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
2022-08-01 11:45:19	ga_s2bm_ard_3-2-1_51JTK_2022-08-01_final.stac-item
2022-08-01 11:45:22	ga_s2bm_ard_3-2-1_50JQQ_2022-08-01_final.stac-item
2022-08-02 11:13:23	ga_s2bm_ard_3-2-1_52KDB_2022-08-02_final.stac-item
2022-08-02 11:14:28	ga_s2bm_ard_3-2-1_52JBT_2022-08-02_final.stac-item
2022-08-03 10:43:45	ga_s2bm_ard_3-2-1_53KMQ_2022-08-03_final.stac-item
2022-08-03 10:44:17	ga_s2bm_ard_3-2-1_53JLN_2022-08-03_final.stac-item
2022-08-04 11:54:52	ga_s2bm_ard_3-2-1_50JPS_2022-08-04_final.stac-item
2022-08-04 11:55:14	ga_s2bm_ard_3-2-1_50JMR_2022-08-04_final.stac-item
2022-08-04 11:56:41	ga_s2bm_ard_3-2-1_50HMK_2022-08-04_final.stac-item
2022-08-04 11:57:14	ga_s2bm_ard_3-2-1_50HLH_2022-08-04_final.stac-item
2022-08-05 11:24:09	ga_s2bm_ard_3-2-1_51KZP_2022-08-05_final.stac-item
2022-08-05 11:26:10	ga_s2bm_ard_3-2-1_51JUG_2022-08-05_final.stac-item
2022-08-05 11:26:19	ga_s2bm_ard_3-2-1_51JVF_2022-08-05_final.stac-item
2022-08-06 10:54:45	ga_s2bm_ard_3-2-1_53JKL_2022-08-06_final.stac-item
2022-08-07 12:04:03	ga_s2bm_ard_3-2-1_50KKA_2022-08-07_final.stac-item
2022-08-07 12:04:03	ga_s2bm_ard_3-2-1_49KHR_2022-08-07_final.stac-item
2022-08-07 12:04:18	ga_s2bm_ard_3-2-1_49KHQ_2022-08-07_final.stac-item
2022-08-07 12:04:22	ga_s2bm_ard_3-2-1_49KGQ_2022-08-07_final.stac-item
2022-08-07 12:04:32	ga_s2bm_ard_3-2-1_49KHP_2022-08-07_final.stac-item
2022-08-07 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-08-07_final.stac-item
2022-08-07 12:04:45	ga_s2bm_ard_3-2-1_49JGN_2022-08-07_final.stac-item
2022-08-07 12:04:58	ga_s2bm_ard_3-2-1_50JLS_2022-08-07_final.stac-item
2022-08-07 12:05:56	ga_s2bm_ard_3-2-1_50JLN_2022-08-07_final.stac-item
2022-08-08 11:35:37	ga_s2bm_ard_3-2-1_51JTJ_2022-08-08_final.stac-item
2022-08-08 11:36:18	ga_s2bm_ard_3-2-1_51JUF_2022-08-08_final.stac-item
2022-08-08 11:36:42	ga_s2bm_ard_3-2-1_50HPK_2022-08-08_final.stac-item
2022-08-08 11:37:07	ga_s2bm_ard_3-2-1_50HQH_2022-08-08_final.stac-item
2022-08-09 11:03:02	ga_s2bm_ard_3-2-1_52KGC_2022-08-09_final.stac-item
2022-08-09 11:03:26	ga_s2bm_ard_3-2-1_52KHA_2022-08-09_final.stac-item
2022-08-09 11:03:38	ga_s2bm_ard_3-2-1_52KEA_2022-08-09_final.stac-item
2022-08-09 11:04:00	ga_s2bm_ard_3-2-1_52KGU_2022-08-09_final.stac-item
2022-08-10 12:13:58	ga_s2bm_ard_3-2-1_50KKA_2022-08-10_final.stac-item
2022-08-10 12:14:25	ga_s2bm_ard_3-2-1_49KHP_2022-08-10_final.stac-item
2022-08-10 12:14:31	ga_s2bm_ard_3-2-1_49KGP_2022-08-10_final.stac-item
2022-08-10 12:14:35	ga_s2bm_ard_3-2-1_49JHN_2022-08-10_final.stac-item
2022-08-10 12:14:49	ga_s2bm_ard_3-2-1_49JFN_2022-08-10_final.stac-item
2022-08-11 11:45:09	ga_s2bm_ard_3-2-1_50JPR_2022-08-11_final.stac-item
2022-08-11 11:45:39	ga_s2bm_ard_3-2-1_50JPP_2022-08-11_final.stac-item
2022-08-11 11:45:50	ga_s2bm_ard_3-2-1_50JQN_2022-08-11_final.stac-item
2022-08-12 11:13:32	ga_s2bm_ard_3-2-1_51KZS_2022-08-12_final.stac-item
2022-08-12 11:14:01	ga_s2bm_ard_3-2-1_52KEU_2022-08-12_final.stac-item
2022-08-12 11:16:47	ga_s2bm_ard_3-2-1_51HWD_2022-08-12_final.stac-item
2022-08-13 10:43:58	ga_s2bm_ard_3-2-1_53KMP_2022-08-13_final.stac-item
2022-08-14 11:55:23	ga_s2bm_ard_3-2-1_50JNQ_2022-08-14_final.stac-item
2022-08-14 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2022-08-14_final.stac-item
2022-08-14 11:55:42	ga_s2bm_ard_3-2-1_50JMP_2022-08-14_final.stac-item
2022-08-15 11:23:42	ga_s2bm_ard_3-2-1_51KYR_2022-08-15_final.stac-item
2022-08-15 11:25:27	ga_s2bm_ard_3-2-1_51JXJ_2022-08-15_final.stac-item
2022-08-15 11:26:08	ga_s2bm_ard_3-2-1_51JUG_2022-08-15_final.stac-item
2022-08-15 11:26:25	ga_s2bm_ard_3-2-1_51HXE_2022-08-15_final.stac-item
2022-08-16 10:53:02	ga_s2bm_ard_3-2-1_53KKT_2022-08-16_final.stac-item
2022-08-16 10:53:09	ga_s2bm_ard_3-2-1_53KMS_2022-08-16_final.stac-item
2022-08-16 10:53:13	ga_s2bm_ard_3-2-1_53KLS_2022-08-16_final.stac-item
2022-08-16 10:54:36	ga_s2bm_ard_3-2-1_52JFS_2022-08-16_final.stac-item
2022-08-16 10:55:16	ga_s2bm_ard_3-2-1_52JGP_2022-08-16_final.stac-item
2022-08-17 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2022-08-17_final.stac-item
2022-08-17 12:04:16	ga_s2bm_ard_3-2-1_49KHQ_2022-08-17_final.stac-item
2022-08-17 12:04:21	ga_s2bm_ard_3-2-1_49KGQ_2022-08-17_final.stac-item
2022-08-17 12:04:30	ga_s2bm_ard_3-2-1_49KHP_2022-08-17_final.stac-item
2022-08-17 12:04:34	ga_s2bm_ard_3-2-1_49KGP_2022-08-17_final.stac-item
2022-08-17 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-08-17_final.stac-item
2022-08-17 12:04:46	ga_s2bm_ard_3-2-1_50JLS_2022-08-17_final.stac-item
2022-08-17 12:04:47	ga_s2bm_ard_3-2-1_50JLT_2022-08-17_final.stac-item
2022-08-17 12:05:54	ga_s2bm_ard_3-2-1_50JLN_2022-08-17_final.stac-item
2022-08-18 11:35:47	ga_s2bm_ard_3-2-1_51JUH_2022-08-18_final.stac-item
2022-08-18 11:35:50	ga_s2bm_ard_3-2-1_51JTH_2022-08-18_final.stac-item
2022-08-18 11:35:52	ga_s2bm_ard_3-2-1_50JQN_2022-08-18_final.stac-item
2022-08-18 11:36:01	ga_s2bm_ard_3-2-1_51JUG_2022-08-18_final.stac-item
2022-08-19 11:02:56	ga_s2bm_ard_3-2-1_53KKT_2022-08-19_final.stac-item
2022-08-19 11:02:57	ga_s2bm_ard_3-2-1_52KHC_2022-08-19_final.stac-item
2022-08-19 11:04:45	ga_s2bm_ard_3-2-1_52JFR_2022-08-19_final.stac-item
2022-08-20 10:31:29	ga_s2bm_ard_3-2-1_54LVH_2022-08-20_final.stac-item
2022-08-20 12:13:41	ga_s2bm_ard_3-2-1_50KKB_2022-08-20_final.stac-item
2022-08-20 12:13:56	ga_s2bm_ard_3-2-1_50KKA_2022-08-20_final.stac-item
2022-08-20 12:14:00	ga_s2bm_ard_3-2-1_49KGR_2022-08-20_final.stac-item
2022-08-20 12:14:43	ga_s2bm_ard_3-2-1_49JGN_2022-08-20_final.stac-item
2022-08-21 11:45:48	ga_s2bm_ard_3-2-1_50JQN_2022-08-21_final.stac-item
2022-08-21 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2022-08-21_final.stac-item
2022-08-22 11:13:45	ga_s2bm_ard_3-2-1_52KEV_2022-08-22_final.stac-item
2022-08-23 10:43:27	ga_s2bm_ard_3-2-1_53KMR_2022-08-23_final.stac-item
2022-08-23 10:43:46	ga_s2bm_ard_3-2-1_53KLQ_2022-08-23_final.stac-item
2022-08-23 10:45:30	ga_s2bm_ard_3-2-1_53JKH_2022-08-23_final.stac-item
2022-08-24 10:10:51	ga_s2bm_ard_3-2-1_55LCE_2022-08-24_final.stac-item
2022-08-24 11:55:10	ga_s2bm_ard_3-2-1_50JMR_2022-08-24_final.stac-item
2022-08-24 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2022-08-24_final.stac-item
2022-08-24 11:55:27	ga_s2bm_ard_3-2-1_50JPP_2022-08-24_final.stac-item
2022-08-24 11:55:39	ga_s2bm_ard_3-2-1_50JMP_2022-08-24_final.stac-item
2022-08-24 11:55:57	ga_s2bm_ard_3-2-1_50JLN_2022-08-24_final.stac-item
2022-08-25 11:25:10	ga_s2bm_ard_3-2-1_51JXK_2022-08-25_final.stac-item
2022-08-25 11:26:15	ga_s2bm_ard_3-2-1_51JVF_2022-08-25_final.stac-item
2022-08-25 11:26:40	ga_s2bm_ard_3-2-1_51HWD_2022-08-25_final.stac-item
2022-08-26 10:53:25	ga_s2bm_ard_3-2-1_53KLR_2022-08-26_final.stac-item
2022-08-26 10:53:28	ga_s2bm_ard_3-2-1_53KKR_2022-08-26_final.stac-item
2022-08-26 10:54:08	ga_s2bm_ard_3-2-1_53JLN_2022-08-26_final.stac-item
2022-08-26 10:54:12	ga_s2bm_ard_3-2-1_53JKN_2022-08-26_final.stac-item
2022-08-26 10:54:52	ga_s2bm_ard_3-2-1_53JLK_2022-08-26_final.stac-item
2022-08-27 12:03:59	ga_s2bm_ard_3-2-1_50KKA_2022-08-27_final.stac-item
2022-08-27 12:04:14	ga_s2bm_ard_3-2-1_49KHQ_2022-08-27_final.stac-item
2022-08-27 12:04:28	ga_s2bm_ard_3-2-1_49KHP_2022-08-27_final.stac-item
2022-08-27 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2022-08-27_final.stac-item

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