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
2017-07-14 12:03:48	ga_s2bm_ard_3-2-1_50KMA_2017-07-14_final.stac-item
2017-07-14 12:03:48	ga_s2bm_ard_3-2-1_50KMV_2017-07-14_final.stac-item
2017-07-21 11:56:07	ga_s2bm_ard_3-2-1_50HMK_2017-07-21_final.stac-item
2017-07-21 11:56:07	ga_s2bm_ard_3-2-1_50JML_2017-07-21_final.stac-item
2017-07-21 11:56:07	ga_s2bm_ard_3-2-1_50JMM_2017-07-21_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50HMH_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50HMJ_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50HMK_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JML_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JMM_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JMN_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JMP_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JMQ_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JMR_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JMS_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JMT_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KMA_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KMU_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KMV_2017-12-28_final.stac-item
2018-02-23 11:44:25	ga_s2bm_ard_3-2-1_50HMH_2018-02-23_final.stac-item
2018-02-23 11:44:25	ga_s2bm_ard_3-2-1_50HMJ_2018-02-23_final.stac-item
2018-02-23 11:44:25	ga_s2bm_ard_3-2-1_50HMK_2018-02-23_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50JMT_2018-03-11_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50KMA_2018-03-11_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50KMB_2018-03-11_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50KMC_2018-03-11_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50KMU_2018-03-11_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50KMV_2018-03-11_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50HMH_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50HMJ_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50HMK_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JML_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JMM_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JMN_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JMP_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JMQ_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JMR_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JMS_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JMT_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50KMA_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50KMU_2018-03-18_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50KMV_2018-03-18_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JMT_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KMA_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KMB_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KMC_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KMU_2018-03-21_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50KMV_2018-03-21_final.stac-item
2018-06-03 11:46:44	ga_s2bm_ard_3-2-1_50HMH_2018-06-03_final.stac-item
2018-06-03 11:46:44	ga_s2bm_ard_3-2-1_50HMJ_2018-06-03_final.stac-item
2018-06-13 11:43:22	ga_s2bm_ard_3-2-1_50HMH_2018-06-13_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_50JMT_2018-06-19_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_50KMA_2018-06-19_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_50KMB_2018-06-19_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_50KMC_2018-06-19_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_50KMU_2018-06-19_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_50KMV_2018-06-19_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50HMH_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50HMJ_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50HMK_2018-06-23_final.stac-item
2018-07-19 12:02:47	ga_s2bm_ard_3-2-1_50KMB_2018-07-19_final.stac-item
2018-07-19 12:02:47	ga_s2bm_ard_3-2-1_50KMC_2018-07-19_final.stac-item
2019-08-30 11:54:00	ga_s2bm_ard_3-2-1_50KMA_2019-08-30_final.stac-item
2019-08-30 11:54:15	ga_s2bm_ard_3-2-1_50KMV_2019-08-30_final.stac-item
2019-08-30 11:54:30	ga_s2bm_ard_3-2-1_50KMU_2019-08-30_final.stac-item
2019-08-30 11:54:44	ga_s2bm_ard_3-2-1_50JMT_2019-08-30_final.stac-item
2019-08-30 11:54:59	ga_s2bm_ard_3-2-1_50JMS_2019-08-30_final.stac-item
2019-08-30 11:55:13	ga_s2bm_ard_3-2-1_50JMR_2019-08-30_final.stac-item
2019-08-30 11:55:28	ga_s2bm_ard_3-2-1_50JMQ_2019-08-30_final.stac-item
2019-08-30 11:55:42	ga_s2bm_ard_3-2-1_50JMP_2019-08-30_final.stac-item
2019-08-30 11:55:57	ga_s2bm_ard_3-2-1_50JMN_2019-08-30_final.stac-item
2019-08-30 11:56:11	ga_s2bm_ard_3-2-1_50JMM_2019-08-30_final.stac-item
2019-08-30 11:56:26	ga_s2bm_ard_3-2-1_50JML_2019-08-30_final.stac-item
2019-08-30 11:56:40	ga_s2bm_ard_3-2-1_50HMK_2019-08-30_final.stac-item
2019-08-30 11:56:55	ga_s2bm_ard_3-2-1_50HMJ_2019-08-30_final.stac-item
2019-08-30 11:57:10	ga_s2bm_ard_3-2-1_50HMH_2019-08-30_final.stac-item
2023-03-28 12:10:33	ga_s2bm_ard_3-2-1_50LMP_2023-03-28_nrt
2023-04-01 11:54:44	ga_s2bm_ard_3-2-1_50JMT_2023-04-01_final
2023-04-01 11:54:58	ga_s2bm_ard_3-2-1_50JMS_2023-04-01_final
2023-04-01 11:55:13	ga_s2bm_ard_3-2-1_50JMR_2023-04-01_final
2023-04-01 11:55:27	ga_s2bm_ard_3-2-1_50JMQ_2023-04-01_final
2023-04-01 11:55:42	ga_s2bm_ard_3-2-1_50JMP_2023-04-01_final
2023-04-01 11:55:56	ga_s2bm_ard_3-2-1_50JMN_2023-04-01_final
2023-04-01 11:56:11	ga_s2bm_ard_3-2-1_50JMM_2023-04-01_final
2023-04-01 11:56:25	ga_s2bm_ard_3-2-1_50JML_2023-04-01_final
2023-04-01 11:56:40	ga_s2bm_ard_3-2-1_50HMK_2023-04-01_final
2023-04-01 11:56:54	ga_s2bm_ard_3-2-1_50HMJ_2023-04-01_final
2023-04-01 11:57:09	ga_s2bm_ard_3-2-1_50HMH_2023-04-01_final
2023-04-01 11:57:24	ga_s2bm_ard_3-2-1_50HMG_2023-04-01_final
2023-04-04 12:01:15	ga_s2bm_ard_3-2-1_50LMM_2023-04-04_nrt
2023-04-04 12:01:30	ga_s2bm_ard_3-2-1_50LML_2023-04-04_nrt
2023-04-04 12:01:42	ga_s2bm_ard_3-2-1_50LMK_2023-04-04_nrt
2023-04-04 12:03:01	ga_s2bm_ard_3-2-1_50KME_2023-04-04_nrt
2023-04-04 12:03:12	ga_s2bm_ard_3-2-1_50KMD_2023-04-04_nrt
2023-04-04 12:03:26	ga_s2bm_ard_3-2-1_50KMC_2023-04-04_final
2023-04-04 12:03:41	ga_s2bm_ard_3-2-1_50KMB_2023-04-04_final
2023-04-04 12:03:55	ga_s2bm_ard_3-2-1_50KMA_2023-04-04_final
2023-04-04 12:04:10	ga_s2bm_ard_3-2-1_50KMV_2023-04-04_final
2023-04-04 12:04:25	ga_s2bm_ard_3-2-1_50KMU_2023-04-04_final
2023-04-04 12:04:34	ga_s2bm_ard_3-2-1_50JMT_2023-04-04_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

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