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
2023-07-14 11:36:24	ga_s2bm_ard_3-2-1_50JQL_2023-07-14_final
2023-07-15 11:01:51	ga_s2bm_ard_3-2-1_52LGH_2023-07-15_final
2023-07-15 11:01:55	ga_s2bm_ard_3-2-1_52LFH_2023-07-15_final
2023-07-15 11:02:02	ga_s2bm_ard_3-2-1_52KHG_2023-07-15_final
2023-07-15 11:02:20	ga_s2bm_ard_3-2-1_52KGF_2023-07-15_final
2023-07-15 11:02:23	ga_s2bm_ard_3-2-1_52KFF_2023-07-15_final
2023-07-15 11:02:42	ga_s2bm_ard_3-2-1_52KGE_2023-07-15_final
2023-07-15 11:02:49	ga_s2bm_ard_3-2-1_52KGD_2023-07-15_final
2023-07-15 11:02:57	ga_s2bm_ard_3-2-1_52KED_2023-07-15_final
2023-07-15 11:03:10	ga_s2bm_ard_3-2-1_52KEC_2023-07-15_final
2023-07-15 11:03:14	ga_s2bm_ard_3-2-1_52KHB_2023-07-15_final
2023-07-15 11:04:11	ga_s2bm_ard_3-2-1_52KDU_2023-07-15_final
2023-07-15 11:04:48	ga_s2bm_ard_3-2-1_52JFR_2023-07-15_final
2023-07-15 11:04:55	ga_s2bm_ard_3-2-1_52JDR_2023-07-15_final
2023-07-15 11:05:03	ga_s2bm_ard_3-2-1_52JFQ_2023-07-15_final
2023-07-15 11:05:10	ga_s2bm_ard_3-2-1_52JDQ_2023-07-15_final
2023-07-15 11:05:35	ga_s2bm_ard_3-2-1_52JEN_2023-07-15_final
2023-07-15 11:05:50	ga_s2bm_ard_3-2-1_52JEM_2023-07-15_final
2023-07-15 11:05:57	ga_s2bm_ard_3-2-1_52JCM_2023-07-15_final
2023-07-15 11:06:08	ga_s2bm_ard_3-2-1_52JDL_2023-07-15_final
2023-07-15 11:06:11	ga_s2bm_ard_3-2-1_52JCL_2023-07-15_final
2023-07-16 12:13:45	ga_s2bm_ard_3-2-1_50KKB_2023-07-16_final
2023-07-16 12:14:46	ga_s2bm_ard_3-2-1_49JGN_2023-07-16_final
2023-07-17 11:41:06	ga_s2bm_ard_3-2-1_51LVG_2023-07-17_final
2023-07-17 11:42:07	ga_s2bm_ard_3-2-1_51LUC_2023-07-17_final
2023-07-17 11:43:27	ga_s2bm_ard_3-2-1_50KQC_2023-07-17_final
2023-07-17 11:43:38	ga_s2bm_ard_3-2-1_51KTS_2023-07-17_final
2023-07-17 11:44:03	ga_s2bm_ard_3-2-1_51KUQ_2023-07-17_final
2023-07-17 11:44:11	ga_s2bm_ard_3-2-1_50KQV_2023-07-17_final
2023-07-17 11:44:25	ga_s2bm_ard_3-2-1_50KQU_2023-07-17_final
2023-07-17 11:44:36	ga_s2bm_ard_3-2-1_51JTN_2023-07-17_final
2023-07-17 11:44:40	ga_s2bm_ard_3-2-1_50JQT_2023-07-17_final
2023-07-17 11:45:41	ga_s2bm_ard_3-2-1_50JPP_2023-07-17_final
2023-07-17 11:46:28	ga_s2bm_ard_3-2-1_50JNL_2023-07-17_final
2023-07-17 11:47:20	ga_s2bm_ard_3-2-1_50HLH_2023-07-17_final
2023-07-18 11:11:33	ga_s2bm_ard_3-2-1_52LGJ_2023-07-18_final
2023-07-18 11:11:50	ga_s2bm_ard_3-2-1_52LFH_2023-07-18_final
2023-07-18 11:12:05	ga_s2bm_ard_3-2-1_52KFG_2023-07-18_final
2023-07-18 11:12:12	ga_s2bm_ard_3-2-1_52KDG_2023-07-18_final
2023-07-18 11:12:19	ga_s2bm_ard_3-2-1_52KFF_2023-07-18_final
2023-07-18 11:12:52	ga_s2bm_ard_3-2-1_52KED_2023-07-18_final
2023-07-18 11:12:55	ga_s2bm_ard_3-2-1_52KDD_2023-07-18_final
2023-07-18 11:13:34	ga_s2bm_ard_3-2-1_51KZS_2023-07-18_final
2023-07-18 11:14:26	ga_s2bm_ard_3-2-1_52JCT_2023-07-18_final
2023-07-18 11:14:40	ga_s2bm_ard_3-2-1_52JCS_2023-07-18_final
2023-07-18 11:14:52	ga_s2bm_ard_3-2-1_52JDR_2023-07-18_final
2023-07-18 11:15:27	ga_s2bm_ard_3-2-1_52JBP_2023-07-18_final
2023-07-18 11:15:53	ga_s2bm_ard_3-2-1_52JCM_2023-07-18_final
2023-07-18 11:17:01	ga_s2bm_ard_3-2-1_51HXC_2023-07-18_final
2023-07-18 11:17:09	ga_s2bm_ard_3-2-1_51HWC_2023-07-18_final
2023-07-20 11:52:43	ga_s2bm_ard_3-2-1_50KPF_2023-07-20_final
2023-07-20 11:53:00	ga_s2bm_ard_3-2-1_51KTU_2023-07-20_final
2023-07-20 11:53:12	ga_s2bm_ard_3-2-1_50KPD_2023-07-20_final
2023-07-20 11:53:23	ga_s2bm_ard_3-2-1_50KQC_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_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 11:54:19	ga_s2bm_ard_3-2-1_50KQU_2023-07-20_final
2023-07-20 11:54:29	ga_s2bm_ard_3-2-1_50JQT_2023-07-20_final
2023-07-20 11:54:32	ga_s2bm_ard_3-2-1_50KMU_2023-07-20_final
2023-07-20 11:54:50	ga_s2bm_ard_3-2-1_50JLT_2023-07-20_final
2023-07-20 11:55:01	ga_s2bm_ard_3-2-1_50JMS_2023-07-20_final
2023-07-20 11:55:12	ga_s2bm_ard_3-2-1_50JNR_2023-07-20_final
2023-07-20 11:55:32	ga_s2bm_ard_3-2-1_50JPP_2023-07-20_final
2023-07-20 11:56:17	ga_s2bm_ard_3-2-1_50JLM_2023-07-20_final
2023-07-20 11:56:24	ga_s2bm_ard_3-2-1_50JNL_2023-07-20_final
2023-07-20 11:56:28	ga_s2bm_ard_3-2-1_50JML_2023-07-20_final
2023-07-20 11:56:42	ga_s2bm_ard_3-2-1_50HMK_2023-07-20_final
2023-07-20 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-07-20_final
2023-07-21 11:21:30	ga_s2bm_ard_3-2-1_52LBK_2023-07-21_final
2023-07-21 11:22:06	ga_s2bm_ard_3-2-1_52KDG_2023-07-21_final
2023-07-21 11:22:14	ga_s2bm_ard_3-2-1_52KBG_2023-07-21_final
2023-07-21 11:22:29	ga_s2bm_ard_3-2-1_51KZA_2023-07-21_final
2023-07-21 11:23:45	ga_s2bm_ard_3-2-1_51KYR_2023-07-21_final
2023-07-21 11:24:10	ga_s2bm_ard_3-2-1_52KBU_2023-07-21_final
2023-07-21 11:24:35	ga_s2bm_ard_3-2-1_51JWN_2023-07-21_final
2023-07-21 11:24:43	ga_s2bm_ard_3-2-1_51JYM_2023-07-21_final
2023-07-21 11:24:46	ga_s2bm_ard_3-2-1_51JXM_2023-07-21_final
2023-07-21 11:25:01	ga_s2bm_ard_3-2-1_51JXL_2023-07-21_final
2023-07-21 11:25:09	ga_s2bm_ard_3-2-1_51JVL_2023-07-21_final
2023-07-21 11:26:20	ga_s2bm_ard_3-2-1_51JVF_2023-07-21_final
2023-07-21 11:26:38	ga_s2bm_ard_3-2-1_51HUE_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_51HXC_2023-07-21_final
2023-07-21 11:27:00	ga_s2bm_ard_3-2-1_51HWC_2023-07-21_final
2023-07-22 10:53:20	ga_s2bm_ard_3-2-1_52KHB_2023-07-22_final
2023-07-22 10:54:18	ga_s2bm_ard_3-2-1_52JGT_2023-07-22_final
2023-07-22 10:54:24	ga_s2bm_ard_3-2-1_52JHS_2023-07-22_final
2023-07-22 10:54:25	ga_s2bm_ard_3-2-1_52JGT_2023-07-22_final
2023-07-22 10:54:53	ga_s2bm_ard_3-2-1_52JFR_2023-07-22_final
2023-07-22 10:55:05	ga_s2bm_ard_3-2-1_52JGQ_2023-07-22_final
2023-07-22 10:55:55	ga_s2bm_ard_3-2-1_52JEM_2023-07-22_final
2023-07-23 12:04:13	ga_s2bm_ard_3-2-1_50KMV_2023-07-23_final
2023-07-23 12:04:35	ga_s2bm_ard_3-2-1_50KMU_2023-07-23_final
2023-07-23 12:04:52	ga_s2bm_ard_3-2-1_49JGN_2023-07-23_final
2023-07-23 12:04:54	ga_s2bm_ard_3-2-1_50JMS_2023-07-23_final
2023-07-23 12:05:03	ga_s2bm_ard_3-2-1_49JHM_2023-07-23_final
2023-07-23 12:05:57	ga_s2bm_ard_3-2-1_50JLN_2023-07-23_final
2023-07-23 12:06:01	ga_s2bm_ard_3-2-1_50JKN_2023-07-23_final
2023-07-23 12:06:10	ga_s2bm_ard_3-2-1_50JLM_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