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
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50HMH_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50HMJ_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50HMK_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JML_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JMM_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JMN_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JMP_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JMQ_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JMR_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JMS_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JMT_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50KMA_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50KMU_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50KMV_2017-10-19_final.stac-item
2019-06-28 11:46:34	ga_s2bm_ard_3-2-1_50JML_2019-06-28_final.stac-item
2019-06-28 11:46:49	ga_s2bm_ard_3-2-1_50HMK_2019-06-28_final.stac-item
2019-06-28 11:47:04	ga_s2bm_ard_3-2-1_50HMJ_2019-06-28_final.stac-item
2019-06-28 11:47:18	ga_s2bm_ard_3-2-1_50HMH_2019-06-28_final.stac-item
2019-07-01 11:56:31	ga_s2bm_ard_3-2-1_50JML_2019-07-01_final.stac-item
2019-07-01 11:56:45	ga_s2bm_ard_3-2-1_50HMK_2019-07-01_final.stac-item
2019-07-01 11:57:00	ga_s2bm_ard_3-2-1_50HMJ_2019-07-01_final.stac-item
2019-07-01 11:57:14	ga_s2bm_ard_3-2-1_50HMH_2019-07-01_final.stac-item
2019-07-08 11:46:35	ga_s2bm_ard_3-2-1_50JML_2019-07-08_final.stac-item
2019-07-08 11:46:49	ga_s2bm_ard_3-2-1_50HMK_2019-07-08_final.stac-item
2019-07-08 11:47:04	ga_s2bm_ard_3-2-1_50HMJ_2019-07-08_final.stac-item
2019-07-08 11:47:19	ga_s2bm_ard_3-2-1_50HMH_2019-07-08_final.stac-item
2019-07-14 12:03:32	ga_s2bm_ard_3-2-1_50KMC_2019-07-14_final.stac-item
2019-07-14 12:03:46	ga_s2bm_ard_3-2-1_50KMB_2019-07-14_final.stac-item
2019-07-14 12:04:01	ga_s2bm_ard_3-2-1_50KMA_2019-07-14_final.stac-item
2019-07-14 12:04:15	ga_s2bm_ard_3-2-1_50KMV_2019-07-14_final.stac-item
2019-07-14 12:04:30	ga_s2bm_ard_3-2-1_50KMU_2019-07-14_final.stac-item
2019-07-14 12:04:44	ga_s2bm_ard_3-2-1_50JMT_2019-07-14_final.stac-item
2019-09-12 12:03:24	ga_s2bm_ard_3-2-1_50KMC_2019-09-12_final.stac-item
2019-09-12 12:03:38	ga_s2bm_ard_3-2-1_50KMB_2019-09-12_final.stac-item
2019-09-12 12:03:53	ga_s2bm_ard_3-2-1_50KMA_2019-09-12_final.stac-item
2019-09-12 12:04:07	ga_s2bm_ard_3-2-1_50KMV_2019-09-12_final.stac-item
2019-09-12 12:04:22	ga_s2bm_ard_3-2-1_50KMU_2019-09-12_final.stac-item
2019-09-12 12:04:36	ga_s2bm_ard_3-2-1_50JMT_2019-09-12_final.stac-item
2019-09-22 12:04:35	ga_s2bm_ard_3-2-1_50JMT_2019-09-22_final.stac-item
2019-09-29 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2019-09-29_final.stac-item
2019-10-09 11:56:37	ga_s2bm_ard_3-2-1_50HMK_2019-10-09_final.stac-item
2019-10-09 11:56:52	ga_s2bm_ard_3-2-1_50HMJ_2019-10-09_final.stac-item
2019-10-09 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2019-10-09_final.stac-item
2019-10-16 11:46:27	ga_s2bm_ard_3-2-1_50JML_2019-10-16_final.stac-item
2019-10-16 11:46:42	ga_s2bm_ard_3-2-1_50HMK_2019-10-16_final.stac-item
2019-10-16 11:46:57	ga_s2bm_ard_3-2-1_50HMJ_2019-10-16_final.stac-item
2019-10-16 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2019-10-16_final.stac-item
2019-10-16 11:47:18	ga_s2bm_ard_3-2-1_50HMH_2019-10-16_final.stac-item
2019-10-19 11:54:42	ga_s2bm_ard_3-2-1_50JMT_2019-10-19_final.stac-item
2019-10-19 11:54:56	ga_s2bm_ard_3-2-1_50JMS_2019-10-19_final.stac-item
2019-10-19 11:55:11	ga_s2bm_ard_3-2-1_50JMR_2019-10-19_final.stac-item
2019-10-19 11:55:25	ga_s2bm_ard_3-2-1_50JMQ_2019-10-19_final.stac-item
2019-10-19 11:55:40	ga_s2bm_ard_3-2-1_50JMP_2019-10-19_final.stac-item
2019-10-19 11:55:54	ga_s2bm_ard_3-2-1_50JMN_2019-10-19_final.stac-item
2019-10-19 11:56:09	ga_s2bm_ard_3-2-1_50JMM_2019-10-19_final.stac-item
2019-10-19 11:56:23	ga_s2bm_ard_3-2-1_50JML_2019-10-19_final.stac-item
2019-10-19 11:56:38	ga_s2bm_ard_3-2-1_50HMK_2019-10-19_final.stac-item
2019-10-19 11:56:52	ga_s2bm_ard_3-2-1_50HMJ_2019-10-19_final.stac-item
2019-10-22 12:03:24	ga_s2bm_ard_3-2-1_50KMC_2019-10-22_final.stac-item
2019-10-22 12:03:34	ga_s2bm_ard_3-2-1_50KMB_2019-10-22_final.stac-item
2019-10-22 12:03:40	ga_s2bm_ard_3-2-1_50KMB_2019-10-22_final.stac-item
2019-10-22 12:03:53	ga_s2bm_ard_3-2-1_50KMA_2019-10-22_final.stac-item
2019-10-22 12:04:08	ga_s2bm_ard_3-2-1_50KMV_2019-10-22_final.stac-item
2019-10-22 12:04:22	ga_s2bm_ard_3-2-1_50KMU_2019-10-22_final.stac-item
2019-10-22 12:04:37	ga_s2bm_ard_3-2-1_50JMT_2019-10-22_final.stac-item
2019-10-26 11:46:27	ga_s2bm_ard_3-2-1_50JML_2019-10-26_final.stac-item
2019-10-26 11:46:42	ga_s2bm_ard_3-2-1_50HMK_2019-10-26_final.stac-item
2019-10-26 11:46:56	ga_s2bm_ard_3-2-1_50HMJ_2019-10-26_final.stac-item
2019-10-26 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2019-10-26_final.stac-item
2019-11-01 12:03:24	ga_s2bm_ard_3-2-1_50KMC_2019-11-01_final.stac-item
2019-11-01 12:03:38	ga_s2bm_ard_3-2-1_50KMB_2019-11-01_final.stac-item
2019-11-01 12:03:52	ga_s2bm_ard_3-2-1_50KMA_2019-11-01_final.stac-item
2019-11-01 12:04:07	ga_s2bm_ard_3-2-1_50KMV_2019-11-01_final.stac-item
2019-11-01 12:04:22	ga_s2bm_ard_3-2-1_50KMU_2019-11-01_final.stac-item
2019-11-01 12:04:36	ga_s2bm_ard_3-2-1_50JMT_2019-11-01_final.stac-item
2019-11-21 12:03:21	ga_s2bm_ard_3-2-1_50KMC_2019-11-21_final.stac-item
2019-11-21 12:03:35	ga_s2bm_ard_3-2-1_50KMB_2019-11-21_final.stac-item
2019-11-21 12:03:49	ga_s2bm_ard_3-2-1_50KMA_2019-11-21_final.stac-item
2019-11-21 12:04:04	ga_s2bm_ard_3-2-1_50KMV_2019-11-21_final.stac-item
2019-11-21 12:04:19	ga_s2bm_ard_3-2-1_50KMU_2019-11-21_final.stac-item
2019-11-21 12:04:33	ga_s2bm_ard_3-2-1_50JMT_2019-11-21_final.stac-item
2019-11-28 11:53:52	ga_s2bm_ard_3-2-1_50KMA_2019-11-28_final.stac-item
2019-11-28 11:54:07	ga_s2bm_ard_3-2-1_50KMV_2019-11-28_final.stac-item
2019-11-28 11:54:22	ga_s2bm_ard_3-2-1_50KMU_2019-11-28_final.stac-item
2019-11-28 11:54:36	ga_s2bm_ard_3-2-1_50JMT_2019-11-28_final.stac-item
2019-11-28 11:54:51	ga_s2bm_ard_3-2-1_50JMS_2019-11-28_final.stac-item
2019-11-28 11:55:05	ga_s2bm_ard_3-2-1_50JMR_2019-11-28_final.stac-item
2019-11-28 11:55:20	ga_s2bm_ard_3-2-1_50JMQ_2019-11-28_final.stac-item
2019-11-28 11:55:34	ga_s2bm_ard_3-2-1_50JMP_2019-11-28_final.stac-item
2019-11-28 11:55:49	ga_s2bm_ard_3-2-1_50JMN_2019-11-28_final.stac-item
2019-11-28 11:56:03	ga_s2bm_ard_3-2-1_50JMM_2019-11-28_final.stac-item
2019-11-28 11:56:18	ga_s2bm_ard_3-2-1_50JML_2019-11-28_final.stac-item
2019-11-28 11:56:32	ga_s2bm_ard_3-2-1_50HMK_2019-11-28_final.stac-item
2019-11-28 11:56:47	ga_s2bm_ard_3-2-1_50HMJ_2019-11-28_final.stac-item
2019-11-28 11:57:02	ga_s2bm_ard_3-2-1_50HMH_2019-11-28_final.stac-item
2019-12-01 12:03:13	ga_s2bm_ard_3-2-1_50KMC_2019-12-01_final.stac-item
2019-12-01 12:03:20	ga_s2bm_ard_3-2-1_50KMC_2019-12-01_final.stac-item
2019-12-01 12:03:33	ga_s2bm_ard_3-2-1_50KMB_2019-12-01_final.stac-item
2019-12-01 12:03:47	ga_s2bm_ard_3-2-1_50KMA_2019-12-01_final.stac-item
2019-12-01 12:04:01	ga_s2bm_ard_3-2-1_50KMV_2019-12-01_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