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
2023-05-06 11:04:35	ga_s2bm_ard_3-2-1_52JES_2023-05-06_final
2023-05-06 11:04:38	ga_s2bm_ard_3-2-1_52JGR_2023-05-06_final
2023-05-08 11:44:30	ga_s2bm_ard_3-2-1_51JUN_2023-05-08_final
2023-05-08 11:45:24	ga_s2bm_ard_3-2-1_50JPQ_2023-05-08_final
2023-05-08 11:46:25	ga_s2bm_ard_3-2-1_50JNL_2023-05-08_final
2023-05-10 10:44:15	ga_s2bm_ard_3-2-1_53JLN_2023-05-10_final
2023-05-10 10:44:30	ga_s2bm_ard_3-2-1_53JLM_2023-05-10_final
2023-05-10 10:45:46	ga_s2bm_ard_3-2-1_53JKG_2023-05-10_final
2023-05-10 10:46:23	ga_s2bm_ard_3-2-1_53HMD_2023-05-10_final
2023-05-11 10:16:54	ga_s2bm_ard_3-2-1_53HQB_2023-05-11_final
2023-05-11 11:52:22	ga_s2bm_ard_3-2-1_50KQG_2023-05-11_final
2023-05-11 11:52:36	ga_s2bm_ard_3-2-1_50KQF_2023-05-11_final
2023-05-11 11:52:51	ga_s2bm_ard_3-2-1_50KQE_2023-05-11_final
2023-05-11 11:53:33	ga_s2bm_ard_3-2-1_50KMC_2023-05-11_final
2023-05-11 11:53:38	ga_s2bm_ard_3-2-1_50KPB_2023-05-11_final
2023-05-11 11:53:50	ga_s2bm_ard_3-2-1_50KPA_2023-05-11_final
2023-05-11 11:53:57	ga_s2bm_ard_3-2-1_50KPA_2023-05-11_final
2023-05-11 11:54:07	ga_s2bm_ard_3-2-1_50KPV_2023-05-11_final
2023-05-11 11:54:43	ga_s2bm_ard_3-2-1_50JMT_2023-05-11_final
2023-05-11 11:54:54	ga_s2bm_ard_3-2-1_50JNS_2023-05-11_final
2023-05-11 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2023-05-11_final
2023-05-11 11:56:20	ga_s2bm_ard_3-2-1_50JNL_2023-05-11_final
2023-05-11 11:56:57	ga_s2bm_ard_3-2-1_50HLJ_2023-05-11_final
2023-05-11 11:57:12	ga_s2bm_ard_3-2-1_50HLH_2023-05-11_final
2023-05-12 11:21:24	ga_s2bm_ard_3-2-1_52LCK_2023-05-12_final
2023-05-12 11:22:03	ga_s2bm_ard_3-2-1_52KDG_2023-05-12_final
2023-05-12 11:22:07	ga_s2bm_ard_3-2-1_52KCG_2023-05-12_final
2023-05-12 11:22:55	ga_s2bm_ard_3-2-1_51KZU_2023-05-12_final
2023-05-12 11:23:27	ga_s2bm_ard_3-2-1_51KYS_2023-05-12_final
2023-05-12 11:24:07	ga_s2bm_ard_3-2-1_51KZP_2023-05-12_final
2023-05-12 11:24:39	ga_s2bm_ard_3-2-1_51JYM_2023-05-12_final
2023-05-12 11:25:20	ga_s2bm_ard_3-2-1_51JWK_2023-05-12_final
2023-05-12 11:25:47	ga_s2bm_ard_3-2-1_51JYG_2023-05-12_final
2023-05-12 11:26:08	ga_s2bm_ard_3-2-1_51JUG_2023-05-12_final
2023-05-12 11:26:57	ga_s2bm_ard_3-2-1_51HWC_2023-05-12_final
2023-05-12 11:27:04	ga_s2bm_ard_3-2-1_51HUC_2023-05-12_final
2023-05-13 10:52:12	ga_s2bm_ard_3-2-1_53KMA_2023-05-13_final
2023-05-13 10:53:02	ga_s2bm_ard_3-2-1_53KKT_2023-05-13_final
2023-05-13 10:54:24	ga_s2bm_ard_3-2-1_52JFT_2023-05-13_final
2023-05-13 10:54:36	ga_s2bm_ard_3-2-1_52JFS_2023-05-13_final
2023-05-13 10:55:27	ga_s2bm_ard_3-2-1_53JKH_2023-05-13_final
2023-05-13 10:56:07	ga_s2bm_ard_3-2-1_52JEL_2023-05-13_final
2023-05-14 10:25:38	ga_s2bm_ard_3-2-1_53JQG_2023-05-14_final
2023-05-14 10:25:52	ga_s2bm_ard_3-2-1_53JQF_2023-05-14_final
2023-05-14 10:26:36	ga_s2bm_ard_3-2-1_53HQC_2023-05-14_final
2023-05-14 10:26:39	ga_s2bm_ard_3-2-1_53HPC_2023-05-14_final
2023-05-14 10:26:54	ga_s2bm_ard_3-2-1_53HPB_2023-05-14_final
2023-05-14 12:03:27	ga_s2bm_ard_3-2-1_50KMC_2023-05-14_final
2023-05-14 12:03:44	ga_s2bm_ard_3-2-1_50KLB_2023-05-14_final
2023-05-14 12:04:40	ga_s2bm_ard_3-2-1_50JMT_2023-05-14_final
2023-05-14 12:05:00	ga_s2bm_ard_3-2-1_50JKS_2023-05-14_final
2023-05-14 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2023-05-14_final
2023-05-15 11:31:46	ga_s2bm_ard_3-2-1_51LXD_2023-05-15_final
2023-05-15 11:32:00	ga_s2bm_ard_3-2-1_51LXC_2023-05-15_final
2023-05-15 11:32:03	ga_s2bm_ard_3-2-1_51KZB_2023-05-15_final
2023-05-15 11:32:15	ga_s2bm_ard_3-2-1_51KXB_2023-05-15_final
2023-05-15 11:32:18	ga_s2bm_ard_3-2-1_51KWB_2023-05-15_final
2023-05-15 11:32:29	ga_s2bm_ard_3-2-1_51KXA_2023-05-15_final
2023-05-15 11:32:33	ga_s2bm_ard_3-2-1_51KWA_2023-05-15_final
2023-05-15 11:32:47	ga_s2bm_ard_3-2-1_51KWV_2023-05-15_final
2023-05-15 11:32:58	ga_s2bm_ard_3-2-1_51KXU_2023-05-15_final
2023-05-15 11:33:13	ga_s2bm_ard_3-2-1_51KXT_2023-05-15_final
2023-05-15 11:33:26	ga_s2bm_ard_3-2-1_51KUT_2023-05-15_final
2023-05-15 11:33:38	ga_s2bm_ard_3-2-1_51KUS_2023-05-15_final
2023-05-15 11:33:49	ga_s2bm_ard_3-2-1_51KVR_2023-05-15_final
2023-05-15 11:34:03	ga_s2bm_ard_3-2-1_51KVQ_2023-05-15_final
2023-05-15 11:34:36	ga_s2bm_ard_3-2-1_51JUN_2023-05-15_final
2023-05-15 11:34:40	ga_s2bm_ard_3-2-1_50JRT_2023-05-15_final
2023-05-15 11:34:50	ga_s2bm_ard_3-2-1_51JUM_2023-05-15_final
2023-05-15 11:35:12	ga_s2bm_ard_3-2-1_51JWK_2023-05-15_final
2023-05-15 11:35:16	ga_s2bm_ard_3-2-1_51JVK_2023-05-15_final
2023-05-15 11:35:23	ga_s2bm_ard_3-2-1_51JTK_2023-05-15_final
2023-05-15 11:35:23	ga_s2bm_ard_3-2-1_51JWJ_2023-05-15_final
2023-05-15 11:35:37	ga_s2bm_ard_3-2-1_51JTJ_2023-05-15_final
2023-05-15 11:35:41	ga_s2bm_ard_3-2-1_50JQP_2023-05-15_final
2023-05-15 11:35:49	ga_s2bm_ard_3-2-1_51JUH_2023-05-15_final
2023-05-15 11:35:54	ga_s2bm_ard_3-2-1_50JQN_2023-05-15_final
2023-05-15 11:36:03	ga_s2bm_ard_3-2-1_51JUG_2023-05-15_final
2023-05-15 11:36:47	ga_s2bm_ard_3-2-1_51HUD_2023-05-15_final
2023-05-15 11:36:52	ga_s2bm_ard_3-2-1_50HQJ_2023-05-15_final
2023-05-15 11:37:01	ga_s2bm_ard_3-2-1_51HUC_2023-05-15_final
2023-05-15 11:37:10	ga_s2bm_ard_3-2-1_50HPH_2023-05-15_final
2023-05-15 11:37:25	ga_s2bm_ard_3-2-1_50HPG_2023-05-15_final
2023-05-24 12:00:28	ga_s2bm_ard_3-2-1_50LRP_2023-05-24_nrt
2023-05-24 12:00:38	ga_s2bm_ard_3-2-1_50LQP_2023-05-24_nrt
2023-05-24 12:00:53	ga_s2bm_ard_3-2-1_50LQN_2023-05-24_nrt
2023-05-24 12:03:13	ga_s2bm_ard_3-2-1_50KMD_2023-05-24_nrt
2023-05-24 12:03:17	ga_s2bm_ard_3-2-1_50KLD_2023-05-24_nrt
2023-05-24 12:05:24	ga_s2bm_ard_3-2-1_49JFL_2023-05-24_nrt
2023-05-24 12:05:37	ga_s2bm_ard_3-2-1_49JFK_2023-05-24_nrt
2023-05-24 12:05:52	ga_s2bm_ard_3-2-1_49JFJ_2023-05-24_nrt
2023-05-24 12:06:07	ga_s2bm_ard_3-2-1_49JFH_2023-05-24_nrt
2023-05-24 12:06:21	ga_s2bm_ard_3-2-1_49JFG_2023-05-24_nrt
2023-05-24 12:06:29	ga_s2bm_ard_3-2-1_49JFF_2023-05-24_nrt
2023-05-25 11:30:49	ga_s2bm_ard_3-2-1_51LXH_2023-05-25_nrt
2023-05-25 11:30:56	ga_s2bm_ard_3-2-1_51LZG_2023-05-25_nrt
2023-05-25 11:31:03	ga_s2bm_ard_3-2-1_51LXG_2023-05-25_nrt
2023-05-25 11:31:11	ga_s2bm_ard_3-2-1_51LZF_2023-05-25_nrt
2023-05-25 11:31:32	ga_s2bm_ard_3-2-1_51LXE_2023-05-25_nrt
2023-05-25 11:37:33	ga_s2bm_ard_3-2-1_51HTA_2023-05-25_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