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
2023-07-13 12:05:42	ga_s2bm_ard_3-2-1_50JLP_2023-07-13_final
2023-07-16 12:13:45	ga_s2bm_ard_3-2-1_50KKB_2023-07-16_final
2023-07-16 12:13:45	ga_s2bm_ard_3-2-1_49KHS_2023-07-16_final
2023-07-16 12:14:00	ga_s2bm_ard_3-2-1_49KHR_2023-07-16_final
2023-07-16 12:14:14	ga_s2bm_ard_3-2-1_49KHQ_2023-07-16_final
2023-07-16 12:14:18	ga_s2bm_ard_3-2-1_49KGQ_2023-07-16_final
2023-07-16 12:14:36	ga_s2bm_ard_3-2-1_49JHN_2023-07-16_final
2023-07-16 12:14:50	ga_s2bm_ard_3-2-1_49JFN_2023-07-16_final
2023-07-16 12:15:05	ga_s2bm_ard_3-2-1_49JFM_2023-07-16_final
2023-07-16 12:15:16	ga_s2bm_ard_3-2-1_49JGL_2023-07-16_final
2023-07-16 12:15:24	ga_s2bm_ard_3-2-1_49JGK_2023-07-16_final
2023-07-17 11:43:24	ga_s2bm_ard_3-2-1_50KRC_2023-07-17_final
2023-07-17 11:43:38	ga_s2bm_ard_3-2-1_50KRB_2023-07-17_final
2023-07-17 11:43:42	ga_s2bm_ard_3-2-1_50KQB_2023-07-17_final
2023-07-17 11:43:56	ga_s2bm_ard_3-2-1_50KQA_2023-07-17_final
2023-07-17 11:44:07	ga_s2bm_ard_3-2-1_51KTQ_2023-07-17_final
2023-07-17 11:44:22	ga_s2bm_ard_3-2-1_51KTP_2023-07-17_final
2023-07-17 11:44:33	ga_s2bm_ard_3-2-1_51JUN_2023-07-17_final
2023-07-17 11:44:36	ga_s2bm_ard_3-2-1_51JTN_2023-07-17_final
2023-07-17 11:44:43	ga_s2bm_ard_3-2-1_50JPT_2023-07-17_final
2023-07-17 11:44:46	ga_s2bm_ard_3-2-1_51JUM_2023-07-17_final
2023-07-17 11:44:54	ga_s2bm_ard_3-2-1_50JQS_2023-07-17_final
2023-07-17 11:44:58	ga_s2bm_ard_3-2-1_50JPS_2023-07-17_final
2023-07-17 11:45:09	ga_s2bm_ard_3-2-1_50JQR_2023-07-17_final
2023-07-17 11:45:23	ga_s2bm_ard_3-2-1_50JQQ_2023-07-17_final
2023-07-17 11:45:49	ga_s2bm_ard_3-2-1_51JTH_2023-07-17_final
2023-07-17 11:45:59	ga_s2bm_ard_3-2-1_50JNN_2023-07-17_final
2023-07-17 11:46:02	ga_s2bm_ard_3-2-1_51JTG_2023-07-17_final
2023-07-17 11:46:14	ga_s2bm_ard_3-2-1_50JNM_2023-07-17_final
2023-07-17 11:46:18	ga_s2bm_ard_3-2-1_50JMM_2023-07-17_final
2023-07-17 11:46:35	ga_s2bm_ard_3-2-1_50HQK_2023-07-17_final
2023-07-17 11:46:39	ga_s2bm_ard_3-2-1_50HPK_2023-07-17_final
2023-07-17 11:46:46	ga_s2bm_ard_3-2-1_50HMK_2023-07-17_final
2023-07-17 11:47:12	ga_s2bm_ard_3-2-1_50HNH_2023-07-17_final
2023-07-17 11:47:26	ga_s2bm_ard_3-2-1_50HNG_2023-07-17_final
2023-07-17 11:47:29	ga_s2bm_ard_3-2-1_50HMG_2023-07-17_final
2023-07-18 11:15:01	ga_s2bm_ard_3-2-1_51JYL_2023-07-18_final
2023-07-18 11:15:16	ga_s2bm_ard_3-2-1_51JYK_2023-07-18_final
2023-07-18 11:16:13	ga_s2bm_ard_3-2-1_51JYF_2023-07-18_final
2023-07-18 11:16:17	ga_s2bm_ard_3-2-1_51JXF_2023-07-18_final
2023-07-18 11:16:25	ga_s2bm_ard_3-2-1_51JWF_2023-07-18_final
2023-07-18 11:17:01	ga_s2bm_ard_3-2-1_51HXC_2023-07-18_final
2023-07-18 11:17:08	ga_s2bm_ard_3-2-1_51HXC_2023-07-18_final
2023-07-18 11:17:08	ga_s2bm_ard_3-2-1_51HWB_2023-07-18_final
2023-07-18 11:17:11	ga_s2bm_ard_3-2-1_51HWB_2023-07-18_final
2023-07-20 11:53:16	ga_s2bm_ard_3-2-1_50KRC_2023-07-20_final
2023-07-20 11:53:37	ga_s2bm_ard_3-2-1_50KQB_2023-07-20_final
2023-07-20 11:53:40	ga_s2bm_ard_3-2-1_50KPB_2023-07-20_final
2023-07-20 11:53:45	ga_s2bm_ard_3-2-1_50KQB_2023-07-20_final
2023-07-20 11:53:45	ga_s2bm_ard_3-2-1_50KQA_2023-07-20_final
2023-07-20 11:53:45	ga_s2bm_ard_3-2-1_50KPA_2023-07-20_final
2023-07-20 11:53:52	ga_s2bm_ard_3-2-1_50KQA_2023-07-20_final
2023-07-20 11:53:56	ga_s2bm_ard_3-2-1_50KPA_2023-07-20_final
2023-07-20 11:54:14	ga_s2bm_ard_3-2-1_50KNV_2023-07-20_final
2023-07-20 11:54:17	ga_s2bm_ard_3-2-1_50KMV_2023-07-20_final
2023-07-20 11:54:32	ga_s2bm_ard_3-2-1_50KMU_2023-07-20_final
2023-07-20 11:54:39	ga_s2bm_ard_3-2-1_50JPT_2023-07-20_final
2023-07-20 11:54:39	ga_s2bm_ard_3-2-1_50KLU_2023-07-20_final
2023-07-20 11:54:43	ga_s2bm_ard_3-2-1_50JNT_2023-07-20_final
2023-07-20 11:55:01	ga_s2bm_ard_3-2-1_50JMS_2023-07-20_final
2023-07-20 11:55:33	ga_s2bm_ard_3-2-1_50JLQ_2023-07-20_final
2023-07-20 11:55:48	ga_s2bm_ard_3-2-1_50JLP_2023-07-20_final
2023-07-20 11:55:59	ga_s2bm_ard_3-2-1_50JMN_2023-07-20_final
2023-07-20 11:56:10	ga_s2bm_ard_3-2-1_50JNM_2023-07-20_final
2023-07-20 11:56:20	ga_s2bm_ard_3-2-1_50JKM_2023-07-20_final
2023-07-20 11:56:42	ga_s2bm_ard_3-2-1_50HMK_2023-07-20_final
2023-07-20 11:56:46	ga_s2bm_ard_3-2-1_50HLK_2023-07-20_final
2023-07-20 11:57:25	ga_s2bm_ard_3-2-1_50HMG_2023-07-20_final
2023-07-21 11:24:35	ga_s2bm_ard_3-2-1_51JWN_2023-07-21_final
2023-07-21 11:24:57	ga_s2bm_ard_3-2-1_51JYL_2023-07-21_final
2023-07-21 11:25:12	ga_s2bm_ard_3-2-1_51JYK_2023-07-21_final
2023-07-21 11:25:48	ga_s2bm_ard_3-2-1_51JWH_2023-07-21_final
2023-07-21 11:25:51	ga_s2bm_ard_3-2-1_51JYG_2023-07-21_final
2023-07-21 11:26:13	ga_s2bm_ard_3-2-1_51JXF_2023-07-21_final
2023-07-21 11:26:17	ga_s2bm_ard_3-2-1_51JWF_2023-07-21_final
2023-07-21 11:26:35	ga_s2bm_ard_3-2-1_51HVE_2023-07-21_final
2023-07-21 11:26:42	ga_s2bm_ard_3-2-1_51HXD_2023-07-21_final
2023-07-21 11:26:53	ga_s2bm_ard_3-2-1_51HUD_2023-07-21_final
2023-07-21 11:26:53	ga_s2bm_ard_3-2-1_51HXC_2023-07-21_final
2023-07-21 11:27:08	ga_s2bm_ard_3-2-1_51HUC_2023-07-21_final
2023-07-21 11:27:13	ga_s2bm_ard_3-2-1_51HWB_2023-07-21_final
2023-07-23 12:03:50	ga_s2bm_ard_3-2-1_50KKB_2023-07-23_final
2023-07-23 12:03:50	ga_s2bm_ard_3-2-1_49KHS_2023-07-23_final
2023-07-23 12:04:05	ga_s2bm_ard_3-2-1_49KHR_2023-07-23_final
2023-07-23 12:04:13	ga_s2bm_ard_3-2-1_50KMV_2023-07-23_final
2023-07-23 12:04:16	ga_s2bm_ard_3-2-1_50KLV_2023-07-23_final
2023-07-23 12:04:19	ga_s2bm_ard_3-2-1_49KHQ_2023-07-23_final
2023-07-23 12:04:27	ga_s2bm_ard_3-2-1_50KMU_2023-07-23_final
2023-07-23 12:04:30	ga_s2bm_ard_3-2-1_50KLU_2023-07-23_final
2023-07-23 12:04:33	ga_s2bm_ard_3-2-1_49KGP_2023-07-23_final
2023-07-23 12:04:35	ga_s2bm_ard_3-2-1_50KMU_2023-07-23_final
2023-07-23 12:04:37	ga_s2bm_ard_3-2-1_50KLU_2023-07-23_final
2023-07-23 12:04:40	ga_s2bm_ard_3-2-1_49KGP_2023-07-23_final
2023-07-23 12:04:48	ga_s2bm_ard_3-2-1_49JHN_2023-07-23_final
2023-07-23 12:04:54	ga_s2bm_ard_3-2-1_50JMS_2023-07-23_final
2023-07-23 12:05:14	ga_s2bm_ard_3-2-1_49JFM_2023-07-23_final
2023-07-23 12:05:21	ga_s2bm_ard_3-2-1_49JGL_2023-07-23_final
2023-07-23 12:05:29	ga_s2bm_ard_3-2-1_50JLQ_2023-07-23_final
2023-07-23 12:05:35	ga_s2bm_ard_3-2-1_49JGK_2023-07-23_final
2023-07-23 12:05:44	ga_s2bm_ard_3-2-1_50JLP_2023-07-23_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