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
2022-08-14 11:55:16	ga_s2bm_ard_3-2-1_50JLR_2022-08-14_final.stac-item
2022-08-17 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2022-08-17_final.stac-item
2022-09-01 11:14:39	ga_s2bm_ard_3-2-1_51JZM_2022-09-01_final.stac-item
2022-09-01 11:15:26	ga_s2bm_ard_3-2-1_51JYJ_2022-09-01_final.stac-item
2022-09-03 11:55:51	ga_s2bm_ard_3-2-1_50JNN_2022-09-03_final.stac-item
2022-09-03 11:55:58	ga_s2bm_ard_3-2-1_50JLN_2022-09-03_final.stac-item
2022-09-04 11:24:46	ga_s2bm_ard_3-2-1_51JWM_2022-09-04_final.stac-item
2022-09-04 11:25:00	ga_s2bm_ard_3-2-1_51JWL_2022-09-04_final.stac-item
2022-09-04 11:25:05	ga_s2bm_ard_3-2-1_51JVL_2022-09-04_final.stac-item
2022-09-06 12:04:46	ga_s2bm_ard_3-2-1_50JLT_2022-09-06_final.stac-item
2022-09-06 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2022-09-06_final.stac-item
2022-09-07 11:34:56	ga_s2bm_ard_3-2-1_51JWL_2022-09-07_final.stac-item
2022-09-09 12:13:42	ga_s2bm_ard_3-2-1_50KKB_2022-09-09_final.stac-item
2022-09-09 12:13:56	ga_s2bm_ard_3-2-1_49KHR_2022-09-09_final.stac-item
2022-09-09 12:14:33	ga_s2bm_ard_3-2-1_49JHN_2022-09-09_final.stac-item
2022-09-13 11:54:57	ga_s2bm_ard_3-2-1_50JMS_2022-09-13_final.stac-item
2022-09-13 11:55:51	ga_s2bm_ard_3-2-1_50JNN_2022-09-13_final.stac-item
2022-09-14 11:25:05	ga_s2bm_ard_3-2-1_51JVL_2022-09-14_final.stac-item
2022-09-16 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2022-09-16_final.stac-item
2022-09-16 12:04:41	ga_s2bm_ard_3-2-1_50JKT_2022-09-16_final.stac-item
2022-09-16 12:04:46	ga_s2bm_ard_3-2-1_50JLT_2022-09-16_final.stac-item
2022-09-17 11:34:45	ga_s2bm_ard_3-2-1_51JVM_2022-09-17_final.stac-item
2022-09-17 11:35:00	ga_s2bm_ard_3-2-1_51JVL_2022-09-17_final.stac-item
2022-09-17 11:35:50	ga_s2bm_ard_3-2-1_51JTH_2022-09-17_final.stac-item
2022-09-20 11:44:50	ga_s2bm_ard_3-2-1_50JQS_2022-09-20_final.stac-item
2022-09-20 11:44:54	ga_s2bm_ard_3-2-1_50JPS_2022-09-20_final.stac-item
2022-09-23 11:55:14	ga_s2bm_ard_3-2-1_50JLR_2022-09-23_final.stac-item
2022-10-01 11:14:23	ga_s2bm_ard_3-2-1_51JZN_2022-10-01_final.stac-item
2022-10-03 11:55:48	ga_s2bm_ard_3-2-1_50JNN_2022-10-03_final.stac-item
2022-10-03 11:56:10	ga_s2bm_ard_3-2-1_50JLM_2022-10-03_final.stac-item
2022-10-03 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2022-10-03_final.stac-item
2022-10-04 11:25:58	ga_s2bm_ard_3-2-1_51JVG_2022-10-04_final.stac-item
2022-10-04 11:26:13	ga_s2bm_ard_3-2-1_51JVF_2022-10-04_final.stac-item
2022-10-06 12:04:08	ga_s2bm_ard_3-2-1_50KLV_2022-10-06_final.stac-item
2022-10-06 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2022-10-06_final.stac-item
2022-10-07 11:32:59	ga_s2bm_ard_3-2-1_51KVU_2022-10-07_final.stac-item
2022-10-07 11:33:57	ga_s2bm_ard_3-2-1_51KVQ_2022-10-07_final.stac-item
2022-10-07 11:34:26	ga_s2bm_ard_3-2-1_51JVN_2022-10-07_final.stac-item
2022-10-07 11:34:40	ga_s2bm_ard_3-2-1_51JVM_2022-10-07_final.stac-item
2022-10-07 11:34:52	ga_s2bm_ard_3-2-1_51JWL_2022-10-07_final.stac-item
2022-10-07 11:36:00	ga_s2bm_ard_3-2-1_51JTG_2022-10-07_final.stac-item
2022-10-07 11:36:07	ga_s2bm_ard_3-2-1_51JVF_2022-10-07_final.stac-item
2022-10-07 11:36:11	ga_s2bm_ard_3-2-1_51JUF_2022-10-07_final.stac-item
2022-10-07 11:36:25	ga_s2bm_ard_3-2-1_51HUE_2022-10-07_final.stac-item
2022-10-09 12:13:52	ga_s2bm_ard_3-2-1_49KHR_2022-10-09_final.stac-item
2022-10-10 11:42:40	ga_s2bm_ard_3-2-1_51KVV_2022-10-10_final.stac-item
2022-10-10 11:42:55	ga_s2bm_ard_3-2-1_51KVU_2022-10-10_final.stac-item
2022-10-10 11:46:32	ga_s2bm_ard_3-2-1_50HPK_2022-10-10_final.stac-item
2022-10-10 11:46:46	ga_s2bm_ard_3-2-1_50HPJ_2022-10-10_final.stac-item
2022-10-11 11:16:39	ga_s2bm_ard_3-2-1_51HXD_2022-10-11_final.stac-item
2022-10-13 11:56:53	ga_s2bm_ard_3-2-1_50HLJ_2022-10-13_final.stac-item
2022-10-14 11:24:18	ga_s2bm_ard_3-2-1_51JZN_2022-10-14_final.stac-item
2022-10-14 11:24:31	ga_s2bm_ard_3-2-1_51JZM_2022-10-14_final.stac-item
2022-10-14 11:24:58	ga_s2bm_ard_3-2-1_51JWL_2022-10-14_final.stac-item
2022-10-14 11:25:23	ga_s2bm_ard_3-2-1_51JXJ_2022-10-14_final.stac-item
2022-10-14 11:25:33	ga_s2bm_ard_3-2-1_51JYH_2022-10-14_final.stac-item
2022-10-14 11:26:13	ga_s2bm_ard_3-2-1_51JVF_2022-10-14_final.stac-item
2022-10-16 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2022-10-16_final.stac-item
2022-10-16 12:04:42	ga_s2bm_ard_3-2-1_50JMS_2022-10-16_final.stac-item
2022-10-16 12:04:45	ga_s2bm_ard_3-2-1_50JKT_2022-10-16_final.stac-item
2022-10-16 12:05:07	ga_s2bm_ard_3-2-1_50JLR_2022-10-16_final.stac-item
2022-10-17 11:33:59	ga_s2bm_ard_3-2-1_51KVQ_2022-10-17_final.stac-item
2022-10-17 11:34:42	ga_s2bm_ard_3-2-1_51JVM_2022-10-17_final.stac-item
2022-10-17 11:35:47	ga_s2bm_ard_3-2-1_51JTH_2022-10-17_final.stac-item
2022-10-17 11:35:55	ga_s2bm_ard_3-2-1_51JVG_2022-10-17_final.stac-item
2022-10-17 11:36:02	ga_s2bm_ard_3-2-1_51JTG_2022-10-17_final.stac-item
2022-10-17 11:36:09	ga_s2bm_ard_3-2-1_51JVF_2022-10-17_final.stac-item
2022-10-17 11:36:28	ga_s2bm_ard_3-2-1_51HUE_2022-10-17_final.stac-item
2022-10-17 11:37:00	ga_s2bm_ard_3-2-1_51HTC_2022-10-17_final.stac-item
2022-10-19 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2022-10-19_final.stac-item
2022-10-19 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2022-10-19_final.stac-item
2022-10-19 12:14:59	ga_s2bm_ard_3-2-1_49JFM_2022-10-19_final.stac-item
2022-10-19 12:15:10	ga_s2bm_ard_3-2-1_49JGL_2022-10-19_final.stac-item
2022-10-20 11:42:30	ga_s2bm_ard_3-2-1_51KUA_2022-10-20_final.stac-item
2022-10-20 11:44:30	ga_s2bm_ard_3-2-1_51JTN_2022-10-20_final.stac-item
2022-10-20 11:45:53	ga_s2bm_ard_3-2-1_50JNN_2022-10-20_final.stac-item
2022-10-20 11:46:29	ga_s2bm_ard_3-2-1_50HQK_2022-10-20_final.stac-item
2022-10-20 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2022-10-20_final.stac-item
2022-10-20 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2022-10-20_final.stac-item
2022-10-23 11:54:36	ga_s2bm_ard_3-2-1_50JNT_2022-10-23_final.stac-item
2022-10-23 11:54:54	ga_s2bm_ard_3-2-1_50JMS_2022-10-23_final.stac-item
2022-10-23 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2022-10-23_final.stac-item
2022-10-23 11:55:46	ga_s2bm_ard_3-2-1_50JKP_2022-10-23_final.stac-item
2022-10-23 11:56:50	ga_s2bm_ard_3-2-1_50HMJ_2022-10-23_final.stac-item
2022-10-24 11:24:18	ga_s2bm_ard_3-2-1_51JZN_2022-10-24_final.stac-item
2022-10-24 11:25:23	ga_s2bm_ard_3-2-1_51JXJ_2022-10-24_final.stac-item
2022-10-24 11:25:33	ga_s2bm_ard_3-2-1_51JYH_2022-10-24_final.stac-item
2022-10-24 11:25:59	ga_s2bm_ard_3-2-1_51JVG_2022-10-24_final.stac-item
2022-10-24 11:26:32	ga_s2bm_ard_3-2-1_51HUE_2022-10-24_final.stac-item
2022-10-24 11:26:39	ga_s2bm_ard_3-2-1_51HWD_2022-10-24_final.stac-item
2022-10-26 12:04:21	ga_s2bm_ard_3-2-1_50KMU_2022-10-26_final.stac-item
2022-10-26 12:04:38	ga_s2bm_ard_3-2-1_50JLT_2022-10-26_final.stac-item
2022-10-26 12:05:51	ga_s2bm_ard_3-2-1_50JLN_2022-10-26_final.stac-item
2022-10-27 11:33:59	ga_s2bm_ard_3-2-1_51KVQ_2022-10-27_final.stac-item
2022-10-27 11:34:16	ga_s2bm_ard_3-2-1_51KUP_2022-10-27_final.stac-item
2022-10-27 11:34:42	ga_s2bm_ard_3-2-1_51JVM_2022-10-27_final.stac-item
2022-10-27 11:34:53	ga_s2bm_ard_3-2-1_51JWL_2022-10-27_final.stac-item
2022-10-27 11:35:55	ga_s2bm_ard_3-2-1_51JVG_2022-10-27_final.stac-item
2022-10-27 11:36:09	ga_s2bm_ard_3-2-1_51JVF_2022-10-27_final.stac-item
2022-10-27 11:36:13	ga_s2bm_ard_3-2-1_51JUF_2022-10-27_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

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