11:35:22	ga_s2bm_ard_3-2-1_51JWJ_2023-03-26_final
2023-03-26 11:35:29	ga_s2bm_ard_3-2-1_51JVJ_2023-03-26_final
2023-03-26 11:35:33	ga_s2bm_ard_3-2-1_51JUJ_2023-03-26_final
2023-03-26 11:35:44	ga_s2bm_ard_3-2-1_51JVH_2023-03-26_final
2023-03-26 11:36:29	ga_s2bm_ard_3-2-1_50JPL_2023-03-26_final
2023-03-26 11:36:31	ga_s2bm_ard_3-2-1_51HUE_2023-03-26_final
2023-03-26 11:36:40	ga_s2bm_ard_3-2-1_50HPK_2023-03-26_final
2023-03-26 11:36:51	ga_s2bm_ard_3-2-1_50HQJ_2023-03-26_final
2023-03-26 11:36:54	ga_s2bm_ard_3-2-1_50HPJ_2023-03-26_final
2023-03-26 11:37:03	ga_s2bm_ard_3-2-1_51HTC_2023-03-26_final
2023-03-26 11:37:09	ga_s2bm_ard_3-2-1_50HPH_2023-03-26_final
2023-03-26 11:37:18	ga_s2bm_ard_3-2-1_51HTB_2023-03-26_final
2023-03-26 11:37:24	ga_s2bm_ard_3-2-1_50HPG_2023-03-26_final
2023-03-26 11:37:29	ga_s2bm_ard_3-2-1_50HNG_2023-03-26_final
2023-03-27 11:01:05	ga_s2bm_ard_3-2-1_52LGL_2023-03-27_final
2023-03-27 11:01:20	ga_s2bm_ard_3-2-1_52LGK_2023-03-27_final
2023-03-27 11:02:29	ga_s2bm_ard_3-2-1_52KHE_2023-03-27_final
2023-03-27 11:02:38	ga_s2bm_ard_3-2-1_52KHE_2023-03-27_final
2023-03-27 11:03:01	ga_s2bm_ard_3-2-1_52KGC_2023-03-27_final
2023-03-27 11:03:12	ga_s2bm_ard_3-2-1_52KHB_2023-03-27_final
2023-03-27 11:03:16	ga_s2bm_ard_3-2-1_52KGB_2023-03-27_final
2023-03-27 11:03:23	ga_s2bm_ard_3-2-1_52KEB_2023-03-27_final
2023-03-27 11:03:52	ga_s2bm_ard_3-2-1_52KEV_2023-03-27_final
2023-03-27 11:04:06	ga_s2bm_ard_3-2-1_52KEU_2023-03-27_final
2023-03-27 11:04:17	ga_s2bm_ard_3-2-1_52JFT_2023-03-27_final
2023-03-27 11:04:24	ga_s2bm_ard_3-2-1_52JDT_2023-03-27_final
2023-03-27 11:04:27	ga_s2bm_ard_3-2-1_52JGS_2023-03-27_final
2023-03-27 11:04:32	ga_s2bm_ard_3-2-1_52JFS_2023-03-27_final
2023-03-27 11:04:38	ga_s2bm_ard_3-2-1_52JGR_2023-03-27_final
2023-03-27 11:04:39	ga_s2bm_ard_3-2-1_52JDS_2023-03-27_final
2023-03-27 11:05:41	ga_s2bm_ard_3-2-1_52JFM_2023-03-27_final
2023-03-27 11:05:55	ga_s2bm_ard_3-2-1_52JCM_2023-03-27_final
2023-03-27 11:06:09	ga_s2bm_ard_3-2-1_52JCL_2023-03-27_final
2023-03-27 11:06:40	ga_s2bm_ard_3-2-1_51HYD_2023-03-27_final
2023-04-07 10:36:45	ga_s2bm_ard_3-2-1_53HLC_2023-04-07_nrt
2023-04-07 10:37:00	ga_s2bm_ard_3-2-1_53HLB_2023-04-07_nrt
2023-04-07 10:37:05	ga_s2bm_ard_3-2-1_53HNA_2023-04-07_nrt
2023-04-07 10:37:07	ga_s2bm_ard_3-2-1_53HMA_2023-04-07_nrt
2023-04-07 10:37:09	ga_s2bm_ard_3-2-1_53HLA_2023-04-07_nrt
2023-04-07 12:13:29	ga_s2bm_ard_3-2-1_49KFU_2023-04-07_nrt
2023-04-07 12:13:32	ga_s2bm_ard_3-2-1_50KKC_2023-04-07_nrt
2023-04-07 12:13:32	ga_s2bm_ard_3-2-1_49KHT_2023-04-07_nrt
2023-04-07 12:13:34	ga_s2bm_ard_3-2-1_49KGT_2023-04-07_nrt
2023-04-07 12:13:46	ga_s2bm_ard_3-2-1_49KGS_2023-04-07_nrt
2023-04-07 12:13:50	ga_s2bm_ard_3-2-1_49KFS_2023-04-07_nrt
2023-04-07 12:14:33	ga_s2bm_ard_3-2-1_49KFP_2023-04-07_nrt
2023-04-07 12:15:17	ga_s2bm_ard_3-2-1_49JFL_2023-04-07_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