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 11:45:41	ga_s2bm_ard_3-2-1_50JPP_2022-08-01_final.stac-item
2022-08-07 12:05:27	ga_s2bm_ard_3-2-1_50JLQ_2022-08-07_final.stac-item
2022-08-31 11:45:51	ga_s2bm_ard_3-2-1_50JPN_2022-08-31_final.stac-item
2022-09-03 11:55:29	ga_s2bm_ard_3-2-1_50JLQ_2022-09-03_final.stac-item
2022-09-03 11:55:51	ga_s2bm_ard_3-2-1_50JNN_2022-09-03_final.stac-item
2022-09-06 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2022-09-06_final.stac-item
2022-09-06 12:04:15	ga_s2bm_ard_3-2-1_49KHQ_2022-09-06_final.stac-item
2022-09-06 12:04:45	ga_s2bm_ard_3-2-1_50JMS_2022-09-06_final.stac-item
2022-09-07 11:35:21	ga_s2bm_ard_3-2-1_51JWJ_2022-09-07_final.stac-item
2022-09-07 11:35:28	ga_s2bm_ard_3-2-1_51JVJ_2022-09-07_final.stac-item
2022-09-07 11:35:43	ga_s2bm_ard_3-2-1_51JVH_2022-09-07_final.stac-item
2022-09-09 12:14:11	ga_s2bm_ard_3-2-1_49KHQ_2022-09-09_final.stac-item
2022-09-09 12:14:15	ga_s2bm_ard_3-2-1_49KGQ_2022-09-09_final.stac-item
2022-09-09 12:14:21	ga_s2bm_ard_3-2-1_50KKU_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
2022-09-10 11:44:47	ga_s2bm_ard_3-2-1_51JTM_2022-09-10_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 11:55:44	ga_s2bm_ard_3-2-1_50JLP_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 11:25:48	ga_s2bm_ard_3-2-1_51JVH_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 12:04:15	ga_s2bm_ard_3-2-1_50KKV_2022-09-16_final.stac-item
2022-09-16 12:04:15	ga_s2bm_ard_3-2-1_49KHQ_2022-09-16_final.stac-item
2022-09-16 12:04:33	ga_s2bm_ard_3-2-1_49KGP_2022-09-16_final.stac-item
2022-09-17 11:35:17	ga_s2bm_ard_3-2-1_51JUK_2022-09-17_final.stac-item
2022-09-19 12:14:10	ga_s2bm_ard_3-2-1_49KHQ_2022-09-19_final.stac-item
2022-09-20 11:45:01	ga_s2bm_ard_3-2-1_51JTL_2022-09-20_final.stac-item
2022-09-20 11:45:37	ga_s2bm_ard_3-2-1_50JPP_2022-09-20_final.stac-item
2022-09-23 11:54:56	ga_s2bm_ard_3-2-1_50JMS_2022-09-23_final.stac-item
2022-09-26 12:04:14	ga_s2bm_ard_3-2-1_50KKV_2022-09-26_final.stac-item
2022-09-26 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2022-09-26_final.stac-item
2022-09-29 12:14:19	ga_s2bm_ard_3-2-1_50KKU_2022-09-29_final.stac-item
2022-09-30 11:44:45	ga_s2bm_ard_3-2-1_51JTM_2022-09-30_final.stac-item
2022-09-30 11:44:59	ga_s2bm_ard_3-2-1_51JTL_2022-09-30_final.stac-item
2022-10-01 11:16:43	ga_s2bm_ard_3-2-1_51HWD_2022-10-01_final.stac-item
2022-10-03 11:52:57	ga_s2bm_ard_3-2-1_50KRD_2022-10-03_final.stac-item
2022-10-03 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2022-10-03_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 11:55:51	ga_s2bm_ard_3-2-1_50JMN_2022-10-03_final.stac-item
2022-10-03 11:56:03	ga_s2bm_ard_3-2-1_50JNM_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 11:25:11	ga_s2bm_ard_3-2-1_51JWK_2022-10-04_final.stac-item
2022-10-04 11:25:29	ga_s2bm_ard_3-2-1_51JVJ_2022-10-04_final.stac-item
2022-10-04 11:27:00	ga_s2bm_ard_3-2-1_51HUC_2022-10-04_final.stac-item
2022-10-06 12:04:11	ga_s2bm_ard_3-2-1_49KHQ_2022-10-06_final.stac-item
2022-10-06 12:04:29	ga_s2bm_ard_3-2-1_49KGP_2022-10-06_final.stac-item
2022-10-06 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2022-10-06_final.stac-item
2022-10-07 11:34:46	ga_s2bm_ard_3-2-1_50JRS_2022-10-07_final.stac-item
2022-10-07 11:35:13	ga_s2bm_ard_3-2-1_51JUK_2022-10-07_final.stac-item
2022-10-07 11:35:16	ga_s2bm_ard_3-2-1_51JWJ_2022-10-07_final.stac-item
2022-10-07 11:35:27	ga_s2bm_ard_3-2-1_51JUJ_2022-10-07_final.stac-item
2022-10-07 11:36:40	ga_s2bm_ard_3-2-1_51HUD_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 11:43:02	ga_s2bm_ard_3-2-1_50KRD_2022-10-10_final.stac-item
2022-10-10 11:44:14	ga_s2bm_ard_3-2-1_50KRU_2022-10-10_final.stac-item
2022-10-10 11:44:21	ga_s2bm_ard_3-2-1_50KPU_2022-10-10_final.stac-item
2022-10-10 11:44:43	ga_s2bm_ard_3-2-1_51JTM_2022-10-10_final.stac-item
2022-10-10 11:44:49	ga_s2bm_ard_3-2-1_51JUL_2022-10-10_final.stac-item
2022-10-10 11:45:59	ga_s2bm_ard_3-2-1_50JQM_2022-10-10_final.stac-item
2022-10-10 11:46:11	ga_s2bm_ard_3-2-1_50JMM_2022-10-10_final.stac-item
2022-10-10 11:46:13	ga_s2bm_ard_3-2-1_50JQL_2022-10-10_final.stac-item
2022-10-10 11:46:54	ga_s2bm_ard_3-2-1_50HMJ_2022-10-10_final.stac-item
2022-10-13 11:54:03	ga_s2bm_ard_3-2-1_50KPV_2022-10-13_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 11:25:27	ga_s2bm_ard_3-2-1_51JWJ_2022-10-14_final.stac-item
2022-10-14 11:25:30	ga_s2bm_ard_3-2-1_51JVJ_2022-10-14_final.stac-item
2022-10-14 11:25:45	ga_s2bm_ard_3-2-1_51JVH_2022-10-14_final.stac-item
2022-10-14 11:26:21	ga_s2bm_ard_3-2-1_51HXE_2022-10-14_final.stac-item
2022-10-16 12:04:06	ga_s2bm_ard_3-2-1_50KMV_2022-10-16_final.stac-item
2022-10-16 12:04:27	ga_s2bm_ard_3-2-1_50KKU_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
2022-10-17 11:35:29	ga_s2bm_ard_3-2-1_51JUJ_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 12:14:26	ga_s2bm_ard_3-2-1_49KGP_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
2022-10-19 12:15:19	ga_s2bm_ard_3-2-1_49JGK_2022-10-19_final.stac-item
2022-10-20 11:45:50	ga_s2bm_ard_3-2-1_50JPN_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 11:46:04	ga_s2bm_ard_3-2-1_50JPM_2022-10-20_final.stac-item
2022-10-20 11:46:12	ga_s2bm_ard_3-2-1_50JMM_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 11:52:58	ga_s2bm_ard_3-2-1_50KRD_2022-10-23_final.stac-item
2022-10-23 11:54:04	ga_s2bm_ard_3-2-1_50KPV_2022-10-23_final.stac-item
2022-10-23 11:54:16	ga_s2bm_ard_3-2-1_50KPU_2022-10-23_final.stac-item
2022-10-23 11:54:27	ga_s2bm_ard_3-2-1_50KMU_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 11:56:07	ga_s2bm_ard_3-2-1_50JMM_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 11:26:39	ga_s2bm_ard_3-2-1_51HWD_2022-10-24_final.stac-item
2022-10-26 12:04:06	ga_s2bm_ard_3-2-1_50KMV_2022-10-26_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 12:05:11	ga_s2bm_ard_3-2-1_50JKR_2022-10-26_final.stac-item
2022-10-26 12:05:41	ga_s2bm_ard_3-2-1_50JLP_2022-10-26_final.stac-item
2022-10-27 11:35:03	ga_s2bm_ard_3-2-1_51JTL_2022-10-27_final.stac-item
2022-10-27 11:35:18	ga_s2bm_ard_3-2-1_51JWJ_2022-10-27_final.stac-item
2022-10-27 11:35:26	ga_s2bm_ard_3-2-1_51JVJ_2022-10-27_final.stac-item
2022-10-27 11:36:47	ga_s2bm_ard_3-2-1_50HQJ_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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